May 2017 – jackburnsblog

Optimizing AngularJS Single-Page Applications for Googlebot Crawlers

Posted on May 31, 2017 by jackburnsblog

It’s almost certain that you’ve encountered AngularJS on the web somewhere, even if you weren’t aware of it at the time. Here’s a list of just a few sites using Angular:

Upwork.com
Freelancer.com
Udemy.com
Youtube.com

Any of those look familiar? If so, it’s because AngularJS is taking over the Internet. There’s a good reason for that: Angular- and other React-style frameworks make for a better user and developer experience on a site. For background, AngularJS and ReactJS are part of a web design movement called single-page applications, or SPAs. While a traditional website loads each individual page as the user navigates the site, including calls to the server and cache, loading resources, and rendering the page, SPAs cut out much of the back-end activity by loading the entire site when a user first lands on a page. Instead of loading a new page each time you click on a link, the site dynamically updates a single HTML page as the user interacts with the site.

Image c/o Microsoft

Why is this movement taking over the Internet? With SPAs, users are treated to a screaming fast site through which they can navigate almost instantaneously, while developers have a template that allows them to customize, test, and optimize pages seamlessly and efficiently. AngularJS and ReactJS use advanced Javascript templates to render the site, which means the HTML/CSS page speed overhead is almost nothing. All site activity runs behind the scenes, out of view of the user.

Unfortunately, anyone who’s tried performing SEO on an Angular or React site knows that the site activity is hidden from more than just site visitors: it’s also hidden from web crawlers. Crawlers like Googlebot rely heavily on HTML/CSS data to render and interpret the content on a site. When that HTML content is hidden behind website scripts, crawlers have no website content to index and serve in search results.

Of course, Google claims they can crawl Javascript (and SEOs have tested and supported this claim), but even if that is true, Googlebot still struggles to crawl sites built on a SPA framework. One of the first issues we encountered when a client first approached us with an Angular site was that nothing beyond the homepage was appearing in the SERPs. ScreamingFrog crawls uncovered the homepage and a handful of other Javascript resources, and that was it.

SF Javascript.png

Another common issue is recording Google Analytics data. Think about it: Analytics data is tracked by recording pageviews every time a user navigates to a page. How can you track site analytics when there’s no HTML response to trigger a pageview?

After working with several clients on their SPA websites, we’ve developed a process for performing SEO on those sites. By using this process, we’ve not only enabled SPA sites to be indexed by search engines, but even to rank on the first page for keywords.

5-step solution to SEO for AngularJS

Make a list of all pages on the site
Install Prerender
“Fetch as Google”
Configure Analytics
Recrawl the site

1) Make a list of all pages on your site

If this sounds like a long and tedious process, that’s because it definitely can be. For some sites, this will be as easy as exporting the XML sitemap for the site. For other sites, especially those with hundreds or thousands of pages, creating a comprehensive list of all the pages on the site can take hours or days. However, I cannot emphasize enough how helpful this step has been for us. Having an index of all pages on the site gives you a guide to reference and consult as you work on getting your site indexed. It’s almost impossible to predict every issue that you’re going to encounter with an SPA, and if you don’t have an all-inclusive list of content to reference throughout your SEO optimization, it’s highly likely you’ll leave some part of the site un-indexed by search engines inadvertently.

One solution that might enable you to streamline this process is to divide content into directories instead of individual pages. For example, if you know that you have a list of storeroom pages, include your /storeroom/ directory and make a note of how many pages that includes. Or if you have an e-commerce site, make a note of how many products you have in each shopping category and compile your list that way (though if you have an e-commerce site, I hope for your own sake you have a master list of products somewhere). Regardless of what you do to make this step less time-consuming, make sure you have a full list before continuing to step 2.

2) Install Prerender

Prerender is going to be your best friend when performing SEO for SPAs. Prerender is a service that will render your website in a virtual browser, then serve the static HTML content to web crawlers. From an SEO standpoint, this is as good of a solution as you can hope for: users still get the fast, dynamic SPA experience while search engine crawlers can identify indexable content for search results.

Prerender’s pricing varies based on the size of your site and the freshness of the cache served to Google. Smaller sites (up to 250 pages) can use Prerender for free, while larger sites (or sites that update constantly) may need to pay as much as $200+/month. However, having an indexable version of your site that enables you to attract customers through organic search is invaluable. This is where that list you compiled in step 1 comes into play: if you can prioritize what sections of your site need to be served to search engines, or with what frequency, you may be able to save a little bit of money each month while still achieving SEO progress.

3) “Fetch as Google”

Within Google Search Console is an incredibly useful feature called “Fetch as Google.” “Fetch as Google” allows you to enter a URL from your site and fetch it as Googlebot would during a crawl. “Fetch” returns the HTTP response from the page, which includes a full download of the page source code as Googlebot sees it. “Fetch and Render” will return the HTTP response and will also provide a screenshot of the page as Googlebot saw it and as a site visitor would see it.

This has powerful applications for AngularJS sites. Even with Prerender installed, you may find that Google is still only partially displaying your website, or it may be omitting key features of your site that are helpful to users. Plugging the URL into “Fetch as Google” will let you review how your site appears to search engines and what further steps you may need to take to optimize your keyword rankings. Additionally, after requesting a “Fetch” or “Fetch and Render,” you have the option to “Request Indexing” for that page, which can be handy catalyst for getting your site to appear in search results.

4) Configure Google Analytics (or Google Tag Manager)

As I mentioned above, SPAs can have serious trouble with recording Google Analytics data since they don’t track pageviews the way a standard website does. Instead of the traditional Google Analytics tracking code, you’ll need to install Analytics through some kind of alternative method.

One method that works well is to use the Angulartics plugin. Angulartics replaces standard pageview events with virtual pageview tracking, which tracks the entire user navigation across your application. Since SPAs dynamically load HTML content, these virtual pageviews are recorded based on user interactions with the site, which ultimately tracks the same user behavior as you would through traditional Analytics. Other people have found success using Google Tag Manager “History Change” triggers or other innovative methods, which are perfectly acceptable implementations. As long as your Google Analytics tracking records user interactions instead of conventional pageviews, your Analytics configuration should suffice.

5) Recrawl the site

After working through steps 1–4, you’re going to want to crawl the site yourself to find those errors that not even Googlebot was anticipating. One issue we discovered early with a client was that after installing Prerender, our crawlers were still running into a spider trap:

As you can probably tell, there were not actually 150,000 pages on that particular site. Our crawlers just found a recursive loop that kept generating longer and longer URL strings for the site content. This is something we would not have found in Google Search Console or Analytics. SPAs are notorious for causing tedious, inexplicable issues that you’ll only uncover by crawling the site yourself. Even if you follow the steps above and take as many precautions as possible, I can still almost guarantee you will come across a unique issue that can only be diagnosed through a crawl.

If you’ve come across any of these unique issues, let me know in the comments! I’d love to hear what other issues people have encountered with SPAs.

Results

As I mentioned earlier in the article, the process outlined above has enabled us to not only get client sites indexed, but even to get those sites ranking on first page for various keywords. Here’s an example of the keyword progress we made for one client with an AngularJS site:

Also, the organic traffic growth for that client over the course of seven months:

All of this goes to show that although SEO for SPAs can be tedious, laborious, and troublesome, it is not impossible. Follow the steps above, and you can have SEO success with your single-page app website.

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No, Paid Search Audiences Won’t Replace Keywords

Posted on May 30, 2017 by jackburnsblog

Posted by PPCKirk

I have been chewing on a keyword vs. audience targeting post for roughly two years now. In that time we have seen audience targeting grow in popularity (as expected) and depth.

“Popularity” is somewhat of an understatement here. I would go so far as to say that I’ve heard it lauded in messianic-like “thy kingdom come, thy will be done” reverential awe by some paid search marketers. as if paid search were lacking a heartbeat before the life-giving audience targeting had arrived and 1-2-3-clear’ed it into relevance.

However, I would argue that despite audience targeting’s popularity (and understandable success), we have also seen the revelation of some weaknesses as well. It turns out it’s not quite the heroic, rescue-the-captives targeting method paid searchers had hoped it would be.

The purpose of this post is to argue against the notion that audience targeting can replace the keyword in paid search.

Now, before we get into the throes of keyword philosophy, I’d like to reduce the number of angry comments this post receives by acknowledging a crucial point.

It is not my intention in any way to set up a false dichotomy. Yes, I believe the keyword is still the most valuable form of targeting for a paid search marketer, but I also believe that audience targeting can play a valuable complementary role in search bidding.

In fact, as I think about it, I would argue that I am writing this post in response to what I have heard become a false dichotomy. That is, that audience targeting is better than keyword targeting and will eventually replace it.

I disagree with this idea vehemently, as I will demonstrate in the rest of this article.

One seasoned (age, not steak) traditional marketer’s point of view

The best illustration I’ve heard on the core weakness of audience targeting was from an older traditional marketer who has probably never accessed the Keyword Planner in his life.

“I have two teenage daughters.” He revealed, with no small amount of pride.

“They are within 18 months of each other, so in age demographic targeting they are the same person.”

“They are both young women, so in gender demographic targeting they are the same person.”

“They are both my daughters in my care, so in income demographic targeting they are the same person.”

“They are both living in my house, so in geographical targeting they are the same person.”

“They share the same friends, so in social targeting they are the same person.”

“However, in terms of personality, they couldn’t be more different. One is artistic and enjoys heels and dresses and makeup. The other loves the outdoors and sports, and spends her time in blue jeans and sneakers.”

If an audience-targeting marketer selling spring dresses saw them in his marketing list, he would (1) see two older high school girls with the same income in the same geographical area, (2) assume they are both interested in what he has to sell, and (3) only make one sale.

The problem isn’t with his targeting, the problem is that not all those forced into an audience persona box will fit.

In September of 2015, Aaron Levy (a brilliant marketing mind; go follow him) wrote a fabulously under-shared post revealing these weaknesses in another way: What You Think You Know About Your Customers’ Persona is Wrong

In this article, Aaron first bravely broaches the subject of audience targeting by describing how it is far from the exact science we all have hoped it to be. He noted a few ways that audience targeting can be erroneous, and even *gasp* used data to formulate his conclusions.

It’s OK to question audience targeting — really!

Let me be clear: I believe audience targeting is popular because there genuinely is value in it (it’s amazing data to have… when it’s accurate!). The insights we can get about personas, which we can then use to power our ads, are quite amazing and powerful.

So, why the heck am I droning on about audience targeting weaknesses? Well, I’m trying to set you up for something. I’m trying to get us to admit that audience targeting itself has some weaknesses, and isn’t the savior of all digital marketing that some make it out to be, and that there is a tried-and-true solution that fits well with demographic targeting, but is not replaced by it. It is a targeting that we paid searchers have used joyfully and successfully for years now.

It is the keyword.

Whereas audience targeting chafes under the law of averages (i.e., “at some point, someone in my demographic targeted list has to actually be interested in what I am selling”), keyword targeting shines in individual-revealing user intent.

Keyword targeting does something an audience can never, ever, ever do…

Keywords: Personal intent powerhouses

A keyword is still my favorite form of targeting in paid search because it reveals individual, personal, and temporal intent. Those aren’t just three buzzwords I pulled out of the air because I needed to stretch this already obesely-long post out further. They are intentional, and worth exploring.

Individual

A keyword is such a powerful targeting method because it is written (or spoken!) by a single person. I mean, let’s be honest, it’s rare to have more than one person huddled around the computer shouting at it. Keywords are generally from the mind of one individual, and because of that they have frightening potential.

Remember, audience targeting is based off of assumptions. That is, you’re taking a group of people who “probably” think the same way in a certain area, but does that mean they cannot have unique tastes? For instance, one person preferring to buy sneakers with another preferring to buy heels?

Keyword targeting is demographic-blind.

It doesn’t care who you are, where you’re from, what you did, as long as you love me… err, I mean, it doesn’t care about your demographic, just about what you’re individually interested in.

Personal

The next aspect of keywords powering their targeting awesomeness is that they reveal personal intent. Whereas the “individual” aspect of keyword targeting narrows our targeting from a group of people to a single person, the “personal” aspect of keyword targeting goes into the very mind of that individual.

Don’t you wish there was a way to market to people in which you could truly discern the intentions of their hearts? Wouldn’t that be a powerful method of targeting? Well, yes — and that is keyword targeting!

Think about it: a keyword is a form of communication. It is a person typing or telling you what is on their mind. For a split second, in their search, you and they are as connected through communication as Alexander Graham Bell and Thomas Watson on the first phone call. That person is revealing to you what’s on her mind, and that’s a power which cannot be underestimated.

When a person tells Google they want to know “how does someone earn a black belt,” that is telling your client — the Jumping Judo Janes of Jordan — this person genuinely wants to learn more about their services and they can display an ad that matches that intent (Ready for that Black Belt? It’s Not Hard, Let Us Help!). Paid search keywords officiate the wedding of personal intent with advertising in a way that previous marketers could only dream of. We aren’t finding random people we think might be interested based upon where they live. We are responding to a person telling us they are interested.

Temporal

The final note of keyword targeting that cannot be underestimated, is the temporal aspect. Anyone worth their salt in marketing can tell you “timing is everything”. With keyword targeting, the timing is inseparable from the intent. When is this person interested in learning about your Judo classes? At the time they are searching, NOW!

You are not blasting your ads into your users lives, interrupting them as they go about their business or family time hoping to jumpstart their interest by distracting them from their activities. You are responding to their query, at the very time they are interested in learning more.

Timing. Is. Everything.

The situation settles into stickiness

Thus, to summarize: a “search” is done when an individual reveals his/her personal intent with communication (keywords/queries) at a specific time. Because of that, I maintain that keyword targeting trumps audience targeting in paid search.

Paid search is an evolving industry, but it is still “search,” which requires communication, which requires words (until that time when the emoji takes over the English language, but that’s okay because the rioting in the streets will have gotten us first).

Of course, we would be remiss in ignoring some legitimate questions which inevitably arise. As ideal as the outline I’ve laid out before you sounds, you’re probably beginning to formulate something like the following four questions.

What about low search volume keywords?
What if the search engines kill keyword targeting?
What if IoT monsters kill search engines?
What about social ads?

We’ll close by discussing each of these four questions.

Low search volume terms (LSVs)

Low search volume keywords stink like poo (excuse the rather strong language there). I’m not sure if there is any data on this out there (if so, please share it below), but I have run into low search volume terms far more in the past year than when I first started managing PPC campaigns in 2010.

I don’t know all the reasons for this; perhaps it’s worth another blog post, but the reality is it’s getting harder to be creative and target high-value long-tail keywords when so many are getting shut off due to low search volume.

This seems like a fairly smooth way being paved for Google/Bing to eventually “take over” (i.e., “automate for our good”) keyword targeting, at the very least for SMBs (small-medium businesses) where LSVs can be a significant problem. In this instance, the keyword would still be around, it just wouldn’t be managed by us PPCers directly. Boo.

Search engine decrees

I’ve already addressed the power search engines have here, but I will be the first to admit that, as much as I like keyword targeting and as much as I have hopefully proven how valuable it is, it still would be a fairly easy thing for Google or Bing to kill off completely. Major boo.

Since paid search relies on keywords and queries and language to work, I imagine this would look more like an automated solution (think DSAs and shopping), in which they make keyword targeting into a dynamic system that works in conjunction with audience targeting.

While this was about a year and a half ago, it is worth noting that at Hero Conference in London, Bing Ads’ ebullient Tor Crockett did make the public statement that Bing at the time had no plans to sunset the keyword as a bidding option. We can only hope this sentiment remains, and transfers over to Google as well.

But Internet of Things (IoT) Frankenstein devices!

Finally, it could be that search engines won’t be around forever. Perhaps this will look like IoT devices such as Alexa that incorporate some level of search into them, but pull traffic away from using Google/Bing search bars. As an example of this in real life, you don’t need to ask Google where to find (queries, keywords, communication, search) the best price on laundry detergent if you can just push the Dash button, or your smart washing machine can just order you more without a search effort.

Image source

On the other hand, I still believe we’re a long way off from this in the same way that the freak-out over mobile devices killing personal computers has slowed down. That is, we still utilize our computers for education & work (even if personal usage revolves around tablets and mobile devices and IoT freaks-of-nature… smart toasters anyone?) and our mobile devices for queries on the go. Computers are still a primary source of search in terms of work and education as well as more intensive personal activities (vacation planning, for instance), and thus computers still rely heavily on search. Mobile devices are still heavily query-centered for various tasks, especially as voice search (still query-centered!) kicks in harder.

The social effect

Social is its own animal in a way, and why I believe it is already and will continue to have an effect on search and keywords (though not in a terribly worrisome way). Social definitely pulls a level of traffic from search, specifically in product queries. “Who has used this dishwasher before, any other recommendations?” Social ads are exploding in popularity as well, and in large part because they are working. People are purchasing more than they ever have from social ads and marketers are rushing to be there for them.

The flip side of this: a social and paid search comparison is apples-to-oranges. There are different motivations and purposes for using search engines and querying your friends.

Audience targeting works great in a social setting since that social network has phenomenally accurate and specific targeting for individuals, but it is the rare individual curious about the ideal condom to purchase who queries his family and friends on Facebook. There will always be elements of social and search that are unique and valuable in their own way, and audience targeting for social and keyword targeting for search complement those unique elements of each.

Idealism incarnate

Thus, it is my belief that as long as we have search, we will still have keywords and keyword targeting will be the best way to target — as long as costs remain low enough to be realistic for budgets and the search engines don’t kill keyword bidding for an automated solution.

Don’t give up, the keyword is not dead. Stay focused, and carry on with your match types!

I want to close by re-acknowledging the crucial point I opened with.

It has not been my intention in any way to set up a false dichotomy. In fact, as I think about it, I would argue that I am writing this in response to what I have heard become a false dichotomy. That is, that audience targeting is better than keyword targeting and will eventually replace it…

I believe the keyword is still the most valuable form of targeting for a paid search marketer, but I also believe that audience demographics can play a valuable complementary role in bidding.

A prime example that we already use is remarketing lists for search ads, in which we can layer on remarketing audiences in both Google and Bing into our search queries. Wouldn’t it be amazing if we could someday do this with massive amounts of audience data? I’ve said this before, but were Bing Ads to use its LinkedIn acquisition to allow us to layer on LinkedIn audiences into our current keyword framework, the B2B angels would surely rejoice over us (Bing has responded, by the way, that something is in the works!).

Either way, I hope I’ve demonstrated that far from being on its deathbed, the keyword is still the most essential tool in the paid search marketer’s toolbox.

Evidence of the Surprising State of JavaScript Indexing

Posted on May 29, 2017 by jackburnsblog

Posted by willcritchlow

Back when I started in this industry, it was standard advice to tell our clients that the search engines couldn’t execute JavaScript (JS), and anything that relied on JS would be effectively invisible and never appear in the index. Over the years, that has changed gradually, from early work-arounds (such as the horrible escaped fragment approach my colleague Rob wrote about back in 2010) to the actual execution of JS in the indexing pipeline that we see today, at least at Google.

In this article, I want to explore some things we’ve seen about JS indexing behavior in the wild and in controlled tests and share some tentative conclusions I’ve drawn about how it must be working.

A brief introduction to JS indexing

At its most basic, the idea behind JavaScript-enabled indexing is to get closer to the search engine seeing the page as the user sees it. Most users browse with JavaScript enabled, and many sites either fail without it or are severely limited. While traditional indexing considers just the raw HTML source received from the server, users typically see a page rendered based on the DOM (Document Object Model) which can be modified by JavaScript running in their web browser. JS-enabled indexing considers all content in the rendered DOM, not just that which appears in the raw HTML.

There are some complexities even in this basic definition (answers in brackets as I understand them):

What about JavaScript that requests additional content from the server? (This will generally be included, subject to timeout limits)
What about JavaScript that executes some time after the page loads? (This will generally only be indexed up to some time limit, possibly in the region of 5 seconds)
What about JavaScript that executes on some user interaction such as scrolling or clicking? (This will generally not be included)
What about JavaScript in external files rather than in-line? (This will generally be included, as long as those external files are not blocked from the robot — though see the caveat in experiments below)

For more on the technical details, I recommend my ex-colleague Justin’s writing on the subject.

A high-level overview of my view of JavaScript best practices

Despite the incredible work-arounds of the past (which always seemed like more effort than graceful degradation to me) the “right” answer has existed since at least 2012, with the introduction of PushState. Rob wrote about this one, too. Back then, however, it was pretty clunky and manual and it required a concerted effort to ensure both that the URL was updated in the user’s browser for each view that should be considered a “page,” that the server could return full HTML for those pages in response to new requests for each URL, and that the back button was handled correctly by your JavaScript.

Along the way, in my opinion, too many sites got distracted by a separate prerendering step. This is an approach that does the equivalent of running a headless browser to generate static HTML pages that include any changes made by JavaScript on page load, then serving those snapshots instead of the JS-reliant page in response to requests from bots. It typically treats bots differently, in a way that Google tolerates, as long as the snapshots do represent the user experience. In my opinion, this approach is a poor compromise that’s too susceptible to silent failures and falling out of date. We’ve seen a bunch of sites suffer traffic drops due to serving Googlebot broken experiences that were not immediately detected because no regular users saw the prerendered pages.

These days, if you need or want JS-enhanced functionality, more of the top frameworks have the ability to work the way Rob described in 2012, which is now called isomorphic (roughly meaning “the same”).

Isomorphic JavaScript serves HTML that corresponds to the rendered DOM for each URL, and updates the URL for each “view” that should exist as a separate page as the content is updated via JS. With this implementation, there is actually no need to render the page to index basic content, as it’s served in response to any fresh request.

I was fascinated by this piece of research published recently — you should go and read the whole study. In particular, you should watch this video (recommended in the post) in which the speaker — who is an Angular developer and evangelist — emphasizes the need for an isomorphic approach:

Resources for auditing JavaScript

If you work in SEO, you will increasingly find yourself called upon to figure out whether a particular implementation is correct (hopefully on a staging/development server before it’s deployed live, but who are we kidding? You’ll be doing this live, too).

To do that, here are some resources I’ve found useful:

Justin again, describing the difference between working with the DOM and viewing source
The developer tools built into Chrome are excellent, and some of the documentation is actually really good:
- The console is where you can see errors and interact with the state of the page
- As soon as you get past debugging the most basic JavaScript, you will want to start setting breakpoints, which allow you to step through the code from specified points
This post from Google’s John Mueller has a decent checklist of best practices
Although it’s about a broader set of technical skills, anyone who hasn’t already read it should definitely check out Mike’s post on the technical SEO renaissance.

Some surprising/interesting results

There are likely to be timeouts on JavaScript execution

I already linked above to the ScreamingFrog post that mentions experiments they have done to measure the timeout Google uses to determine when to stop executing JavaScript (they found a limit of around 5 seconds).

It may be more complicated than that, however. This segment of a thread is interesting. It’s from a Hacker News user who goes by the username KMag and who claims to have worked at Google on the JS execution part of the indexing pipeline from 2006–2010. It’s in relation to another user speculating that Google would not care about content loaded “async” (i.e. asynchronously — in other words, loaded as part of new HTTP requests that are triggered in the background while assets continue to download):

“Actually, we did care about this content. I’m not at liberty to explain the details, but we did execute setTimeouts up to some time limit.

If they’re smart, they actually make the exact timeout a function of a HMAC of the loaded source, to make it very difficult to experiment around, find the exact limits, and fool the indexing system. Back in 2010, it was still a fixed time limit.”

What that means is that although it was initially a fixed timeout, he’s speculating (or possibly sharing without directly doing so) that timeouts are programmatically determined (presumably based on page importance and JavaScript reliance) and that they may be tied to the exact source code (the reference to “HMAC” is to do with a technical mechanism for spotting if the page has changed).

It matters how your JS is executed

I referenced this recent study earlier. In it, the author found:

Inline vs. External vs. Bundled JavaScript makes a huge difference for Googlebot

The charts at the end show the extent to which popular JavaScript frameworks perform differently depending on how they’re called, with a range of performance from passing every test to failing almost every test. For example here’s the chart for Angular:

It’s definitely worth reading the whole thing and reviewing the performance of the different frameworks. There’s more evidence of Google saving computing resources in some areas, as well as surprising results between different frameworks.

CRO tests are getting indexed

When we first started seeing JavaScript-based split-testing platforms designed for testing changes aimed at improving conversion rate (CRO = conversion rate optimization), their inline changes to individual pages were invisible to the search engines. As Google in particular has moved up the JavaScript competency ladder through executing simple inline JS to more complex JS in external files, we are now seeing some CRO-platform-created changes being indexed. A simplified version of what’s happening is:

For users:
- CRO platforms typically take a visitor to a page, check for the existence of a cookie, and if there isn’t one, randomly assign the visitor to group A or group B
- Based on either the cookie value or the new assignment, the user is either served the page unchanged, or sees a version that is modified in their browser by JavaScript loaded from the CRO platform’s CDN (content delivery network)
- A cookie is then set to make sure that the user sees the same version if they revisit that page later
For Googlebot:
- The reliance on external JavaScript used to prevent both the bucketing and the inline changes from being indexed
- With external JavaScript now being loaded, and with many of these inline changes being made using standard libraries (such as JQuery), Google is able to index the variant and hence we see CRO experiments sometimes being indexed

I might have expected the platforms to block their JS with robots.txt, but at least the main platforms I’ve looked at don’t do that. With Google being sympathetic towards testing, however, this shouldn’t be a major problem — just something to be aware of as you build out your user-facing CRO tests. All the more reason for your UX and SEO teams to work closely together and communicate well.

Split tests show SEO improvements from removing a reliance on JS

Although we would like to do a lot more to test the actual real-world impact of relying on JavaScript, we do have some early results. At the end of last week I published a post outlining the uplift we saw from removing a site’s reliance on JS to display content and links on category pages.

A simple test that removed the need for JavaScript on 50% of pages showed a >6% uplift in organic traffic — worth thousands of extra sessions a month. While we haven’t proven that JavaScript is always bad, nor understood the exact mechanism at work here, we have opened up a new avenue for exploration, and at least shown that it’s not a settled matter. To my mind, it highlights the importance of testing. It’s obviously our belief in the importance of SEO split-testing that led to us investing so much in the development of the ODN platform over the last 18 months or so.

Conclusion: How JavaScript indexing might work from a systems perspective

Based on all of the information we can piece together from the external behavior of the search results, public comments from Googlers, tests and experiments, and first principles, here’s how I think JavaScript indexing is working at Google at the moment: I think there is a separate queue for JS-enabled rendering, because the computational cost of trying to run JavaScript over the entire web is unnecessary given the lack of a need for it on many, many pages. In detail, I think:

Googlebot crawls and caches HTML and core resources regularly
Heuristics (and probably machine learning) are used to prioritize JavaScript rendering for each page:
- Some pages are indexed with no JS execution. There are many pages that can probably be easily identified as not needing rendering, and others which are such a low priority that it isn’t worth the computing resources.
- Some pages get immediate rendering – or possibly immediate basic/regular indexing, along with high-priority rendering. This would enable the immediate indexation of pages in news results or other QDF results, but also allow pages that rely heavily on JS to get updated indexation when the rendering completes.
- Many pages are rendered async in a separate process/queue from both crawling and regular indexing, thereby adding the page to the index for new words and phrases found only in the JS-rendered version when rendering completes, in addition to the words and phrases found in the unrendered version indexed initially.
The JS rendering also, in addition to adding pages to the index:
- May make modifications to the link graph
- May add new URLs to the discovery/crawling queue for Googlebot

The idea of JavaScript rendering as a distinct and separate part of the indexing pipeline is backed up by this quote from KMag, who I mentioned previously for his contributions to this HN thread (direct link) [emphasis mine]:

“I was working on the lightweight high-performance JavaScript interpretation system that sandboxed pretty much just a JS engine and a DOM implementation that we could run on every web page on the index. Most of my work was trying to improve the fidelity of the system. My code analyzed every web page in the index.

Towards the end of my time there, there was someone in Mountain View working on a heavier, higher-fidelity system that sandboxed much more of a browser, and they were trying to improve performance so they could use it on a higher percentage of the index.”

This was the situation in 2010. It seems likely that they have moved a long way towards the headless browser in all cases, but I’m skeptical about whether it would be worth their while to render every page they crawl with JavaScript given the expense of doing so and the fact that a large percentage of pages do not change substantially when you do.

My best guess is that they’re using a combination of trying to figure out the need for JavaScript execution on a given page, coupled with trust/authority metrics to decide whether (and with what priority) to render a page with JS.

Run a test, get publicity

I have a hypothesis that I would love to see someone test: That it’s possible to get a page indexed and ranking for a nonsense word contained in the served HTML, but not initially ranking for a different nonsense word added via JavaScript; then, to see the JS get indexed some period of time later and rank for both nonsense words. If you want to run that test, let me know the results — I’d be happy to publicize them.

Should SEOs Care About Internal Links? – Whiteboard Friday

Posted on May 26, 2017 by jackburnsblog

Posted by randfish

Internal links are one of those essential SEO items you have to get right to avoid getting them really wrong. Rand shares 18 tips to help inform your strategy, going into detail about their attributes, internal vs. external links, ideal link structures, and much, much more in this edition of Whiteboard Friday.

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Video Transcription

Howdy, Moz fans, and welcome to another edition of Whiteboard Friday. This week we’re going to chat a little bit about internal links and internal link structures. Now, it is not the most exciting thing in the SEO world, but it’s something that you have to get right and getting it wrong can actually cause lots of problems.

Attributes of internal links

So let’s start by talking about some of the things that are true about internal links. Internal links, when I say that phrase, what I mean is a link that exists on a website, let’s say ABC.com here, that is linking to a page on the same website, so over here, linking to another page on ABC.com. We’ll do /A and /B. This is actually my shipping routes page. So you can see I’m linking from A to B with the anchor text “shipping routes.”

The idea of an internal link is really initially to drive visitors from one place to another, to show them where they need to go to navigate from one spot on your site to another spot. They’re different from internal links only in that, in the HTML code, you’re pointing to the same fundamental root domain. In the initial early versions of the internet, that didn’t matter all that much, but for SEO, it matters quite a bit because external links are treated very differently from internal links. That is not to say, however, that internal links have no power or no ability to change rankings, to change crawling patterns and to change how a search engine views your site. That’s what we need to chat about.

1. Anchor text is something that can be considered. The search engines have generally minimized its importance, but it’s certainly something that’s in there for internal links.

2. The location on the page actually matters quite a bit, just as it does with external links. Internal links, it’s almost more so in that navigation and footers specifically have attributes around internal links that can be problematic.

Those are essentially when Google in particular sees manipulation in the internal link structure, specifically things like you’ve stuffed anchor text into all of the internal links trying to get this shipping routes page ranking by putting a little link down here in the footer of every single page and then pointing over here trying to game and manipulate us, they hate that. In fact, there is an algorithmic penalty for that kind of stuff, and we can see it very directly.

We’ve actually run tests where we’ve observed that jamming this type of anchor text-rich links into footers or into navigation and then removing it gets a site indexed, well let’s not say indexed, let’s say ranking well and then ranking poorly when you do it. Google reverses that penalty pretty quickly too, which is nice. So if you are not ranking well and you’re like, “Oh no, Rand, I’ve been doing a lot of that,” maybe take it away. Your rankings might come right back. That’s great.

3. The link target matters obviously from one place to another.

4. The importance of the linking page, this is actually a big one with internal links. So it is generally the case that if a page on your website has lots of external links pointing to it, it gains authority and it has more ability to sort of generate a little bit, not nearly as much as external links, but a little bit of ranking power and influence by linking to other pages. So if you have very well-linked two pages on your site, you should make sure to link out from those to pages on your site that a) need it and b) are actually useful for your users. That’s another signal we’ll talk about.

5. The relevance of the link, so pointing to my shipping routes page from a page about other types of shipping information, totally great. Pointing to it from my dog food page, well, it doesn’t make great sense. Unless I’m talking about shipping routes of dog food specifically, it seems like it’s lacking some of that context, and search engines can pick up on that as well.

6. The first link on the page. So this matters mostly in terms of the anchor text, just as it does for external links. Basically, if you are linking in a bunch of different places to this page from this one, Google will usually, at least in all of our experiments so far, count the first anchor text only. So if I have six different links to this and the first link says “Click here,” “Click here” is the anchor text that Google is going to apply, not “Click here” and “shipping routes” and “shipping.” Those subsequent links won’t matter as much.

7. Then the type of link matters too. Obviously, I would recommend that you keep it in the HTML link format rather than trying to do something fancy with JavaScript. Even though Google can technically follow those, it looks to us like they’re not treated with quite the same authority and ranking influence. Text is slightly, slightly better than images in our testing, although that testing is a few years old at this point. So maybe image links are treated exactly the same. Either way, do make sure you have that. If you’re doing image links, by the way, remember that the alt attribute of that image is what becomes the anchor text of that link.

Internal versus external links

A. External links usually give more authority and ranking ability.

That shouldn’t be surprising. An external link is like a vote from an independent, hopefully independent, hopefully editorially given website to your website saying, “This is a good place for you to go for this type of information.” On your own site, it’s like a vote for yourself, so engines don’t treat it the same.

B. Anchor text of internal links generally have less influence.

So, as we mentioned, me pointing to my page with the phrase that I want to rank for isn’t necessarily a bad thing, but I shouldn’t do it in a manipulative way. I shouldn’t do it in a way that’s going to look spammy or sketchy to visitors, because if visitors stop clicking around my site or engaging with it or they bounce more, I will definitely lose ranking influence much faster than if I simply make those links credible and usable and useful to visitors. Besides, the anchor text of internal links is not as powerful anyway.

C. A lack of internal links can seriously hamper a page’s ability to get crawled + ranked.

It is, however, the case that a lack of internal links, like an orphan page that doesn’t have many internal or any internal links from the rest of its website, that can really hamper a page’s ability to rank. Sometimes it will happen. External links will point to a page. You’ll see that page in your analytics or in a report about your links from Moz or Ahrefs or Majestic, and then you go, “Oh my gosh, I’m not linking to that page at all from anywhere else on my site.” That’s a bad idea. Don’t do that. That is definitely problematic.

D. It’s still the case, by the way, that, broadly speaking, pages with more links on them will send less link value per link.

So, essentially, you remember the original PageRank formula from Google. It said basically like, “Oh, well, if there are five links, send one-fifth of the PageRank power to each of those, and if there are four links, send one-fourth.” Obviously, one-fourth is bigger than one-fifth. So taking away that fifth link could mean that each of the four pages that you’ve linked to get a little bit more ranking authority and influence in the original PageRank algorithm.

Look, PageRank is old, very, very old at this point, but at least the theories behind it are not completely gone. So it is the case that if you have a page with tons and tons of links on it, that tends to send out less authority and influence than a page with few links on it, which is why it can definitely pay to do some spring cleaning on your website and clear out any rubbish pages or rubbish links, ones that visitors don’t want, that search engines don’t want, that you don’t care about. Clearing that up can actually have a positive influence. We’ve seen that on a number of websites where they’ve cleaned up their information architecture, whittled down their links to just the stuff that matters the most and the pages that matter the most, and then seen increased rankings across the board from all sorts of signals, positive signals, user engagement signals, link signals, context signals that help the engine them rank better.

E. Internal link flow (aka PR sculpting) is rarely effective, and usually has only mild effects… BUT a little of the right internal linking can go a long way.

Then finally, I do want to point out that what was previous called — you probably have heard of it in the SEO world — PageRank sculpting. This was a practice that I’d say from maybe 2003, 2002 to about 2008, 2009, had this life where there would be panel discussions about PageRank sculpting and all these examples of how to do it and software that would crawl your site and show you the ideal PageRank sculpting system to use and which pages to link to and not.

When PageRank was the dominant algorithm inside of Google’s ranking system, yeah, it was the case that PageRank sculpting could have some real effect. These days, that is dramatically reduced. It’s not entirely gone because of some of these other principles that we’ve talked about, just having lots of links on a page for no particularly good reason is generally bad and can have harmful effects and having few carefully chosen ones has good effects. But most of the time, internal linking, optimizing internal linking beyond a certain point is not very valuable, not a great value add.

But a little of what I’m calling the right internal linking, that’s what we’re going to talk about, can go a long way. For example, if you have those orphan pages or pages that are clearly the next step in a process or that users want and they cannot find them or engines can’t find them through the link structure, it’s bad. Fixing that can have a positive impact.

Ideal internal link structures

So ideally, in an internal linking structure system, you want something kind of like this. This is a very rough illustration here. But the homepage, which has maybe 100 links on it to internal pages. One hop away from that, you’ve got your 100 different pages of whatever it is, subcategories or category pages, places that can get folks deeper into your website. Then from there, each of those have maybe a maximum of 100 unique links, and they get you 2 hops away from a homepage, which takes you to 10,000 pages who do the same thing.

I. No page should be more than 3 link “hops” away from another (on most small–>medium sites).

Now, the idea behind this is that basically in one, two, three hops, three links away from the homepage and three links away from any page on the site, I can get to up to a million pages. So when you talk about, “How many clicks do I have to get? How far away is this in terms of link distance from any other page on the site?” a great internal linking structure should be able to get you there in three or fewer link hops. If it’s a lot more, you might have an internal linking structure that’s really creating sort of these long pathways of forcing you to click before you can ever reach something, and that is not ideal, which is why it can make very good sense to build smart categories and subcategories to help people get in there.

I’ll give you the most basic example in the world, a traditional blog. In order to reach any post that was published two years ago, I’ve got to click Next, Next, Next, Next, Next, Next through all this pagination until I finally get there. Or if I’ve done a really good job with my categories and my subcategories, I can click on the category of that blog post and I can find it very quickly in a list of the last 50 blog posts in that particular category, great, or by author or by tag, however you’re doing your navigation.

II. Pages should contain links that visitors will find relevant and useful.

If no one ever clicks on a link, that is a bad signal for your site, and it is a bad signal for Google as well. I don’t just mean no one ever. Very, very few people ever and many of them who do click it click the back button because it wasn’t what they wanted. That’s also a bad sign.

III. Just as no two pages should be targeting the same keyword or searcher intent, likewise no two links should be using the same anchor text to point to different pages. Canonicalize!

For example, if over here I had a shipping routes link that pointed to this page and then another shipping routes link, same anchor text pointing to a separate page, page C, why am I doing that? Why am I creating competition between my own two pages? Why am I having two things that serve the same function or at least to visitors would appear to serve the same function and search engines too? I should canonicalize those. Canonicalize those links, canonicalize those pages. If a page is serving the same intent and keywords, keep it together.

IV. Limit use of the rel=”nofollow” to UGC or specific untrusted external links. It won’t help your internal link flow efforts for SEO.

Rel=”nofollow” was sort of the classic way that people had been doing PageRank sculpting that we talked about earlier here. I would strongly recommend against using it for that purpose. Google said that they’ve put in some preventative measures so that rel=”nofollow” links sort of do this leaking PageRank thing, as they call it. I wouldn’t stress too much about that, but I certainly wouldn’t use rel=”nofollow.”

What I would do is if I’m trying to do internal link sculpting, I would just do careful curation of the links and pages that I’ve got. That is the best way to help your internal link flow. That’s things like…

V. Removing low-value content, low-engagement content and creating internal links that people actually do want. That is going to give you the best results.

VI. Don’t orphan! Make sure pages that matter have links to (and from) them. Last, but not least, there should never be an orphan. There should never be a page with no links to it, and certainly there should never be a page that is well linked to that isn’t linking back out to portions of your site that are of interest or value to visitors and to Google.

So following these practices, I think you can do some awesome internal link analysis, internal link optimization and help your SEO efforts and the value visitors get from your site. We’ll see you again next week for another edition of Whiteboard Friday. Take care.

Video transcription by Speechpad.com

It’s Here: The Finalized MozCon 2017 Agenda

Posted on May 24, 2017 by jackburnsblog

Posted by ronell-smith

That sound you hear is the coming together of MozCon 2017.

[You can hear that, right? It’s not just me.]

With less than two months to go, most of the nuts and bolts of the event have been fastened together to create what looks to be one of the strongest MozCons in history. Yeah, that’s saying a lot, but once you’ve perused the speakers’ lineup, we’re sure you’ll agree.

MozCon has a rich tradition of bringing together the best and brightest minds in digital marketing, creating a place for individuals across the globe to learn from top-notch speakers, network, share ideas, and learn about the tools, services, and tactics they can put to use in their work and their business.

As a bonus, attendees also get to enjoy lots of snacks, coffee and lots and lots of bacon.

Also, this year we’ll offer pre-MozCon SEO workshops on Sunday, July 16. Keep reading for more info.

You will, however, need a ticket to attend the event, so you might want to take care of that sooner rather later, since it always sells out:

Buy my MozCon 2017 ticket!

Now for the meaty details you’ve been waiting for.

The MozCon 2017 Agenda

Monday

08:00–09:00am
Breakfast

Rand Fishkin

09:00–09:20am
Welcome to MozCon 2017

Rand Fishkin, Wizard of Moz
@randfish

Rand Fishkin is the founder and former CEO of Moz, co-author of a pair of books on SEO, and co-founder of Inbound.org. Rand’s an un-save-able addict of all things content, search, and social on the web.

09:20–10:05am
How to Get Big Links

Lisa Myers, Verve Search
@LisaDMyers

Everyone wants links and coverage from sites such as New York Times, the Wall Street Journal, and the BBC, but very few achieve it. This is how we cracked it. Over and over.

Lisa is the founder and CEO of award-winning SEO agency Verve Search and founder of Womeninsearch.net. Feminist, mother of two, and modern-day shield maiden.

10:05–10:35am
Data-Driven Design

Oli Gardner, Unbounce
@oligardner

Data-Driven Design (3D) is an actionable, evidence-based framework for creating websites & landing pages that will increase your leads, sales, and customers. In this session you’ll learn how to use the latest industry conversion data to inform copywriting and design decisions that impact conversions. Additionally, I’ll share a new methodology for prioritizing your marketing optimization that will show you which pages are awesome (leave them alone), which pages aren’t (massive ROI potential here), and help you develop a common language that your teams of marketers, designers, and copywriters can use to work better together to collectively increase your conversion rates.

Oli, founder of Unbounce, is on a mission to rid the world of marketing mediocrity by using data-informed copywriting, design, interaction, and psychology to create a more delightful experience for marketers and customers alike.

10:35–11:05am
AM Break

11:10–11:30am
How to Write Customer-Driven Copy That Converts

Joel Klettke, Business Casual Copywriting & Case Study Buddy
@JoelKlettke

If you want to write copy that converts, you need to get into your customers’ heads. But how do you do that? How do you know which pain points you need to address, features customers care about, or benefits your audience needs to hear? Marketers are sick and tired of hearing “it depends.” I’ll give the audience a practical framework for writing customer-driven copy that any business can apply.

Joel is a freelance conversion copywriter and strategist for Business Casual Copywriting. He also owns and runs Case Study Buddy, a done-for-you case studies service.

11:30–11:50am
What We Learned From Reddit & How It Can Help Your Brand Take Content Marketing to the Next Level

Daniel Russell, Go Fish Digital
@dnlRussell ‏

It almost seems too good to be true — online forums where people automatically segment themselves into different markets and demographics and then vote on what content they like best. These forums, including Reddit, are treasure troves of content ideas. I’ll share actionable insights from three case studies that demonstrate how your marketing can benefit from content on Reddit.

Daniel is a director at Go Fish Digital whose work has hit the front page of Reddit, earned the #1 spot on YouTube, and been featured in Entrepreneur, Inc., The Washington Post, WSJ, and Fast Company.

11:50am–12:10pm
How to Build an SEO-Intent-Based Framework for Any Business

Kathryn Cunningham, Adept Marketing
@kac4509

Everyone knows intent behind the search matters. In e-commerce, intent is somewhat easy to see. B2B, or better yet healthcare, isn’t quite as easy. Matching persona intent to keywords requires a bit more thought. I will cover how to find intent modifiers during keyword research, how to organize those modifiers into the search funnel, and how to quickly find unique universal results at different levels of the search funnel to utilize.

Kathryn is an SEO consultant for Adept Marketing, although to many of her office mates she is known as the Excel nerd.

12:10–01:40pm
Lunch

01:45–02:30pm
Size Doesn’t Matter: Great Content by Teams of One

Ian Lurie, Portent, Inc.
@portentint

Feel the energy surge through your veins as you gain content creation powers THE LIKES OF WHICH YOU HAVE NEVER EXPERIENCED… Or, just learn a process for creating great content when it’s just you and your little teeny team. Because size doesn’t matter.

Ian Lurie is founder, CEO, and nerdiest marketing nerd at Portent, a digital marketing agency he started in the Cretaceous era, aka 1995. Ian’s meandering career includes marketing copywriting, expert dungeon master, bike messenger-ing, and office temp worker.

02:30–03:00pm
The Tie That Binds: Why Email is Key to Maximizing Marketing ROI

Justine Jordan, Litmus
@meladorri

If nailing the omnichannel experience (whatever that means!) is key to getting more traffic and converting more leads, what happens if we have our channel priorities out of order? Justine will show you how email — far from being an old-school afterthought — is core to hitting marketing goals, building lifetime value, and making customers happy.

Justine is obsessed with helping marketers create, test, and send better email. Named 2015 Email Marketer Thought Leader of the Year, she is strangely passionate about email marketing, hates being called a spammer, and still gets nervous when pressing send.

03:00–03:30pm
PM Break

03:35–04:05pm

How to Be a Happy Marketer: Survive the Content Crisis and Drive Results by Mastering Your Customer’s Transformational Journey

Tara-Nicholle Nelson, Transformational Consumer Insights
@taranicholle

Branded content is way up, but customer engagement with that content is plummeting. This whole scene makes it hard to get up in the morning, as a marketer. But there’s a new path beyond the epidemic of disengagement and, at the end of it, your brand and your content become regular stops along your customer’s everyday journey.

Tara-Nicholle Nelson is the CEO of Transformational Consumer Insights, the former VP of Marketing for MyFitnessPal, and author of the Transformational Consumer.

04:05–04:50pm
Thinking Smaller: Optimizing for the New Wave of Social Video Platforms

Phil Nottingham, Wistia
@philnottingham ‏

SnapChat, Facebook, Twitter, Instagram, Periscope… the list goes on. All social networks are now video platforms, but it’s hard to know where to invest. In this session, Phil will be giving you all the tips and tricks for what to make, how to get your content in front of the right audiences, and how get the most value from the investment you’re making in social video.

Phil Nottingham is a strategist who believes in the power of creative video content to improve the way companies speak to their customers, and regularly speaks around the world about video strategy, SEO, and technical marketing.

07:00–10:00pm
Monday Night #MozCrawl

The Monday night pub crawl is back.

For the uninitiated, “pub crawl” is not meant to convey what you do after a night of drinking.

Rather, during the MozCon pub crawl, attendees visit some of the best bars in Seattle.

(Each stop is sponsored by a trusted partner; You’ll need to bring your MozCon badge for free drinks and light appetizers. You’ll also need your US ID or passport.)

More deets to follow.

Tuesday

08:00–09:00am
Breakfast

09:05–09:50am
I’d Rather Be Thanked Than Ranked

Wil Reynolds, Seer Interactive
@wilreynolds

Ego and assumptions led me to chose the wrong keywords for my own site — yeah, me, Wil Reynolds, Mr. RCS. How did I spend three years optimizing my site and building links to finally crack the top three for six critical keywords, only to find out that I wasted all that time? However, in spite of targeting the wrong words, Seer grew the business. In this presentation, I’ll show you the mistakes I made and share with you to approaches that can help you to build content that gets you thanked.

A former teacher with a knack for advising, he’s been helping Fortune 500 companies develop SEO strategies since 1999. Today, Seer is home to over 100 employees across Philadelphia and San Diego.

09:50–10:35am
Winning Value Propositions for Crawlers and Consumers

Dawn Anderson, Move It Marketing/Manchester Metropolitan University
@dawnieando

In an evolving mobile-first web, we can utilize preempting solutions to create winning value propositions, which are designed to attract and satisfy search engine crawlers and keep consumers happy. I’ll outline a strategy and share tactics that help ensure increased organic reach, in addition to highlighting smart ways to view data, intent, consumer choice theory, and crawl optimization.

Dawn Anderson is an International and Technical SEO Consultant, Director of Move It Marketing, and a lecturer at Manchester Metropolitan University.

10:35–11:05am
AM Break

11:10–11:15am
MozCon Ignite Preview

11:15–11:35am
More Than SEO: 3 Ways To Prove UX Matters Too

Matthew Edgar, Elementive
@MatthewEdgarCO

Great SEO is increasingly dependent on having a website with a great user experience. To make your user experience great requires carefully tracking what people do so that you always know where to improve. But what do you track? In this 15-minute talk, I’ll cover three effective and advanced ways to use event tracking in Google Analytics to understand a website’s user

Matthew is a web analytics and technical marketing consultant at Elementive.

11:35–11:55am
A Site Migration: Redirects, Resources, & Reflection

Jayna Grassel, Dick’s Sporting Goods
@jaynagrassel

Site. Migration. No two words elicit more fear, joy, or excitement to a digital marketer. When the idea was shared three years ago, the company was excited. They dreamed of new features and efficiency. But as SEOs, we knew better. We knew there would be midnight strategy sessions with IT. More UAT environments than we could track. Deadlines, requirements, and compromises forged through hallway chats. …The result was a stable transition with minimal dips in traffic. What we didn’t know, however, was the amount of cross-functional coordination that was required to pull it off.

Jayna is the SEO manager at Dick’s Sporting Goods and is the unofficial world’s second-fastest crocheter.

11:55am–12:15pm
The 8 Paid Promotion Tactics That Will Get You To Quit Organic Traffic

Kane Jamison, Content Harmony
@kanejamison

Digital marketers are ignoring huge opportunities to promote their content through paid channels, and I want to give them the tools to get started. How many brands out there are spending $500+ on a blog post, then moving on to the next one before that post has been seen by 500 people, or even 50? For some reason, everyone thinks about Outbrain and native ads when we talk about paid content distribution, but the real opportunity is in highly targeted paid social.

Kane is the founder of Content Harmony, a content marketing agency based here in Seattle. The Content Harmony team specializes in full funnel content marketing and content promotion.

12:15–01:45pm
Lunch

01:50–02:20pm
Marketing in a Conversational World: How to Get Discovered, Delight Your Customers and Earn the Conversion

Purna Virji, Microsoft
@purnavirji

Capturing and keeping attention is one of the hardest parts of our job today. Fact: It’s just going to get harder with the advent of new technology and conversational interfaces. In the brave new world we’re stepping into, the key questions are: How do we get discovered? How can we delight our audiences? And how can we grow revenue for our clients? Come to this session to learn how to make your marketing and advertising efforts something people are going to want to consume.

Named by PPC Hero as the #1 most influential PPC expert in the world, Purna specializes in SEM, SEO, and future search trends. She is a popular global keynote speaker and columnist, an avid traveler, aspiring top chef, and amateur knitter.

02:20–02:50pm
Up and to the Right: Growing Traffic, Conversions, & Revenue

Matthew Barby, HubSpot
@matthewbarby

So many of the case studies that document how a company has grown from 0 to X forget to mention that solutions that they found are applicable to their specific scenario and won’t work for everyone. This falls into the dangerous category of bad advice for generic problems. Instead of building up a list of other companies’ tactics, marketers need to understand how to diagnose and solve problems across their entire funnel. Illustrated with real-world examples, I’ll be talking you through the process that I take to come up with ideas that none of my competitors are thinking of.

Matt, who heads up user acquisition at HubSpot, is an award-winning blogger, startup advisor, and a lecturer.

02:50–03:20pm
How to Operationalize Growth for Maximum Revenue

Joanna Lord, ClassPass
@JoannaLord

Joanna will walk through tactical ways to organize your team, build system foundations, and create processes that fuel growth across the company. You’ll hear how to coordinate with product, engineering, CX, and sales to ensure you’re maximizing your opportunity to acquire, retain, and monetize your customers.

Joanna is the CMO of ClassPass, the world’s leading fitness membership. Prior to that she was VP of Marketing at Porch and CMO of BigDoor. She is a global keynote and digital evangelist. Joanna is a recognized thought leader in digital marketing and a startup mentor.

03:20–03:50pm
PM Break

03:55–04:25pm
Analytics to Drive Optimization & Personalization

Krista Seiden, Google
@kristaseiden

Getting the most out of your optimization efforts means understanding the data you’re collecting, from analytics implementation, to report setup, to analysis techniques. In this session, Krista walks you through several tips for using analytics data to empower your optimization efforts, and then takes it further to show you how to up-level your efforts to take advantage of personalization from mass scale all the way down to individual user actions.

Krista Seiden is the Analytics Advocate for Google, advocating for all things data, web, mobile, optimization, and more. Keynote speaker, practitioner, writer on Analytics and Optimization, and passionate supporter of #WomenInAnalytics.

04:25–05:10pm
Facing the Future: 5 Simple Tactics for 5 Scary Changes

Dr. Pete Meyers, Moz
@dr_pete ‏

We’ve seen big changes to SEO recently, from an explosion in SERP features to RankBrain to voice search. These fundamental changes to organic search marketing can be daunting, and it’s hard to know where to get started. Dr. Pete will walk you through five big changes and five tactics for coping with those changes today.

Dr. Peter J. Meyers (aka “Dr. Pete”) is Marketing Scientist for Seattle-based Moz, where he works with the marketing and data science teams on product research and data-driven content.

07:00–10:00pm
MozCon Ignite

Join us for an evening of networking and passion-talks. Laugh, cheer, and be inspired as your peers share their 5-minute talks about their hobbies, passion projects, and life lessons.

Be sure to bring your MozCon badge.

Wednesday

09:00–10:00am
Breakfast

10:05–10:50am
The Truth About Mobile-First Indexing

Cindy Krum, MobileMoxie, LLC
@suzzicks

Mobile-first design has been a best practice for a while, and Google is finally about to support it with mobile-first indexing. But mobile-first design and mobile-first indexing are not the same thing. Mobile-first indexing is about cross-device accessibility of information, to help integrate digital assistants and web-enabled devices that don’t even have browsers to achieve Google’s larger goals. Learn how mobile-first indexing will give digital marketers their first real swing at influencing Google’s new AI (Artificial Intelligence) landscape. Marketers who embrace an accurate understanding of mobile-first indexing could see a huge first-mover advantage, similar to the early days of the web, and we all need to be prepared.

Cindy, the CEO and Founder of MobileMoxie, LLC, is the author of Mobile Marketing: Finding Your Customers No Matter Where They Are. She brings fresh and creative ideas to her clients, and regularly speaks at US and international digital marketing events.

10:50–11:20am
Powerful Brands Have Communities

Tara Reed, Apps Without Code
@TaraReed_

You are laser-focused on user growth. Meanwhile, you’re neglecting a gold mine of existing customers who desperately want to be part of your brand’s community. Tara Reed shares how to use communities, gamification, and membership content to grow your revenue.

Tara Reed is a tech entrepreneur & marketer. After running marketing initiatives at Google, Foursquare, & Microsoft, Tara branched out to launch her own apps & startups. Today, Tara helps people implement cutting-edge marketing into their businesses.

11:20–11:50am
AM Break

11:55–12:25am

From Anchor to Asset: How Agencies Can Wisely Create Data-Driven Content

Heather Physioc, VML
@HeatherPhysioc

Creative agencies are complicated and messy, often embracing chaos instead of process, and focusing exclusively on one-time campaign creative instead of continuous web content creation. Campaign creative can be costly, and not sustainable for most large brands. How can creative shops produce data-driven streams of high-quality content for the web that stays true to its creative roots — but faster, cheaper, and continuously? I’ll show you how.

Heather is director of Organic Search at global digital ad agency VML, which performs search engine optimization services for multinational brands like Hill’s Pet Nutrition, Electrolux/Frigidaire, Bridgestone, EXPRESS, and Wendy’s.

12:25–12:55pm
5 Secrets: How to Execute Lean SEO to Increase Qualified Leads

Britney Muller, Moz
@BritneyMuller

I invite you to steal some of the ideas I’ve gleaned from managing SEO for the behemoth bad-ass Moz.com. Learn what it takes to move the needle on qualified leads, execute quick wins, and keep your head above water. I’ll go over my biggest Moz.com successes, failures, tests, and lessons.

Britney is a Minnesota native who moved to Colorado to fulfill a dream of being a snowboard bum! After 50+ days on the mountain her first season, she got stir-crazy and taught herself how to program, then found her way into SEO while writing for a local realtor.

12:55–02:25pm
Lunch

02:30–03:15pm
SEO Experimentation for Big-Time Results

Stephanie Chang, Etsy
@@stephpchang

One of the biggest business hurdles any brand faces is how to prioritize and validate SEO recommendations. This presentation describes an SEO experimentation framework you can use to effectively test how changes made to your pages affect SEO performance.

Stephanie currently leads the Global Acquisition & Retention Marketing teams at Etsy. Previously, she was a Senior Consultant at Distilled.

03:15–03:45pm
Reverse-Engineer Google’s Research to Serve Up the Best, Most Relevant Content for Your Audience

Rob Bucci, STAT Search Analytics
@STATrob

The SERP is the front-end to Google’s multi-billion dollar consumer research machine. They know what searchers want. In this data-heavy talk, Rob will teach you how to uncover what Google already knows about what web searchers are looking for. Using this knowledge, you can deliver the right content to the right searchers at the right time, every time.

Rob loves the challenge of staying ahead of the changes Google makes to their SERPs. When not working, you can usually find him hiking up a mountain, falling down a ski slope, or splashing around in the ocean.

03:45–04:15pm
PM Break

04:20–05:05pm
Inside the Googling Mind: An SEO’s Guide to Winning Clicks, Hearts, & Rankings in the Years Ahead

Rand Fishkin, Founder of Moz, doer of SEO, feminist
@randfish

Searcher behavior, intent, and satisfaction are on the verge of overtaking classic SEO inputs (keywords, links, on-page, etc). In this presentation, Rand will examine the shift that behavioral signals have caused, and list the step-by-step process to build a strategy that can thrive long-term in Google’s new reality.

07:00–11:30pm
MozCon Bash

Join us at Garage Billiards for an evening of networking, billiards, bowling, and karaoke with MozCon friends new and old. Don’t forget to bring your MozCon badge and US ID or passport.

Additional Pre-MozCon Sunday Workshops

12:30pm–5:05pm
SEO Intensive

Offered as 75-minute sessions, the five workshops will be taught by Mozzers Rand Fishkin, Britney Muller, Brian Childs, Russ Jones, and Dr. Pete. Topics include The 10 Jobs of SEO-focused Content, Keyword Targeting for RankBrain and Beyond, and Risk-Averse Link Building at Scale, among others.

These workshops are separate from MozCon; you’ll need a ticket to attend them.

Amped up for a talk or ten? Curious about new methods? Excited to learn? Get your ticket before they sell out:

Snag my ticket to MozCon 2017!

Tackling Tag Sprawl: Crawl Budget, Duplicate Content, and User-Generated Content

Posted on May 24, 2017 by jackburnsblog

Posted by rjonesx.

Alright, so here’s the situation. You have a million-product website. Your competitors have a lot of the same products. You need unique content. What do you do? The same thing everyone does — you turn to user-generated content. Problem solved, right?

User-generated content (UGC) can be an incredibly valuable source of content and organization, helping you build natural language descriptions and human-driven organization of site content. One common feature used by sites to take advantage of user-created content are tags, found everywhere from e-commerce sites to blogs. Webmasters can leverage tags to power site search, create taxonomies and categories of products for browsing, and to provide rich descriptions of site content.

This is a logical and practical approach, but can cause intractable SEO problems if left unchecked. For mega-sites, manually moderating millions of user-submitted tags can be cumbersome (if not wholly impossible). Leaving tags unchecked, though, can create massive problems with thin content, duplicate content, and general content sprawl. In our case study below, three technical SEOs from different companies joined forces to solve a massive tag sprawl problem. The project was led by Jacob Bohall, VP of Marketing at Hive Digital, while computational statistics services were provided by J.R. Oakes of Adapt Partners and Russ Jones of Moz. Let’s dive in.

What is tag sprawl?

We define tag sprawl as the unchecked growth of unique, user-contributed tags resulting in a large amount of near-duplicate pages and unnecessary crawl space. Tag sprawl generates URLs likely to be classified as doorway pages, pages appearing to exist only for the purpose of building an index across an exhaustive array of keywords. You’ve probably seen this in its most basic form in the tagging of posts across blogs, which is why most SEOs recommend a blanket “noindex, follow” across tag pages in WordPress sites. This simple approach can be an effective solution for small blog sites, but is not often the solution for major e-commerce sites that rely more heavily on tags for categorizing products.

The three following tag clouds represent a list of user-generated terms associated with different stock photos. Note: User behavior is generally to place as many tags as possible in an attempt to ensure maximum exposure for their products.

USS Yorktown, Yorktown, cv, cvs-10, bonhomme richard, revolutionary war-ships, war-ships, naval ship, military ship, attack carriers, patriots point, landmarks, historic boats, essex class aircraft carrier, water, ocean
ship, ships, Yorktown, war boats, Patriot pointe, old war ship, historic landmarks, aircraft carrier, war ship, naval ship, navy ship, see, ocean
Yorktown ship, Warships and aircraft carriers, historic military vessels, the USS Yorktown aircraft carrier

As you can see, each user has generated valuable information for the photos, which we would want to use as a basis for creating indexable taxonomies for related stock images. However, at any type of scale, we have immediate threats of:

Thin content: Only a handful of products share the user-generated tag when a user creates a more specific/defining tag, e.g. “cvs-10”
Duplicate and similar content: Many of these tags will overlap, e.g. “USS Yorktown” vs. “Yorktown,” “ship” vs. “ships,” “cv” vs. “cvs-10,” etc.
Bad content: Created by improper formatting, misspellings, verbose tags, hyphenation, and similar mistakes made by users.

Now that you understand what tag sprawl is and how it negatively effects your site, how can we address this issue at scale?

The proposed solution

In correcting tag sprawl, we have some basic (at the surface) problems to solve. We need to effectively review each tag in our database and place them in groups so further action can be taken. First, we determine the quality of a tag (how likely is someone to search for this tag, is it spelled correctly, is it commercial, is it used for many products) and second, we determine if there is another tag very similar to it that has a higher quality.

Identify good tags: We defined a good tag as term capable of contributing meaning, and easily justifiable as an indexed page in search results. This also entailed identifying a “master” tag to represent groups of similar terms.
Identify bad tags: We wanted to isolate tags that should not appear in our database due to misspellings, duplicates, poor format, high ambiguity, or likely to cause a low-quality page.
Relate bad tags to good tags: We assumed many of our initial “bad tags” could be a range of duplicates, i.e. plural/singular, technical/slang, hyphenated/non-hyphenated, conjugations, and other stems. There could also be two phrases which refer to the same thing, like “Yorktown ship” vs. “USS Yorktown.” We need to identify these relationships for every “bad” tag.

For the project inspiring this post, our sample tag database comprised over 2,000,000 “unique” tags, making this a nearly impossible feat to accomplish manually. While theoretically we could have leveraged Mechanical Turk or similar platform to get “manual” review, early tests of this method proved to be unsuccessful. We would need a programmatic method (several methods, in fact) that we could later reproduce when adding new tags.

The methods

Keeping the goal in mind of identifying good tags, labeling bad tags, and relating bad tags to good tags, we employed more than a dozen methods, including: spell correction, bid value, tag search volume, unique visitors, tag count, Porter stemming, lemmatization, Jaccard index, Jaro-Winkler distance, Keyword Planner grouping, Wikipedia disambiguation, and K-Means clustering with word vectors. Each method either helped us determine whether the tag was valuable and, if not, helped us identify an alternate tag that was valuable.

Spell correction

Method: One of the obvious issues with user-generated content is the occurrence of misspellings. We would regularly find misspellings where semicolons are transposed for the letter “L” or words have unintended characters at the beginning or end. Luckily, Linux has an excellent built-in spell checker called Aspell which we were able to use to fix a large volume of issues.
Benefits: This offered a quick, early win in that it was fairly easy to identify bad tags when they were composed of words that weren’t included in the dictionary or included characters that were simply inexplicable (like a semicolon in the middle of a word). Moreover, if the corrected word or phrase occurred in the tag list, we could trust the corrected phrase as a potentially good tag, and relate the misspelled term to the good tag. Thus, this method help us both filter bad tags (misspelled terms) and find good tags (the spell-corrected term)
Limitations: The biggest limitation with this methodology was that combinations of correctly spelled words or phrases aren’t necessarily useful for users or the search engine. For example, many of the tags in the database were concatenations of multiple tags where the user space-delimited rather than comma-delimited their submitted tags. Thus, a tag might consist of correctly spelled terms but still be useless in terms of search value. Moreover, there were substantial dictionary limitations, especially with domain names, brand names, and Internet slang. In order to accommodate this, we added a personal dictionary that included a list of the top 10,000 domains according to Quantcast, several thousand brands, and a slang dictionary. While this was helpful, there were still several false recommendations that needed to be handled. For example, we saw “purfect” correct to “perfect,” despite being a pop-culture reference for cat images. We also noticed some users reference this saying as “purrfect,” “purrrfect,” “purrrrfect,” “purrfeck,” etc. Ultimately, we had to rely on other metrics to determine whether we trusted the misspelling recommendations.

Bid value

Method: While a tag might be good in the sense that it is descriptive, we wanted tags that were commercially relevant. Using the estimated cost-per-click of the tag or tag phrase proved useful in making sure that the term could attract buyers, not just visitors.
Benefits: One of the great features of this methodology is that it tends to have a high signal-to-noise ratio. Most tags that have high CPCs tend to be commercially relevant and searched frequently enough to warrant inclusion as “good tags.” In many cases we could feel confident that a tag was good just on this metric alone.
Limitations: However, the bid value metric comes with some pretty big limitations, too. For starters, Google Keyword Planner’s disambiguation problem is readily apparent. Google combines related keywords together when reporting search volume and CPC data, which means a tag like “facbook” would return the same data as “facebook.” Obviously, we would prefer to map “facbook” to “facebook” rather than keep both tags, so in some cases the CPC metric wasn’t sufficient to identify good tags. A further limitation of the bid value was the difficulty of acquiring CPC data. Google now requires running active Adwords campaigns to get access to CPC value. It is no simple feat to look up 5,000,000 keywords in Google Keyword Planner, even if you have a sufficient account. Luckily, we felt comfortable that historical data would be trustworthy enough, so we didn’t need to acquire fresh data.

Tag search volume

Method: Similar to CPC, we could use search volume to determine the potential value of a tag. We had to be careful not to rely on the tag itself, though, since the tag could be so generic that it earns traffic unrelated to the product itself. For example, the tag “USS Yorktown” might get a few hundred searches a month, but “USS Yorktown T-shirt” gets 0. For all of the tags in our index, we tracked down the search volume for the tag plus the product name, in order to make sure we had good estimates of potential product traffic.
Benefits: Like CPC, this metric did a very good job of consolidating our tag data set to just keywords that were likely to deliver traffic. In the vast majority of cases, if “tag + product” had search volume, we could feel confident that it is a good term.
Limitations: Unfortunately, this method fell victim to the same disambiguation problem that CPC presents. Because Google groups terms together, it is possible that on some occasions two tags will be given the same metrics. For example: “pontoons boat,” “pontoonboat,” “pontoon boats,” “pontoon boat,” “pontoon boating,” and “pontoons boats” were in the same traffic volume group which also included tags like “yacht” and “yachts.” Moreover, there is no accounting for keyword difficulty in this metric. Some tags, when combined with product types, produce keywords that receive substantial traffic but will always be out of reach for a templated tag page.

Unique visitors

Method: This method was a no-brainer: protect the tags that already receive traffic from Google. We exported all of the tags from Google Analytics that had received search traffic from Google in the last 12 months. Generally speaking, this should be a fairly safe list of terms.
Benefits: When doing experimental work with a client, it is always nice to be able to give them a scenario that almost guarantees improvement. Because we were able to protect tags that already receive traffic by labeling them as good (in the vast majority of cases), we could ensure that the client had a high probability of profiting from the changes we made and minimal risk of any traffic loss.
Limitations: Unfortunately, even this method wasn’t perfect. If a product (or set of products) with high enough authority included a poor variation of a tag, then the bad variant would rank and receive traffic. We had to use other strategies to verify our selections from this method and devise a method to encourage a tag swap in the index for the correct version of a term.

Tag count

Description: The frequency with which a tag was used on the site was often a strong signal that we could trust the tag, especially when compared with other similar tags. By counting the number of times each tag was used on the site, we could bias our final set of trusted tags in favor of these more popular terms.
Benefits: This was a great tie-breaker metric when we had two tags that were very similar but needed to choose just one. For example, sometimes two variants of a phrase were completely acceptable (such as a version with and without a hyphen). We could simply defer to the one with a higher tag count.
Limitations: The clear limitation of tag frequency is that many of the most frequent tags were too generic to be useful. The tag “blue” isn’t particularly useful when it just helps people find “blue t-shirts.” The term is too generic and too competitive to warrant inclusion. Additionally, the inclusion of too broad of a tag would simply create a very large crawl vs. traffic-potential ratio. A common tag will have hundreds if not thousands of matching products, creating many pages of products for the single tag. If a tag produces 50 paginated product listings, but only has the potential to drive 10 visitors a year, it might not be worth it.

Porter stemming

Method: Stemming is a method used to identify the root word from a tag by scanning the word right to left and using various pattern matching rules to remove characters (suffixes) until you arrive at the word’s stem. There are a couple of popular stemmers available, but we found Porter stemming to be more accurate as a tool for seeing alternative word forms. You can geek out by looking at the Porter stemming algorithm in Snowball here, or you can play with a JS version here.
Benefits: Plural and possessive terms can be grouped by their stem for further analysis. Running Porter stemming on the terms “pony” and “ponies” will return “poni” as the stem, which can then be used to group terms for further analysis. You can also run Porter stemming on phrases. For example, “boating accident,” “boat accidents,” “boating accidents,” etc. share the stem “boat accid.” This can be a crude and quick method for grouping variations. Porter stemming also is able to clean text more kindly, where others stemmers can be too aggressive for our efforts; e.g., Lancaster stemmer reduces “woman” to “wom,” while Porter stemmer leaves it as “woman.”
Limitations: Stemming is intended for finding a common root for terms and phrases, and does not create any type of indication as to the proper form of a term. The Porter stemming method applies a fixed set of rules to the English language by blanket removing trailing “s,” “e,” “ance,” “ing,” and similar word endings to try and find the stem. For this to work well, you have to have all of the correct rules (and exceptions) in place to get the correct stems in all cases. This can be particularly problematic with words that end in S but are not plural, like “billiards” or “Brussels.” Additionally, this method does not help with mapping related terms such as “boat crash,” “crashed boat,” “boat accident,” etc. which would stem to “boat crash,” “crash boat,” and “boat acci.”

Lemmatization

Method: Lemmatization works similarly to stemming. However, instead of using a rule set for editing words by removing letters to arrive at a stem, lemmatization attempts to map the term to its most simple dictionary form, such as WordNet, and return a canonical “lemma” of the word. A crude way to think about lemmatization is just simplifying a word. Here’s an API to check out.
Benefits: This method often works better than stemming. Terms like “ship,” “shipped,” and “ships” are all mapped to “ship” by this method, while “shipping” or “shipper,” which are terms that have distinct meaning despite the same stem, are retained. You can create an array of “lemma” from phrases which can be compared to other phrases resolving word order issues. This proved to be a more reliable method for grouping variations than stemming.
Limitations: As with many of the methods, context for mapping related terms can be difficult. Lemmatization can provide better filters for context, but to do so generally relies on identifying the word form (noun, adjective, etc) to appropriately map to a root term. Given the inconsistency of the user-generated content, it is inaccurate to assume all words are in adjective form (describing a product), or noun form (the product itself). This inconsistency can present wild results. For example, “strip socks” could be intended as as a tag for socks with a strip of color on them, such as as “striped socks,” or it could be “stripper socks” or some other leggings that would be a match only found if there other products and tags to compare for context. Additionally, it doesn’t create associations between all related words, just textual derivatives, so you are still seeking out a canonical between mailman, courier, shipper, etc.

Jaccard index

Method: The Jaccard index is a similarity coefficient measured by Intersection over Union. Now, don’t run off just yet, it is actually quite straightforward.
Imagine you had two piles of with 3 marbles in each: Red, Green, and Blue in the first, Red, Green and Yellow in the second. The “Intersection” of these two piles would be Red and Green, since both piles have those two colors. The “Union” would be Red, Green, Blue and Yellow, since that is the complete list of all the colors. The Jaccard index would be 2 (Red and Green) divided by 4 (Red, Green, Blue, and Yellow). Thus, the Jaccard index of these two piles would be .5. The higher the Jaccard index, the more similar the two sets.
So what does this have to do with tags? Well, imagine we have two tags: “ocean” and “sea.” We can get a list of all of the products that have the tag “ocean” and “sea.” Finally, we get the Jaccard index of those two sets. The higher the score, the more related they are. Perhaps we find that 70% of the products with the tag “ocean” also have the tag “sea”; we now know that the two are fairly well-related. However, when we run the same measurement to compare “basement” or “casement,” we find that they only have a Jaccard index of .02. Even though they are very similar in terms of characters, they mean quite different things. We can rule out mapping the two terms together.
Benefits: The greatest benefit of using the Jaccard index is that it allows us to find highly related tags which may have absolutely no textual characteristics in common, and are more likely to have an overly similar or duplicate results set. While most of the the metrics we have considered so far help us find “good” or “bad” tags, the Jaccard index helps us find “related” tags without having to do any complex machine learning.
Limitations: While certainly useful, the Jaccard index methodology has its own problems. The biggest issue we ran into had to do with tags that were used together nearly all the time but weren’t substitutes of one another. For example, consider the tags “babe ruth” and his nickname, “sultan of swat.” The latter tag only occurred on products which also had the “babe ruth” tag (since this was one of his nicknames), so they had quite a high Jaccard index. However, Google doesn’t map these two terms together in search, so we would prefer to keep the nickname and not simply redirect it to “babe ruth.” We needed to dig deeper if we were to determine when we should keep both tags or when we should redirect one to another. As a standalone, this method also was not sufficient at identifying cases where a user consistently misspelled tags or used incorrect syntax, as their products would essentially be orphans without “union.”

Jaro-Winkler distance

Method: There are several edit distance and string similarity metrics that we used throughout this process. Edit Distance is simply some measurement of how difficult it is to change one word to another. For example, the most basic edit distance metric, Levenshtein distance, between “Russ Jones” and “Russell Jones” is 3 (you have to add “E”,”L”, and “L” to transform Russ to Russell). This can be used to help us find similar words and phrases. In our case, we used a particular edit distance measure called “Jaro-Winkler distance” which gives higher precedence to words and phrases that are similar at the beginning. For example, “Baseball” would be closer to “Baseballer” than to “Basketball” because the differences are at the very end of the term.
Benefits: Edit distance metrics helped us find many very similar variants of tags, especially when the variants were not necessarily misspellings. This was particularly valuable when used in conjunction with the Jaccard index metrics, because we could apply a character-level metric on top of a character-agnostic metric (i.e. one that cares about the letters in the tag and one that doesn’t).
Limitations: Edit distance metrics can be kind of stupid. According to Jaro-Winkler distance, “Baseball” and “Basketball” are far more related to one another than “Baseball” and “Pitcher” or “Catcher.” “Round” and “Circle” have a horrible edit distance metric, while “Round” and “Pound” look very similar. Edit distance simply cannot be used in isolation to find similar tags.

Keyword Planner grouping

Method: While Google’s choice to combine similar keywords in Keyword Planner has been problematic for predicting traffic, it has actually offered us a new method to identify highly related terms. Whenever two tags share identical metrics from Google Keyword Planner (average monthly traffic, historical traffic, CPC, and competition), we can conclude that there is an increased chance the two are related to one another.
Benefits: This method is extremely useful for acronyms (which are particularly difficult to detect). While Google groups together COO and Chief Operating Officer, you can imagine that standard methods like those outlined above might have problems detecting the relationship.
Limitations: The greatest drawback for this methodology was that it created numerous false positives among less popular terms. There are just too many keywords which have an annual search volume average of 10, are searched 10 times monthly, and have a CPC and competition of 0. Thus, we had to limit the use of this methodology to more popular terms where there were only a handful of matches.

Wikipedia disambiguation

Method: Many of the methods above are great for grouping similar/related terms, but do not provide a high-confidence method for determining the “master” term or phrase to represent a grouping of related/duplicate terms. While considerations can be made for testing all tags against an English language model, the lack of pop culture references and phrases makes it unreliable. To do this effectively, we found Wikipedia to be a trusted source for identifying the proper spelling, tense, formatting, and word order for any given tag. For example, if users tagged a product as “Lord of the Rings,” “LOTR,” and “The Lord of the Rings,” it can be difficult to determine which tag should be preferred (certainly we don’t need all 3). If you search Wikipedia for these terms, you will see that they redirect you to the page titled “The Lord of the Rings.” In many cases, we can trust their canonical variant as the “good tag.” Please note that we don’t encourage scraping any website or violating their terms of use. Wikipedia does offer an export of their entire database that can be used for research purposes.
Benefits: When a tag could be mapped to a Wikipedia entry, this method proved to be a highly effective at providing validation that a tag had potential value, or creating a point of reference for related tags. If the Wikipedia community felt a tag or tag phrase was important enough to have an article dedicated to it, then the tag was more likely to be a valuable term vs. random entry or keyword stuffing by the user. Further, the methodology allows for grouping related terms without any bias on word order. Doing a search on Wikipedia creates a search results page (“pontoon boats”), or redirects you to a correction of the article (“disneyworld” becomes “Walt Disney World”). Wikipedia also tends to have entries for some pop culture references, so things that would get flagged as a misspelling, such as “lolcats,” can be vindicated by the existence of a matching Wikipedia article.
Limitations: While Wikipedia is effective at delivering a consistent formal tag for disambiguation, it can at times be more sterile than user-friendly. This can run counter to other signals such as CPC or traffic volume methods. For example, “pontoon boats” becomes “Pontoon (Boat)”, or “Lily” becomes “lilium.” All signals indicate the former case as the most popular, but Wikipedia disambiguation suggests the latter to be the correct usage. Wikipedia also contains entries for very broad terms, like each number, year, letter, etc. so simply applying a rule that any Wikipedia article is an allowed tag would continue to contribute to tag sprawl problems.

K-means clustering with word vectors

Method: Finally, we attempted to transform the tags into a subset of more meaningful tags using word embeddings and k-means clustering. Generally, the process involved transforming the tags into tokens (individual words), then refining by part-of-speech (noun, verb, adjective), and finally lemmatizing the tokens (“blue shirts” becomes “blue shirt”). From there, we transformed all the tokens into a custom Word2Vec embedding model based on adding the vectors of each resulting token array. We created a label array and a vector array of each tag in the dataset, then ran k-means with 10 percent of the total count of the tags as the value for number of centroids. At first we tested on 30,000 tags and obtained reasonable results.

Once k-means had completed, we pulled all of the centroids and obtained their nearest relative from the custom Word2Vec model, then we assigned the tags to their centroid category in the main dataset.

Tag Tokens	Tag Pos	Tag Lemm.	Categorization
[‘beach’, ‘photographs’]	[(‘beach’, ‘NN’), (‘photographs’, ‘NN’)]	[‘beach’, ‘photograph’]	beach photo
[‘seaside’, ‘photographs’]	[(‘seaside’, ‘NN’), (‘photographs’, ‘NN’)]	[‘seaside’, ‘photograph’]	beach photo
[‘coastal’, ‘photographs’]	[(‘coastal’, ‘JJ’), (‘photographs’, ‘NN’)]	[‘coastal’, ‘photograph’]	beach photo
[‘seaside’, ‘photographs’]	[(‘seaside’, ‘NN’), (‘photographs’, ‘NN’)]	[‘seaside’, ‘photograph’]	beach photo
[‘seaside’, ‘posters’]	[(‘seaside’, ‘NN’), (‘posters’, ‘NNS’)]	[‘seaside’, ‘poster’]	beach photo
[‘coast’, ‘photographs’]	[(‘coast’, ‘NN’), (‘photographs’, ‘NN’)]	[‘coast’, ‘photograph’]	beach photo
[‘beach’, ‘photos’]	[(‘beach’, ‘NN’), (‘photos’, ‘NNS’)]	[‘beach’, ‘photo’]	beach photo

The Categorization column above was the centroid selected by Kmeans. Notice how it handled the matching of “seaside” to “beach” and “coastal” to “beach.”

Benefits: This method seemed to do a good job of finding associations between the tags and their categories that were more semantic than character-driven. “Blue shirt” might be matched to “clothing.” This was obviously not possible without the semantic relationships found within the vector space.
Limitations: Ultimately, the chief limitation that we encountered was trying to run k-means on the full two million tags while ending up with 200,000 categories (centroids). Sklearn for Python allows for multiple concurrent jobs, but only across the initialization of the centroids, which in this case was 11 — meaning that even if you ran on a 60-core processor, the number of concurrent jobs was limited by the number of initialization, which in this case, was again 11. We tried PCA (principal component analysis) to reduce the vector sizes (300 to 10) but the results were overall poor. Finally, because embeddings are generally built based on probabilistic closeness of terms in the corpus on which they were trained, there were matches that you could understand why they matched, but would obviously not have been the correct category (eg “19th century art” was picked as a category for “18th century art”). Finally, context matters and the word embeddings obviously suffer from understanding the difference between “duck” (the animal) and “duck” (the action).

Bringing it all together

Using a combination of the methods above, we were able to develop a series of methodology confidence scores that could be applied to any tag in our dataset, generating a heuristic for how to consider each tag going forward. These were case-level strategies to determine the appropriate methodology. We denoted these as follows:

Good Tags: This mostly started as our “do not touch” list of terms which already received traffic from Google. After some confirmation exercises, the list was expanded to include unique terms with rankings potential, commercial appeal, and unique product sets to deliver to customers. For example, a heuristic for this category might look like this:
1. If tag is identical to Wikipedia entry and
2. Tag + product has estimated search traffic and
3. Tag has CPC value then
4. Mark as “Good Tag”
Okay Tags: This represents terms that we would like to retain associated with products and their descriptions, as they could be used within the site to add context to a page, but do not warrant their own indexable space. These tags were mapped to be redirected or canonicaled to a “master,” but still included on a page for topical relevancy, natural language queries, long-tail searches, etc. For example, a heuristic for this category might look like this:
1. If tag is identical to Wikipedia entry but
2. Tag + product has no search volume
3. Vector tag matches a “Good Tag”
4. Mark as “Okay Tag” and redirect to “Good Tag”
Bad Tags to Remap: This grouping represents bad tags that were mapped to a replacement. These tags would literally be deleted and replaced with a corrected version. These were most often misspellings or terms discovered through stemming/lemmatization/etc. where a dominant replacement was identified. For example, a heuristic for this category might look like this:
1. If tag is not identical to either Wikipedia or vector space and
2. Tag + product has no search volume
3. Tag has no volume
4. Tag Wikipedia entry matches a “Good Tag”
5. Mark as “Bad Tag to Remap”
Bad Tags to Remove: These are tags that were flagged as bad tags that could not be related to a good tag. Essentially, these needed to be removed from our database completely. This final group represented the worst of the worst in the sense that the existence of the tag would likely be considered a negative indicator of site quality. Considerations were made for character length of tags, lack of Wikipedia entries, inability to map to word vectors, no previous traffic, no predicted traffic or CPC value, etc. In many cases, these were nonsense phrases.

All together, we were able to reduce the number of tags by 87.5%, consolidating the site down to a reasonable, targeted, and useful set of tags which properly organized the corpus without wasting either crawl budget or limiting user engagement.

Conclusions: Advanced white hat SEO

It was nearly nine years ago that a well-known black hat SEO called out white hat SEO as being simple, stale, and bereft of innovation. He claimed that “advanced white hat SEO” was an oxymoron — it simply did not exist. I was proud at the time to respond to his claims with a technique Hive Digital was using which I called “Second Page Poaching.” It was a great technique, but it paled in comparison to the sophistication of methods we now see today. I never envisioned either the depth or breadth of technical proficiency which would develop within the white hat SEO community for dealing with unique but persistent problems facing webmasters.

I sincerely doubt most of the readers here will have the specific tag sprawl problem described above. I’d be lucky if even a few of you have run into it. What I hope is that this post might disabuse us of any caricatures of white hat SEO as facile or stagnant and inspire those in our space to their best work.

Lessons from 1,000 Voice Searches (on Google Home)

Posted on May 23, 2017 by jackburnsblog

Posted by Dr-Pete

It’s hardly surprising that Google Home is an extension of Google’s search ecosystem. Home is attempting to answer more and more questions, drawing those answers from search results. There’s an increasingly clear connection between Featured Snippets in search and voice answers.

For example, let’s say a hedgehog wanders into your house and you naturally find yourself wondering what you should feed it. You might search for “What do hedgehogs eat?” On desktop, you’d see a Featured Snippet like the following:

Given that you’re trying to wrangle a strange hedgehog, searching on your desktop may not be practical, so you ask Google Home: “Ok, Google — What do hedgehogs eat?” and hear the following:

Google Home leads with the attribution to Ark Wildlife (since a voice answer has no direct link), and then repeats a short version of the desktop snippet. The connection between the two answers is, I hope, obvious.

Anecdotally, this is a pattern we see often on Google Home, but how consistent is it? How does Google handle Featured Snippets in other formats (including lists and tables)? Are some questions answered wildly differently by Google Home compared to desktop search?

Methodology (10K –> 1K)

To find out the answer to these questions, I needed to start with a fairly large set of searches that were likely to generate answers in the form of Featured Snippets. My colleague Russ Jones pulled a set of roughly 10,000 popular searches beginning with question words (Who, What, Where, Why, When, How) from a third-party “clickstream” source (actual web activity from a very large set of users).

I ran those searches on desktop (automagically, of course) and found that just over half (53%) had Featured Snippets. As we’ve seen in other data sets, Google is clearly getting serious about direct answers.

The overall set of popular questions was dominated by “What?” and “How?” phrases:

Given the prevalence of “How to?” questions, I’ve broken them out in this chart. The purple bars show how many of these searches generated Featured Snippets. “How to?” questions were very likely to display a Featured Snippet, with other types of questions displaying them less than half of the time.

Of the roughly 5,300 searches in the full data set that had Featured Snippets, those snippets broke down into four types, as follows:

Text snippets — paragraph-based answers like the one at the top of this post — accounted for roughly two-thirds of all of the Featured Snippets in our original data set. List snippets accounted for just under one-third — these are bullet lists, like this one for “How to draw a dinosaur?”:

Step 1 – Draw a small oval. Step 5 – Dinosaur! It’s as simple as that.

Table snippets made up less than 2% of the Featured Snippets in our starting data set. These snippets contain a small amount of tabular data, like this search for “What generation am I?”:

If you throw your money recklessly at your avocado toast habit instead of buying a house, you’re probably a millennial (sorry, content marketing joke).

Finally, video snippets are a special class of Featured Snippet with a large video thumbnail and direct link (dominated by YouTube). Here’s one for “Who is the spiciest memelord?”:

I’m honestly not sure what commentary I can add to that result. Since there’s currently no way for a video to appear on Google Home, we excluded video snippets from the rest of the study.

Google has also been testing some hybrid Featured Snippets. In some cases, for example, they attempt to extract a specific answer from the text, such as this answer for “When was 1984 written?” (Hint: the answer is not 1984):

For the purposes of this study, we treated these hybrids as text snippets. Given the concise answer at the top, these hybrids are well-suited to voice results.

From the 5.3K questions with snippets, I selected 1,000, excluding video but purposely including a disproportionate number of list and table types (to better see if and how those translated into voice).

Why only 1,000? Because, unlike desktop searches, there’s no easy way to do this. Over the course of a couple of days, I had to run all of these voice searches manually on Google Home. It’s possible that I went temporarily insane. At one point, I saw a spider on my Google Home staring back at me. Fearing that I was hallucinating, I took a picture and posted it on Twitter:

I was assured that the spider was, in point of fact, not a figment of my imagination. I’m still not sure about the half-hour when the spider sang me selections from the Hamilton soundtrack.

From snippets to voice answers

So, how many of the 1,000 searches yielded voice answers? The short answer is: 71%. Diving deeper, it turns out that this percentage is strongly dependent on the type of snippet:

Text snippets in our 1K data set yielded voice answers 87% of the time. List snippets dropped to just under half, and table snippets only generated voice answers one-third of the time. This makes sense — long lists and most tables are simply harder to translate into voice.

In the case of tables, some of these results were from different sites or in a different format. In other words, the search generated a Featured Snippet and a voice answer, but the voice answer was of a different type (text, for example) and attributed to a different source. Only 20% of Featured Snippets in table format generated voice answers that came from the same source.

From a search marketing standpoint, text snippets are going to generate a voice answer almost 9 out of 10 times. Optimizing for text/paragraph snippets is a good starting point for ranking on voice search and should generally be a win-win across devices.

Special: Knowledge Graph

What about the Featured Snippets that didn’t generate voice answers? It turns out there was quite a variety of exceptions in play. One exception was answers that came directly from the Knowledge Graph on Google Home, without any attribution. For example, the question “What is the nuclear option?” produces this Featured Snippet (for me, at least) on desktop:

On Google Home, though, I get an unattributed answer that seems to come from the Knowledge Graph:

It’s unclear why Google has chosen one over the other for voice in this particular case. Across the 1,000 keyword set, there were about 30 keywords where something similar happened.

Special: Device help

Google Home seems to translate some searches as device-specific help. For example, “How to change your name?” returns desktop results about legally changing your name as an individual. On Google Home, I get the following:

Other searches from our list that triggered device help include:

How to contact Google?
How to send a fax online?
What are you up to?

Special: Easter eggs

Google Home has some Easter eggs that seem unique to voice search. One of my personal favorites — the question “What is best in life?” — generates the following:

Here’s a list of the other Easter eggs in our 1,000 phrase data set:

How many letters are in the alphabet?
What are your strengths?
What came first, the chicken or the egg?
What generation am I?
What is the meaning of life?
What would you do for a Klondike bar?
Where do babies come from?
Where in the world is Carmen Sandiego?
Where is my iPhone?
Where is Waldo?
Who is your daddy?

Easter eggs are a bit less predictable than device help. Generally speaking, though, both are rare and shouldn’t dissuade you from trying to rank for Featured Snippets and voice answers.

Special: General confusion

In a handful of cases, Google simply didn’t understand the question or couldn’t answer the exact question. For example, I could not get Google to understand the question “What does MAGA mean?” The answer I got back (maybe it’s my Midwestern accent?) was:

On second thought, maybe that’s not entirely inaccurate.

One interesting case is when Google decides to answer a slightly different question. On desktop, if you search for “How to become a vampire?”, you might see the following Featured Snippet:

On Google Home, I’m asked to clarify my intent:

I suspect both of these cases will improve over time, as voice recognition continues to advance and Google becomes better at surfacing answers.

Special: Recipe results

Back in April, Google launched a new set of recipe functions across search and Google Home. Many “How to?” questions related to cooking now generate something like this (the question I asked was “How to bake chicken breast?”):

You can opt to find a recipe on Google search and send it to your Google Home, or Google can simply pick a recipe for you. Either way, it will guide you through step-by-step instructions.

Special: Health conditions

A half-dozen or so health questions, from general questions to diseases, generated results like the following. This one is for the question “Why do we sneeze?”:

This has no clear connection to desktop search results, and I’m not clear if it’s a signal for future, expanded functionality. It seems to be of limited use right now.

Special: WikiHow

A handful of “How to?” questions triggered an unusual response. For example, if I ask Google Home “How to write a press release?” I get back:

If I say “yes,” I’m taken directly to a wikiHow assistant that uses a different voice. The wikiHow answers are much longer than text-based Featured Snippets.

How should we adapt?

Voice search and voice appliances (including Google Assistant and Google Home) are evolving quickly right now, and it’s hard to know where any of this will be in the next couple of years. From a search marketing standpoint, I don’t think it makes sense to drop everything to invest in voice, but I do think we’ve reached a point where some forward momentum is prudent.

First, I highly recommend simply being aware of how your industry and your major keywords/questions “appear” on Google Home (or Google Assistant on your mobile device). Look at the recipe situation above — for 99%+ of the people reading this article, that’s a novelty. If you’re in the recipe space, though, it’s game-changing, and it’s likely a sign of more to come.

Second, I feel strongly that Featured Snippets are a win-win right now. Almost 90% of the text-only Featured Snippets we tracked yielded a voice answer. These snippets are also prominent on desktop and mobile searches. Featured Snippets are a great starting point for understanding the voice ecosystem and establishing your foothold.

Location Data + Reviews: The 1–2 Punch of Local SEO

Posted on May 22, 2017 by jackburnsblog

Posted by MiriamEllis

My father, a hale and hearty gentleman in his seventies, simply won’t dine at a new restaurant these days before he checks its reviews on his cell phone. Your 23-year-old nephew, who travels around the country for his job as a college sports writer, has devoted 233 hours of his young life to writing 932 reviews on Yelp (932 reviews x @15 minutes per review).

Yes, our local SEO industry knows that my dad and your nephew need to find accurate NAP on local business listings to actually find and get to business locations. This is what makes our historic focus on citation data management totally reasonable. But reviews are what help a business to be chosen. Phil Rozek kindly highlighted a comment of mine as being among the most insightful on the Local Search Ranking Factors 2017 survey:

“If I could drive home one topic in 2017 for local business owners, it would surround everything relating to reviews. This would include rating, consumer sentiment, velocity, authenticity, and owner responses, both on third-party platforms and native website reviews/testimonials pages. The influence of reviews is enormous; I have come to see them as almost as powerful as the NAP on your citations. NAP must be accurate for rankings and consumer direction, but reviews sell.”

I’d like to take a few moments here to dive deeper into that list of review elements. It’s my hope that this post is one you can take to your clients, team or boss to urge creative and financial allocations for a review management campaign that reflects the central importance of this special form of marketing.

Ratings: At-a-glance consumer impressions and impactful rankings filter

Whether they’re stars or circles, the majority of rating icons send a 1–5 point signal to consumers that can be instantly understood. This symbol system has been around since at least the 1820s; it’s deeply ingrained in all our brains as a judgement of value.

So, when a modern Internet user is making a snap decision, like where to grab a taco, the food truck with 5 Yelp stars is automatically going to look more appealing than the one with only 2. Ratings can also catch the eye when Schema (or Google serendipity) causes them to appear within organic SERPs or knowledge panels.

All of the above is well-understood, but while the exact impact of high star ratings on local pack rankings has long been speculative (it’s only factor #24 in this year’s Local Search Ranking Factors), we may have just reached a new day with Google. The ability to filter local finder results by rating has been around for some time, but in May, Google began testing the application of a “highly rated” snippet on hotel rankings in the local packs. Meanwhile, searches with the format of “best X in city” (e.g. best burrito in Dallas) appear to be defaulting to local results made up of businesses that have earned a minimum average of 4 stars. It’s early days yet, but totally safe for us to assume that Google is paying increased attention to numeric ratings as indicators of relevance.

Because we’re now reaching the point from which we can comfortably speculate that high ratings will tend to start correlating more frequently with high local rankings, it’s imperative for local businesses to view low ratings as the serious impediments to growth that they truly are. Big brands, in particular, must stop ignoring low star ratings, or they may find themselves not only having to close multiple store locations, but also, to be on the losing end of competing for rankings for their open stores when smaller competitors surpass their standards of cleanliness, quality, and employee behavior.

Consumer sentiment: The local business story your customers are writing for you

Here is a randomly chosen Google 3-pack result when searching just for “tacos” in a small city in the San Francisco Bay Area:

We’ve just been talking about ratings, and you can look at a result like this to get that instant gut feeling about the 4-star-rated eateries vs. the 2-star place. Now, let’s open the book on business #3 and see precisely what kind of story its consumers are writing. This is the first step towards doing a professional review audit for any business whose troubling reviews may point to future closure if problems aren’t fixed. A full audit would look at all relevant review platforms, but we’ll be brief here and just look at Google and Yelp and sort negative sentiments by type:

It’s easy to ding fast food chains. Their business model isn’t commonly associated with fine dining or the kind of high wages that tend to promote employee excellence. In some ways, I think of them as extreme examples. Yet, they serve as good teaching models for how even the most modest-quality offerings create certain expectations in the minds of consumers, and when those basic expectations aren’t met, it’s enough of a story for consumers to share in the form of reviews.

This particular restaurant location has an obvious problem with slow service, orders being filled incorrectly, and employees who have not been trained to represent the brand in a knowledgeable, friendly, or accessible manner. Maybe a business you are auditing has pain points surrounding outdated fixtures or low standards of cleanliness.

Whatever the case, when the incoming consumer turns to the review world, their eyes scan the story as it scrolls down their screen. Repeat mentions of a particular negative issue can create enough of a theme to turn the potential customer away. One survey says only 13% of people will choose a business that has wound up with a 1–2 star rating based on poor reviews. Who can afford to let the other 87% of consumers go elsewhere?

There are 20 restaurants showing up in Google’s local finder for my “tacos” search, highlighted above. Taco Bell is managing to hold the #3 spot in the local pack right now, perhaps due to brand authority. My question is, what happens next, particularly if Google is going to amplify ratings and review sentiment in the overall local ranking mix? Will this chain location continue to beat out 4-star restaurants with 100+ positive reviews, or will it slip down as consumers continue to chronicle specific and unresolved issues?

No third-party brand controls Google, but your brand can open the book right now and make maximum use of the story your customers are constantly publishing — for free. By taking review insights as real and representative of all the customers who don’t speak up, and by actively addressing repeatedly cited issues, you could be making one of the smartest decisions in your company’s history.

Velocity/recency: Just enough of a timely good thing

This is one of the easiest aspects of review management to teach clients. You can sum it up in one sentence: don’t get too many reviews at once on any given platform but do get enough reviews on an ongoing basis to avoid looking like you’ve gone out of business.

For a little more background on the first part of that statement, watch Mary Bowling describing in this LocalU video how she audited a law firm that went from zero to thirty 5-star reviews within a single month. Sudden gluts of reviews like this not only look odd to alert customers, but they can trip review platform filters, resulting in removal. Remember, reviews are a business lifetime effort, not a race. Get a few this month, a few next month, and a few the month after that. Keep going.

The second half of the review timing paradigm relates to not running out of steam in your acquisition campaigns. One survey found that 73% of consumers don’t believe that reviews that are older than 3 months are still relevant to them, yet you will frequently encounter businesses that haven’t earned a new review in over a year. It makes you wonder if the place is still in business, or if it’s in business but is so unimpressive that no one is bothering to review it.

While I’d argue that review recency may be more important in review-oriented industries (like restaurants) vs. those that aren’t quite as actively reviewed (like septic system servicing), the idea here is similar to that of velocity, in that you want to keep things going. Don’t run a big review acquisition campaign in January and then forget about outreach for the rest of the year. A moderate, steady pace of acquisition is ideal.

Authenticity: Honesty is the only honest policy

For me, this is one of the most prickly and interesting aspects of the review world. Three opposing forces meet on this playing field: business ethics, business education, and the temptations engendered by the obvious limitations of review platforms to police themselves.

I recently began a basic audit of a family-owned restaurant for a friend of a friend. Within minutes, I realized that the family had been reviewing their own restaurant on Yelp (a glaring violation of Yelp’s policy). I felt sorry to see this, but being acquainted with the people involved (and knowing them to be quite nice!), I highly doubted they had done this out of some dark impulse to deceive the public. Rather, my guess was that they may have thought they were “getting the ball rolling” for their new business, hoping to inspire real reviews. My gut feeling was that they simply lacked the necessary education to understand that they were being dishonest with their community and how this could lead to them being publicly shamed by Yelp, if caught.

In such a scenario, there is definitely opportunity for the marketer to offer the necessary education to describe the risks involved in tying a brand to misleading practices, highlighting how vital it is to build trust within the local community. Fake positive reviews aren’t building anything real on which a company can stake its future. Ethical business owners will catch on when you explain this in honest terms and can then begin marketing themselves in smarter ways.

But then there’s the other side. Mike Blumenthal recently wrote of his discovery of the largest review spam network he’d ever encountered and there’s simply no way to confuse organized, global review spam with a busy small business making a wrong, novice move. Real temptation resides in this scenario, because, as Blumenthal states:

“Review spam at this scale, unencumbered by any Google enforcement, calls into question every review that Google has. Fake business listings are bad, but businesses with 20, or 50, or 150 fake reviews are worse. They deceive the searcher and the buying public and they stain every real review, every honest business, and Google.”

When a platform like Google makes it easy to “get away with” deception, companies lacking ethics will take advantage of the opportunity. All we can do, as marketers, is to offer the education that helps ethical businesses make honest choices. We can simply pose the question:

Is it better to fake your business’ success or to actually achieve success?

On a final note, authenticity is a two-way street in the review world. When spammers target good businesses with fake, negative reviews, this also presents a totally false picture to the consumer public. I highly recommend reading about Whitespark’s recent successes in getting fake Google reviews removed. No guarantees here, but excellent strategic advice.

Owner responses: Your contributions to the consumer story

In previous Moz blog posts, I’ve highlighted the five types of Google My Business reviews and how to respond to them, and I’ve diagrammed a real-world example of how a terrible owner response can make a bad situation even worse. If the world of owner responses is somewhat new to you, I hope you’ll take a gander at both of those. Here, I’d like to focus on a specific aspect of owner responses, as it relates to the story reviews are telling about your business.

We’ve discussed above the tremendous insight consumer sentiment can provide into a company’s pain points. Negative reviews can be a roadmap to resolving repeatedly cited problems. They are inherently valuable in this regard, and by dint of their high visibility, they carry the inherent opportunity for the business owner to make a very public showing of accountability in the form of owner responses. A business can state all it wants on its website that it offers lightning-quick service, but when reviews complain of 20-minute waits for fast food, which source do you think the average consumer will trust?

The truth is, the hypothetical restaurant has a problem. They’re not going to be able to resolve slow service overnight. Some issues are going to require real planning and real changes to overcome. So what can the owner do in this case?

Whistle past the graveyard, claiming everything is actually fine now, guaranteeing further disappointed expectations and further negative reviews resulting therefrom?
Be gutsy and honest, sharing exactly what realizations the business has had due to the negative reviews, what the obstacles are to fixing the problems, and what solutions the business is implementing to do their best to overcome those obstacles?

Let’s look at this in living color:

In yellow, the owner response is basically telling the story that the business is ignoring a legitimate complaint, and frankly, couldn’t care less. In blue, the owner has jumped right into the storyline, having the guts to take the blame, apologize, explain what happened and promise a fix — not an instant one, but a fix on the way. In the end, the narrative is going to go on with or without input from the owner, but in the blue example, the owner is taking the steering wheel into his own hands for at least part of the road trip. That initiative could save not just his franchise location, but the brand at large. Just ask Florian Huebner:

“Over the course of 2013 customers of Yi-Ko Holding’s restaurants increasingly left public online reviews about “broken and dirty furniture,” “sleeping and indifferent staff,” and “mice running around in the kitchen.” Per the nature of a franchise system, to the typical consumer it was unclear that these problems were limited to this individual franchisee. Consequently, the Burger King brand as a whole began to deteriorate and customers reduced their consumption across all locations, leading to revenue declines of up to 33% for some other franchisees.”

Positive news for small businesses working like mad to compete: You have more agility to put initiatives into quick action than the big brands do. Companies with 1,000 locations may let negative reviews go unanswered because they lack a clear policy or hierarchy for owner responses, but smaller enterprises can literally turn this around in a day. Just sit down at the nearest computer, claim your review profiles, and jump into the story with the goal of hearing, impressing, and keeping every single customer you can.

Big brands: The challenge for you is larger, by dint of your size, but you’ve also likely got the infrastructure to make this task no problem. You just have to assign the right people to the job, with thoughtful guidelines for ensuring your brand is being represented in a winning way.

NAP and reviews: The 1–2 punch combo every local business must practice

When traveling salesman Duncan Hines first published his 1935 review guide Adventures in Good Eating, he was pioneering what we think of today as local SEO. Here is my color-coded version of his review of the business that would one day become KFC. It should look strangely familiar to every one of you who has ever tackled citation management:

No phone number on this “citation,” of course, but then again telephones were quite a luxury in 1935. Barring that element, this simple and historic review has the core earmarks of a modern local business listing. It has location data and review data; it’s the 1–2 punch combo every local business still needs to get right today. Without the NAP, the business can’t be found. Without the sentiment, the business gives little reason to be chosen.

Are you heading to a team meeting today? Preparing to chat with an incoming client? Make the winning combo as simple as possible, like this:

We’ve got to manage our local business listings so that they’re accessible, accurate, and complete. We can automate much of this (check out Moz Local) so that we get found.
We’ve got to breathe life into the listings so that they act as interactive advertisements, helping us get chosen. We can do this by earning reviews and responding to them. This is our company heartbeat — our story.

From Duncan Hines to the digital age, there may be nothing new under the sun in marketing, but when you spend year after year looking at the sadly neglected review portions of local business listings, you realize you may have something to teach that is new news to somebody. So go for it — communicate this stuff, and good luck at your next big meeting!

Blog Post Ideas: Maximize Your Reach with the Right Topics – Whiteboard Friday

Posted on May 19, 2017 by jackburnsblog

Posted by randfish

With the ubiquity of blogs, one of the questions we hear the most is how to come up with the right topics for new posts. In today’s episode of Whiteboard Friday, Rand explores six different paths to great blog topic ideas, and tells you what you need to keep in mind before you start.

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Video transcription

Howdy, Moz fans, and welcome to another edition of Whiteboard Friday. This week, we’re going to chat about blog post ideas, how to have great ones, how to make sure that the topics that you’re covering on your blog actually accomplish the goals that you want, and how to not run out of ideas as well.

The goals of your blog

So let’s start with the goals of a blog and then what an individual post needs to do, and then I’ll walk you through kind of six formats for coming up with great ideas for what to blog about. But generally speaking, you have created a blog, either on your company’s website or your personal website or for the project that you’re working on, because you want to:

Attract a certain audience, which is great.
Capture the attention and amplification, the sharing of certain types of influencers, so that you can grow that audience.
Rank highly in search engines. That’s not just necessarily a goal for the blog’s content itself. But one of the reasons that you started a blog is to grow the authority, the ranking signals, the ability to rank for the website as a whole, and the blog hopefully is helping with that.
Inspire some trust, some likeability, loyalty, and maybe even some evangelism from your readers.
Provide a reference point for their opinions. So if you are a writer, an author, a journalist, a contributor to all sorts of sources, a speaker, whatever it is, you’re trying to provide a home for your ideas and your content, potentially your opinions too.
Covert our audience to take an action. Then, finally, many times a blog is crafted with the idea that it is a first step in capturing an audience that will then take an action. That could be buy something from you, sign up for an email list, potentially take a free trial of something, maybe take some action. A political blog might be about, “Call your Congress person.” But those types of actions.

What should an individual post do?

From there, we get into an individual post. An individual post is supposed to help with these goals, but on its own doesn’t do all of them. It certainly doesn’t need to do more than one at a time. It can hopefully do some. But one of those is, generally speaking, a great blog post will do one of these four things and hopefully two or even three.

I. Help readers to accomplish a goal that they have.

So if I’m trying to figure out which hybrid electric vehicle should I buy and I read a great blog post from someone who’s very, very knowledgeable in the field, and they have two or three recommendations to help me narrow down my search, that is wonderful. It helps me accomplish my goal of figuring out which hybrid car to buy. That accomplishment of goal, that helping of people hits a bunch of these very, very nicely.

II. Designed to inform people and/or entertain them.

So it doesn’t have to be purely informational. It doesn’t have to be purely entertainment, but some combination of those, or one of the two, about a particular topic. So you might be trying to make someone excited about something or give them knowledge around it. It may be knowledge that they didn’t previously know that they wanted, and they may not actually be trying to accomplish a goal, but they are interested in the information or interested in finding the humor.

III. Inspiring some amplification and linking.

So you’re trying to earn signals to your site that will help you rank in search engines, that will help you grow your audience, that will help you reach more influencers. Thus, inspiring that amplification behavior by creating content that is designed to be shared, designed to be referenced and linked to is another big goal.

IV. Creating a more positive association with the brand.

So you might have a post that doesn’t really do any of these things. Maybe it touches a little on informational or entertaining. But it is really about crafting a personal story, or sharing an experience that then draws the reader closer to you and creates that association of what we talked about up here — loyalty, trust, evangelism, likeability.

6 paths to great blog topic ideas

So knowing what our blog needs to do and what our individual posts are trying to do, what are some great ways that we can come up with the ideas, the actual topics that we should be covering? I have kind of six paths. These six paths actually cover almost everything you will read in every other article about how to come up with blog post ideas. But I think that’s what’s great. These frameworks will get you into the mindset that will lead you to the path that can give you an infinite number of blog post ideas.

1. Are there any unanswered or poorly answered questions that are in your field, that your audience already has/is asking, and do you have a way to provide great answers to those?

So that’s basically this process of I’m going to research my audience through a bunch of methodologies, going to come up with topics that I know I could cover. I could deliver something that would answer their preexisting questions, and I could come up with those through…

Surveys of my readers.
In-person meetings or emails or interviews.
Informal conversations just in passing around events, or if I’m interacting with members of my audience in any way, social settings.
Keyword research, especially questions.

So if you’re using a tool like Moz’s Keyword Explorer, or I think some of the other ones out there, Ahrefs might have this as well, where you can filter by only questions. There are also free tools like Answer the Public, which many folks like, that show you what people are typing into Google, specifically in the form of questions, “Who? What? When? Where? Why? How? Do?” etc.

So I’m not just going to walk you through the ideas. I’m also going to challenge myself to give you some examples. So I’ve got two — one less challenging, one much more challenging. Two websites, both have blogs, and coming up with topic ideas based on this.

So one is called Remoters. It’s remoters.net. It’s run by Aleyda Solis, who many of you in the SEO world might know. They talk about remote work, so people who are working remotely. It’s a content platform for them and a service for them. Then, the second one is a company, I think, called Schweiss Doors. They run hydraulicdoors.com. Very B2B. Very, very niche. Pretty challenging to come up with good blog topics, but I think we’ve got some.

Remote Worker: I might say here, “You know what? One of the questions that’s asked very often by remote workers, but is not well-answered on the internet yet is: ‘How do I conduct myself in a remote interview and present myself as a remote worker in a way that I can be competitive with people who are actually, physically on premises and in the room? That is a big challenge. I feel like I’m always losing out to them. Remote workers, it seems, don’t get the benefits of being there in person.'” So a piece of content on how to sell yourself on a remote interview or as a remote worker could work great here.

Hydraulic doors: One of the big things that I see many people asking about online, both in forums which actually rank well for it, the questions that are asked in forums around this do rank around costs and prices for hydraulic doors. Therefore, I think this is something that many companies are uncomfortable answering right online. But if you can be transparent where no one else can, I think these Schweiss Doors guys have a shot at doing really well with that. So how much do hydraulic doors cost versus alternatives? There you go.

2. Do you have access to unique types of assets that other people don’t?

That could be research. It could be data. It could be insights. It might be stories or narratives, experiences that can help you stand out in a topic area. This is a great way to come up with blog post content. So basically, the idea is you could say, “Gosh, for our quarterly internal report, we had to prepare some data on the state of the market. Actually, some of that data, if we got permission to share it, would be fascinating.”

We can see through keyword research that people are talking about this or querying Google for it already. So we’re going to transform it into a piece of blog content, and we’re going to delight many, many people, except for maybe this guy. He seems unhappy about it. I don’t know what his problem is. We won’t worry about him. Wait. I can fix it. Look at that. So happy. Ignore that he kind of looks like the Joker now.

We can get these through a bunch of methodologies:

Research, so statistical research, quantitative research.
Crowdsourcing. That could be through audiences that you’ve already got through email or Facebook or Twitter or LinkedIn.
Insider interviews, interviews with people on your sales team or your product team or your marketing team, people in your industry, buyers of yours.
Proprietary data, like what you’ve collected for your internal annual reports.
Curation of public data. So if there’s stuff out there on the web and it just needs to be publicly curated, you can figure out what that is. You can visit all those websites. You could use an extraction tool, or you could manually extract that data, or you could pay an intern to go extract that data for you, and then synthesize that in a useful way.
Multimedia talent. Maybe you have someone, like we happen to here at Moz, who has great talent with video production, or with audio production, or with design of visuals or photography, or whatever that might be in the multimedia realm that you could do.
Special access to people or information, or experiences that no one else does and you can present that.

Those assets can become the topic of great content that can turn into really great blog posts and great post ideas.

Remote Workers: They might say, “Well, gosh, we have access to data on the destinations people go and the budgets that they have around those destinations when they’re staying and working remotely, because of how our service interacts with them. Therefore, we can craft things like the most and least expensive places to work remotely on the planet,” which is very cool. That’s content that a lot of people are very interested in.

Hydraulic doors: We can look at, “Hey, you know what? We actually have a visual overlay tool that helps an architect or a building owner visualize what it will look like if a hydraulic door were put into place. We can go use that in our downtime to come up with we can see how notable locations in the city might look with hydraulic doors or notable locations around the world. We could potentially even create a tool, where you could upload your own visual, photograph, and then see how the hydraulic door looked on there.” So now we can create images that will help you share.

3. Relating a personal experience or passion to your topic in a resonant way.

I like this and I think that many personal bloggers use it well. I think far too few business bloggers do, but it can be quite powerful, and we’ve used it here at Moz, which is relating a personal experience you have or a passion to your topic in some way that resonates. So, for example, you have an interaction that is very complex, very nuanced, very passionate, perhaps even very angry. From that experience, you can craft a compelling story and a headline that draws people in, that creates intrigue and that describes something with an amount of emotion that is resonant, that makes them want to connect with it. Because of that, you can inspire people to further connect with the brand and potentially to inform and entertain.

There’s a lot of value from that. Usually, it comes from your own personal creativity around experiences that you’ve had. I say “you,” you, the writer or the author, but it could be anyone in your organization too. Some resources I really like for that are:

Photos. Especially, if you are someone who photographs a reasonable portion of your life on your mobile device, that can help inspire you to remember things.
A journal can also do the same thing.
Conversations that you have can do that, conversations in person, over email, on social media.
Travel. I think any time you are outside your comfort zone, that tends to be those unique things.

Remote workers: I visited an artist collective in Santa Fe, New Mexico, and I realized that, “My gosh, one of the most frustrating parts of remote work is that if you’re not just about remote working with a laptop and your brain, you’re almost removed from the experience. How can you do remote work if you require specialized equipment?” But in fact, there are ways. There are maker labs and artist labs in cities all over the planet at this point. So I think this is a topic that potentially hasn’t been well-covered, has a lot of interest, and that personal experience that I, the writer, had could dig into that.

Hydraulic doors: So I’ve had some conversations with do-it-yourselfers, people who are very, very passionate about DIY stuff. It turns out, hydraulic doors, this is not a thing that most DIYers can do. In fact, this is a very, very dramatic investment. That is an intense type of project. Ninety-nine percent of DIYers will not do it, but it turns out there’s actually search volume for this.

People do want to, or at least want to learn how to, DIY their own hydraulic doors. One of my favorite things, after realizing this, I searched, and then I found that Schweiss Doors actually created a product where they will ship you a DIY kit to build your own hydraulic door. So they did recognize this need. I thought that was very, very impressive. They didn’t just create a blog post for it. They even served it with a product. Super-impressive.

4. Covering a topic that is “hot” in your field or trending in your field or in the news or on other blogs.

The great part about this is it builds in the amplification piece. Because you’re talking about something that other people are already talking about and potentially you’re writing about what they’ve written about, you are including an element of pre-built-in amplification. Because if I write about what Darren Rowse at ProBlogger has written about last week, or what Danny Sullivan wrote about on Search Engine Land two weeks ago, now it’s not just my audience that I can reach, but it’s theirs as well. Potentially, they have some incentive to check out what I’ve written about them and share that.

So I could see that someone potentially maybe posted something very interesting or inflammatory, or wrong, or really right on Twitter, and then I could say, “Oh, I agree with that,” or, “disagree,” or, “I have nuance,” or, “I have some exceptions to that.” Or, “Actually, I think that’s an interesting conversation to which I can add even more value,” and then I create content from that. Certainly, social networks like:

Twitter
Instagram
Forums
Subreddits. I really like Pocket for this, where I’ll save a bunch of articles, and then I’ll see which one might be very interesting to cover or write about in the future. News aggregators are great for this too. So that could be a Techmeme in the technology space, or a Memeorandum in the political space, or many others.

Remote workers: You might note, well, health care, last week in the United States and for many months now, has been very hot in the political arena. So for remoters, that is a big problem and a big question, because if your health insurance is tied to your employer again, as it was before the American Care Act, then you could be in real trouble. Then you might have a lot of problems and challenges. So what does the politics of health care mean for remote workers? Great. Now, you’ve created a real connection, and that could be something that other outlets would cover and that people who’ve written about health care might be willing to link to your piece.

Hydraulic doors: One of the things that you might note is that Eater, which is a big blog in the restaurant space, has written about indoor and outdoor space trends in the restaurant industry. So you could, with the data that you’ve got and the hydraulic doors that you provide, which are very, very common, well moderately common, at least in the restaurant indoor/outdoor seating space, potentially cover that. That’s a great way to tie in your audience and Eater’s audience into something that’s interesting. Eater might be willing to cover that and link to you and talk about it, etc.

The last two, I’m not going to go too into depth, because they’re a little more basic.

5. Pure keyword research-driven.

So this is using Google AdWords or keywordtool.io, or Moz’s Keyword Explorer, or any of the other keyword research tools that you like to figure out: What are people searching for around my topic? Can I cover it? Can I make great content there?

6. Readers who care about my topics also care about ______________?

Essentially taking any of these topics, but applying one level of abstraction. What I mean by that is there are people who care about your topic, but also there’s an overlap of people who care about this other topic and who also care about yours.

hydraulic doors: People who care about restaurant building trends and hydraulic doors has a considerable overlap, and that is quite interesting.

Remote workers: It could be something like, “I care about remote work. I also care about the gear that I use, my laptop and my bag, and those kinds of things.” So gear trends could be a very interesting intersect. Then, you can apply any of these other four processes, five processes onto that intersection or one level of an abstraction.

All right, everyone. We have done a tremendous amount here to cover a lot about blog topics. But I think you will have some great ideas from this, and I look forward to hearing about other processes that you’ve got in the comments. Hopefully, we’ll see you again next week for another edition of Whiteboard Friday. Take care.

Video transcription by Speechpad.com

Tasty SEO Report Recipes to Save Time & Add Value for Clients [Next Level]

Posted on May 17, 2017 by jackburnsblog

Posted by jocameron

Reporting can be the height of tedium. You spend your time making those reports, your client may (or may not) spend their time trying to understand them. And then, in the end, we’re all left with some unanswered questions and a rumble in the tum of dissatisfaction.

I’m going to take some basic metrics, throw in some culinary metaphors, and take your client reporting to the next level.

By the end of this article you’ll know how to whip up intelligent SEO reports for your clients (or potential clients) that will deliver actionable insights any search chef worth their salt would be proud of.

[Part one] Freshly foraged keywords on sourdough to power your campaign

I’ve got intel on some really tasty keywords; did you know you can scoop these up like wild porcini mushrooms using your website categories? The trick is to find the keywords that you can use to make a lovely risotto, and discard the ones that taste nasty.

The overabundance of keywords has become a bit of a challenge for SEOs. Google is better at gauging user intent — it’s kind of their thing, right? This results in the types of keywords that send traffic to your clients expanding, and it’s becoming trickier to track every. single. keyword. Of course, with a budget big enough almost anything is possible, but why hemorrhage cash on tracking the keyword minutiae when you can wrangle intelligent data by tracking a sample of keywords from a few pots?

With Keyword Explorer, you can save your foraged terms to lists. By bundling together similar “species,” you’ll get a top-level view of the breadth and depth of search behavior within the categories of your niche. Easily compare volume, difficulty, opportunity, and potential to instigate a data-driven approach to website architecture. You’ll also know, at a glance, where to expand on certain topics and apply more resources to content creation.

With these metrics in hand and your client’s industry knowledge, you can cherry-pick keywords to track ranking positions week over week and add them to your Moz Pro campaign with the click of a button.

What’s the recipe?

Step 1: Pluck keywords from the category pages of your client’s site.

Step 2: Find keyword suggestions in Keyword Explorer.

Step 3: Group by low lexicon to bundle together similar keywords to gather up that long tail.

Step 4: Analyze and save relevant results to a list

Step 5: Head to the Keyword Lists and compare the metrics: where is the opportunity? Can you compete with the level of difficulty? Is there a high-volume long tail that you can dig in to?

Step 6: Add sample keywords from your pots directly to your campaign.

Bonus step: Repeat for products or other topic segments of the niche.

Don’t forget to drill into the keywords that are turning up here to see if there are categories and subcategories you hadn’t thought of. These can be targeted in existing content to further extend the relevancy and reach of your client’s content. Or it may inspire new content which can help to grow the authority of the site.

Why your client will be impressed

Through solid, informed research, you’ll be able to demonstrate why their site should be structured with certain categories on the top-level navigation right down to product pages. You’ll also be able to prioritize work on building, improving, or refining content on certain sections of the site by understanding the breakdown of search behavior and demand. Are you seeing lots of keywords with a good level of volume and lower difficulty? Or more in-depth long tail with low search volume? Or fewer different keywords with high search volume but stronger competition?

Let the demand drive the machine forward and make sure you’re giving the hordes what they want.

All this helps to further develop your understanding of the ways people search so you can make informed decisions about which keywords to track.

[Part two] Palate-cleansing lemon keyword label sorbet

Before diving into the next course you need to cleanse your palate with a lemon “label” sorbet.

In Part One, we talked about the struggle of maintaining gigantic lists of keywords. We’ve sampled keywords from our foraged pots, keeping these arranged and segmented in our Moz Pro campaign.

Now you want to give those tracked keywords a more defined purpose in life. This will help to reinforce to your client why you’re tracking these keywords, what the goal is for tracking them, and in what sort of timeframe you’re anticipating results.

Types of labels may include:

Local keywords: Is your business serving local people, like a mushroom walking tour? You can add geo modifiers to your keywords and label them as such.
Long-tail keywords: Might have lower search volume, but focused intent can convert well for your client.
High-priority keywords: Where you’re shoveling more resources, these keywords are more likely impacting the other keyword segments.
Brand keywords: Mirror, mirror on the wall… yeah, we all want those vanity keywords, don’t lie. You can manage brand keywords automatically through “Manage Brand Rules” in Moz Pro:

A generous scoop of tasty lemon “label” sorbet will make all the work you do and progress you achieve infinitely easier to report on with clear, actionable focus.

What’s the recipe?

Step 1: Label your keywords like a pro.

Step 2: Filter by labels in the Ranking tab to analyze Search Visibility for your keyword segments.

In this example, I’m comparing our visibility for “learn” keywords against “guide” keywords:

Step 3: Create a custom report for your keyword segments.

Step 4: Add a drizzle of balsamic vinegar by triggering the Optimize button — now you can send the latest on-page reporting with your super-focused ranking report.

Why your client will be impressed

Your ranking reports will be like nothing your client has ever tasted. They will be tightly focused on the segments of keywords you’re working on, so they aren’t bamboozled by a new slew of keywords or a sudden downward trend. By clearly segmenting your piles of lovely keywords, you’ll be proactively answering those inevitable queries about why, when, and in what form your client will begin to see results.

With the on-page scores updating automatically and shipping out to your client’s inbox every month via a custom report, you’ll be effortlessly highlighting what your team has achieved.

[Part three] Steak sandwich links with crispy competitor bacon

You’re working with your client to publish content, amplifying it through social channels and driving brand awareness through PR campaigns.

Now you want to keep them informed of the big wins you’ve had as a result of that grind. Link data in Moz Pro focuses on the highest-quality links with our Mozscape index, coming from the most prominent pages of authoritative sites. So, while you may not see every link for a site within our index, we’re reporting the most valuable ones.

Alongside our top-quality steak sarnie, we’re add some crispy competitor bacon so you can identify what content is working for the other sites in your industry.

What’s the recipe?

Step 1: Check that you have direct competitors set up on your campaign.

Step 2: Compare link metrics for your site and your competitors.

Step 4: Head to Top Pages to see what those competitors are doing to get ahead.

Step 5: Compile a delicious report sandwich!

Step 6: Make another report for Top Pages for the bacon-filled sandwich experience.

Why your client will be impressed

Each quality established link gives your client a clear idea of the value of their content and the blood, sweat, and tears of your team.

These little gems are established and more likely to have an impact on their ranking potential. Don’t forget to have a chat with your client where you explain that a link’s impact on rankings takes time.

By comparing this directly with the other sites battling it out for top SERP property, it’s easier to identify progress and achievements.

By highlighting those pesky competitors and their top pages by authority, you’re also getting ahead of that burning question of: How can we improve?

[Part four] Cinnamon-dusted ranking reports with cherry-glazed traffic

Rankings are a staple ingredient in the SEO diet. Much like the ever-expanding keyword list, reporting on rankings has become something we do without thinking enough about that what clients can do with that information.

Dish up an all-singing, all-dancing cinnamon-dusted rankings report with cherry-glazed traffic by illustrating the direct impact these rankings have on organic traffic. Real people, coasting on through the search results to your client’s site.

Landing Pages in Moz Pro compares rankings with organic landing pages, imparting not just the ranking score but the value of those pages. Compliments to the chef, because that good work is down to you.

What’s the recipe?

Step 1: Track your target keywords in Moz Pro.

Step 2: Check you’ve hooked up Google Analytics for that tasty traffic data.

Step 3: Discover landing pages and estimated traffic share.

As your SEO work drives more traffic to those pages and your keyword rankings steadily increase, you’ll see your estimated traffic share go up.

If your organic traffic from search is increasing but your ranking is dropping off, it’s an indication that this keyword isn’t the driving force.

Now you can have a dig around and find out why that keyword isn’t performing, starting with your on-page optimization and following up with keyword research.

Why your client will be impressed

We all send ranking reports, and I’m sure clients just love it. But now you can dazzle them with an insight into what those rankings mean for the lifeblood of their site.

You can also take action by directing more energy towards those well-performing keywords, or investigate what worked well for those pages and replicate it across other keywords and pages on your site.

Wrapping up

It’s time to say “enough is enough” and inject some flavor into those bland old SEO reports. Your team will save time and your clients will thank you for the tasty buffet of reporting delight.

Next Level is our educational series combining actionable SEO tips with tools you can use to achieve them. Check out any of our past editions below:

Month: May 2017

5-step solution to SEO for AngularJS

1) Make a list of all pages on your site

2) Install Prerender

3) “Fetch as Google”

4) Configure Google Analytics (or Google Tag Manager)

5) Recrawl the site

Results

One seasoned (age, not steak) traditional marketer’s point of view

It’s OK to question audience targeting — really!

Keywords: Personal intent powerhouses

Individual

Personal

Temporal

The situation settles into stickiness

Low search volume terms (LSVs)

Search engine decrees

But Internet of Things (IoT) Frankenstein devices!

The social effect

Idealism incarnate

A brief introduction to JS indexing

A high-level overview of my view of JavaScript best practices

Resources for auditing JavaScript

Some surprising/interesting results

There are likely to be timeouts on JavaScript execution

It matters how your JS is executed

CRO tests are getting indexed

Split tests show SEO improvements from removing a reliance on JS

Conclusion: How JavaScript indexing might work from a systems perspective

Run a test, get publicity

Video Transcription

Attributes of internal links

Internal versus external links

Ideal internal link structures

The MozCon 2017 Agenda

Monday

Tuesday

Wednesday

Additional Pre-MozCon Sunday Workshops

What is tag sprawl?

The proposed solution

The methods

Spell correction

Bid value

Tag search volume

Unique visitors

Tag count

Porter stemming

Lemmatization

Jaccard index

Jaro-Winkler distance

Keyword Planner grouping

Wikipedia disambiguation

K-means clustering with word vectors

Bringing it all together

Conclusions: Advanced white hat SEO

Methodology (10K –> 1K)

From snippets to voice answers

Special: Knowledge Graph

Special: Device help

Special: Easter eggs

Special: General confusion

Special: Recipe results

Special: Health conditions

Special: WikiHow

How should we adapt?

Ratings: At-a-glance consumer impressions and impactful rankings filter

Consumer sentiment: The local business story your customers are writing for you

Velocity/recency: Just enough of a timely good thing

Authenticity: Honesty is the only honest policy

Owner responses: Your contributions to the consumer story

NAP and reviews: The 1–2 punch combo every local business must practice

Video transcription

The goals of your blog

What should an individual post do?

6 paths to great blog topic ideas

1. Are there any unanswered or poorly answered questions that are in your field, that your audience already has/is asking, and do you have a way to provide great answers to those?

2. Do you have access to unique types of assets that other people don’t?

3. Relating a personal experience or passion to your topic in a resonant way.

4. Covering a topic that is “hot” in your field or trending in your field or in the news or on other blogs.