The Secret SEO Tool of 2016: Machine Learning

Machine learning technology are the secret SEO tools of 2016. As Google and other search engines increasingly incorporate artificial intelligence into their algorithms, SEO practitioners will need to keep pace to rank well.

Until now, SEO practitioners have relied on basic keywords and phrases to focus their efforts. We know from previous patents and code that search engines like Google rely on artificial intelligence and deep neural networks to learn how people think and deliver optimized search results. If we don’t understand and use machine learning tools to evaluate our SEO efforts, we risk an algorithmic ambush.

Consider Google’s major open-source announcement in November 2015, when the company released TensorFlow to the public as open-source software. TensorFlow is a library of software for artificial intelligence; Google has used it and components of it to understand natural language in search. If we can develop similar (albeit smaller-scale) tools or even leverage TensorFlow itself, we could begin to understand how Google sees the language we use in our content.

What can we do to focus our SEO efforts with machine learning? We must learn how machines see the words we write in relation to each other; that’s what Google does. Machine learning algorithms like Latent Dirichlet Allocation (LDA) identify words that cluster together. Once we know what words naturally associate together, we can refine our SEO and content marketing efforts.

Let’s look at an example of how this might work. Suppose we work at a gin company like Nolet Spirits.

Perhaps we have a page on our site about cocktail recipes which use gin, but we’re not ranking well in search for this phrase. What might we want to do with our page to help it rank better? What content might make the most sense for us to write?

We’d start by using an SEO ranking tool to identify what pages and sites currently hold the top spots. I’m partial to SpyFu, but use whatever tool you’re most comfortable with.

Once we know what the top 10-20 pages are, we download the text from those pages to a machine learning tool. Again, this is your choice; use whatever you’re most comfortable with. If you can make TensorFlow work for you, use that. If you prefer Python and NLTK, go with what you know.


Above, we see the broad topics the LDA algorithm has identified. Note how spread out the topics are. This indicates a lot of diversity in the content we downloaded about gin. However, we see a tight cluster in the lower left-hand side; if we dig in, we find these topics all center around tonic:


How does this help our SEO efforts? Topic 12 discusses simple syrups; many of the pages we downloaded share recipes for a simple syrup for use in cocktails with tonic, or as part of making our own tonic water with cinchona bark.

If we’re in charge of Nolet Spirits’ content marketing strategy, we have an entirely new line of content we can create which is closely related to tonic water – which pairs with our gin – but isn’t directly about gin recipes per se. From our analysis, we can draw the insight that we can attract additional search traffic about tonics based on the content from top ranking sites.

Compare this to our old way of doing SEO. We’d write up pages and pages of content optimized for our product names and related generics: Nolet gin, best gin, gin recipes, gin and tonic, etc. Would we know to create content solely about tonic water? Not through this method. Machine learning identified a clustered, closely related topic for us.

Machine learning tools focused around natural language processing are the secret tools of SEO for 2016. Learn the tools. Learn how they work. Become proficient with them. Measure your SEO program by how well your topic model matches the top ranking sites in your industry. You are practicing content innovation – taking old content from other places and remixing it with your own insights to create new, intelligently optimized content.

Disclosure: At the time of this writing, I have no affiliation with Nolet Spirits; I was not asked to write about them in any capacity. I just like their gin.

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3 Key Tactics for Local SEO Success

Whether you have a retail presence or not, local search engine optimization is good for your business. Why? Big brands with big budgets have won the Internet, by and large. Certainly, there are a fair number of unicorns (startups with billion dollar valuations) but compared to the vast number of total companies, most startups competing for search engine placement against large brands don’t do well at the global level.

This scale advantage can be partially mitigated by becoming excellent at local search; Google has made numerous statements that local search, particularly on mobile devices, can give some advantage to smaller businesses that are closer to the querant. Thus, if you’re searching for, say, coffee, a small coffee shop that’s well optimized for local search could reasonably compete with nearby mega-brand franchises.

The same is true of any business that doesn’t serve customers at its location. If you are, say, an email marketing company, having appropriate geographic and local business data will help you win searches in your home city.

In order to effectively compete, at least on Google, for local search, you need to do three activities.

First, set up a My Business account with Google and populate it with the appropriate data. You’ll want to specify your mailing address, phone number, website URL, and any other business data you can provide. This will tell Google where you are located and bind your website URL to your physical location:


Second, tag your geo-data on your website appropriately with microdata. This involves making relatively simple edits to any postal address text on your website that declares the contents are geographic data:


Once you’ve implemented your microdata, you’ll want to verify in a few days that Google has detected it by looking in the Structured Data menu in Webmaster Tools/Search Console:


When you log in, if you don’t see the above entry, your markup data may not be correctly formatted.

Third, ensure your Google Maps listing is correct. If it’s not, use the Suggest an Edit function to fix your listing:


These three tactics must be done together in order to achieve maximum local search impact. Most organizations and competitors do one or two of them, but rarely do companies do all three. Do them well, and you’ll level the playing field a little when someone searches for you on any geo-aware device.

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Do you know how to measure assisted search?

What’s behind the recent resurgence of interest in search engine optimization, SEO?

Shown above: large spikes of mentions in SEO over the last 2 years

Is it because companies feel like the only channels they have control over any more are search and email? Perhaps. Certainly, moves by social networks to undercut companies’ non-paid reach have reduced confidence of marketers in social channels.

Is it because Google’s changing the rules behind search results at an ever-increasing pace? Perhaps. The menagerie of pandas, penguins, and hummingbirds certainly keep webmasters and content marketers on their toes.

There might be a third, harder to see reason: assisted search.

What is assisted search? In Google Analytics, there’s a concept called assisted conversions, things that impacted the final conversion but were not the last touch. A Tweet might not be the last thing that someone saw prior to converting into a lead, but it certainly might have helped.

Assisted search is a similar idea. Something else could have contributed to search without being the search query itself:

  • You might have driven by a billboard.
  • You might have heard about it on a podcast.
  • You might have seen a mention of a brand on a TV show.
  • You might have talked to a friend or colleague who told you to check something out.

Any of those things might have been the impetus for you to search, but no web analytics tool in existence will be able to detect it.

We all assume that SEO is once again super-important because organic search traffic is going up. What if it’s not SEO? What if it’s assisted search instead?

There’s only one way to know the answer to this question: ask people when they get to your website how they heard of you. Don’t wait for them to go buy something or fill out a form – ask up front:


This is a little 1-question custom survey I’ve got running on my site. I can take the results of this survey and compare it to my web analytics to see just how much of my organic search traffic can be attributed to assisted search. Here’s an example of the early results:


Obviously, the above is statistically invalid, laughably so, but it’s a start. I already see one out of three responses are word of mouth. One is referral, likely from the interview I did with Michael Stelzner. One is social media. Over time, more of this data will tell me just how much of my traffic is from assisted search.

Consider setting up this kind of survey (can be done with a popup or third party services like Google Consumer Surveys for Websites) on your own website so you can start measuring assisted search!

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