The U.S. Department of Justice has released several new trial exhibits – including internal Google presentations, documents and emails related to ranking.
Here are seven that specifically discuss elements of Google Search ranking:
- Life of a Click (user-interaction)
- Q4 Search All Hands: Ranking
- Ranking for Research
- Google is magical.
- Logging & Ranking
- Ranking Newsletter
- Bullet points for presentation to Sundar
1. Life of a Click (user-interaction)
This is a heavily redacted PowerPoint presentation put together by Google’s Eric Lehman – and like most of the other documents, it lacks the full context accompanying it.
However, what’s here is interesting for all SEOs.
In “The 3 Pillars of Ranking,” slide, Google highlights three areas:
- Body: What the document says about itself.
- Anchors: What the Web says about the document.
- User-interactions: What users say about the document.
Google added a note about user interactions:
- “we may use ‘clicks’ as a stand-in for ‘user-interactions’ in some places. User-interactions include clicks, attention on a result, swipes on carousels and entering a new query.
If this sounds familiar to you, it should. Mike Grehan has written and spoken extensively about this for 20 years – including his Search Engine Land article The origins of E-A-T: Page content, hyperlink analysis and usage data.
In this slide, titled “User interaction signals,” Google illustrates the relationships of queries, interactions and Search results, alongside results for the query [why is the ocean salty]. Specific interactions mentioned by Google:
- Mouse hovers
In September, Lehman testified during the antitrust trial that Google uses clicks in rankings. However, once again, it’s important to make clear that individual clicks alone are a noisy signal for ranking (more on that in Ranking for Research). Google has publicly said it uses click data for training, evaluation, controlled experiments and personalization.
What is redacted:
- A slide titled “Metrics” – all that is visible is one line: “Web Ranking Components.”
- Seven additional slides, including two titled “Outline” and “Summary.”
These seven slides were part of a larger Q4 2016 Search All Hands presentation, prepared by Lehman.
In this slide, Google says “We do not understand documents. We fake it.”
- “Today, our ability to understand documents directly is minimal.
- So we watch how people react to documents and memorize their responses.”
And the source of Google’s “magic” is revealed:
So how does this work?
In this slide, Google explains how “each searcher benefits from the responses of past users … and contributes responses that benefit future users”:
And in the final slide, Google sums up with this statement:
- “When fake understanding fails, we look stupid.”
The other four slides are entirely skippable, unless you’re interested in knowing that “Search is a great place to start understanding language. Success has implications far beyond Search.”
So when you see Google claiming links aren’t a top 3 ranking factor, now you can hopefully start to better understand why. That isn’t to say links are unimportant or that user data is the entire reason – machine learning and natural language processing are other huge pieces, more on that in Bullet points for presentation to Sundar.
Google is looking at end users – how people interact with Search results. Not as individuals – but as a collective.
3. Ranking for Research
It’s unclear who created this presentation, but there are some very interesting findings in here.
In this slide, Google talks about 18 aspects of search quality:
- Page quality
- Topical diversity
- Web ecosystem
- Mobile friendly
- Social fairness
- Porn demotion
- User control of spell correction
This slide discusses the shortcomings of live traffic evaluations. Yes, essentially Google is talking about clicks not being a good signal because they are hard to interpret.
- “The association between observed user behavior and search result quality is tenuous. We need lots of traffic to draw conclusions, and individual examples are difficult to interpret.”
Finally, this slide provides a different illustration of how Google Search result ranking works:
There are some other interesting tidbits in this presentation, though not necessarily tied to ranking. Of note:
- “Attempts to manipulate search results are continuous, sophisticated, and well-funded. Information about how search works should remain need-to-know.” (Slide 5)
- “Keep talk about how search works on a need-to-know basis. Everything we leak will be used against us by SEOs, patent trolls, competitors, etc.” (Slide 10)
- “Do not discuss the use of clicks in search, except on a need-to-know basis with people who understand not to talk about this topic externally. Google has a public position. It is debatable. But please don’t craft your own.” (Slide 11)
4. Google is magical.
In this presentation, we learn how search really works.
This slide explains how search does not work. From the notes:
In this slide, we learn how search does work:
Next, we learn the source of Google’s “magic.” From the notes:
So how does Google learn more from users? From the notes:
This slide looks at the 10 blue links.
This slide is on Image Search:
Finally, knowledge cards:
5. Logging & Ranking
This presentation discusses the “critical role that logging plays” in ranking and search.
This familiar-looking slide revisits the two-way dialogue being the source of Google’s magic. As explained in the notes:
In this slide, Google discusses translating user behaviors. From the slide notes:
Finally, this slide discusses how logging supports ranking and Search. From the notes:
6. Mobile vs. desktop ranking
This newsletter dove into the differences between desktop and mobile search ranking, user intents and user satisfaction – at a time when mobile traffic was starting to surpass desktop traffic on some days.
Google did a comparison of metrics, including:
- Manual refinement
- Queries per task
- Query length (in char)
- Query lengths (in word)
- Average Click Position
Based on the findings, one of the recommendations was:
- “Separate mobile ranking signals or evaluation reflecting different intents. Mobile queries often have different intents, and we may need to incorporate additional or supplementary signals reflecting these intents into our ranking framework. As discussed earlier, it is desirable that these signals handle local-level breakdowns properly.
7. Bullet points for presentation to Sundar
Nothing surprising in this document (it’s unclear who wrote it), but one interesting bullet on BERT and Search ranking:
- “Early experiments with BERT applied to several other areas in Search, including Web Ranking, suggest very significant improvements in understanding queries, documents and intents.”
- “While BERT is revolutionary, it is merely the beginning of a leap in Natural Language Understanding technologies.”