Tech
How we measure the quality of Google Search
![How we measure the quality of Google Search](https://images.seroundtable.com/elizabeth-tucker-at-google-1719502675.jpg)
Elizabeth Tucker, Director of Product Management for Google Search, appeared as a guest on Google's Search Off the Record podcast, where Google's Lizzi Sassman and John Mueller asked her questions about search quality, how Google measures it, and more.
Just to let you know, I interviewed Elizabeth Tucker on SMX.
I'll post my notes below, but here are some points that stood out to me:
When Google improves one type of search, it can destroy 50 others. Four-word searches used to be long, but now they're common. Data can be misleading, so it's important to understand that. The better Google gets at searching, the harder search queries become. If queries spike in the short term, something might be wrong with Google Search. If queries slow down in the long term, people might not be happy with Google Search. PageRank might be like the “A” (authority) in EEAT. There is no ranking signal that matches EEAT 1:1.
Below is an embed of the interview and my raw notes.
Raw notes:
Who is Elizabeth Tucker? What do Google's data scientists do? What do searchers do? Are they finding what they're looking for? You can vastly improve one search, but ruin 50 others. How do you know if you're improving?It's hard to find and fix parts of a search that aren't working What does it mean to be satisfied when you finish a search? Usually, you should see related content, but this used to be a challenge Google search is biased For example: Is Google showing too many different types of sites for your query Too many evergreen results Too many fresh results Too many results from organizations Too many results from blogs and small sites Too many results from social media Google wants to have a good mix of these User experience researchers and data scientists work together to improve Google search Where do complaints come from Sometimes they come from management Sometimes they come from the data scientist team Sometimes they come from engineers They come from all over the place How do we prioritize these questions? Scams and the like take priority What does Google do when bad things appear in our search results Some systems demote, like web spam and malicious download sites Most systems promote or find good things, like systems that try to match the topic of your query Google used to focus on keywords, but now Google can understand actual sentencesIn the past, a four-word search was considered long, but now it's not Kids search differently and it's interesting to watch kids search BERT was a linguistic breakthrough in search However, this is not a solved problem and will improve The better Google gets at this, the harder search queries become for Google If Google doesn't move, search will get worse Data can be misleading, so Google needs to be careful Before Elizabeth started, Google used very little data to test search quality, but now Google uses loads of data If search isn't working, people may search more in the short term but less in the long term, she gave some examples.Measuring search can be harder than improving search Google wants to ensure search results are understandable and controllable, and that's a challenge with machine learning and AI The Search Quality Rater Guidelines were one of the first projects she worked on at Google Her desk was right next to Sergey Brin and Larry Page (she barely saw them) Who are the search quality raters, how do they work, and how are they evaluated The origins of EAT (now EEAT) The original version didn't mention EAT specifically, but it was scattered throughout the document, so the raters got tired of writing out expertise, authority, and trustworthiness and wrote EAT Health-related queries absolutely need authoritative results, but other queries might not need to be EAT (e.g. “show me the cutest kitten”). EAT doesn't have a single ranking signal that matches it 1:1 PageRank is on the authoritative side, but not other letters
The full transcript is here.
Glenn Gabe also posted a summary about X, writing:
Great episode of SOTR with Elizabeth Tucker from Google. She covers a variety of search areas including UX research (qualitative and quantitative), the power of hearing from objective third-party users (who else would have said that, btw? :), prioritizing search issues (balancing frequency vs. severity), systems to DEMOTE, systems to PROMOTE, QRG, when EAT first started being used and how it evolved into EEAT. Also, a great episode and I highly recommend listening to it. 🙂
We’ve covered this before based on a PDF published by Google (screenshot below), and when talking about EEAT, Elizabeth explained that there is no ranking signal that is a one-to-one match with EEAT, but as an example of a character that *matches* a ranking signal, PageRank, one of Google’s traditional ranking signals, matches most closely with authority, but doesn’t necessarily match the other characters in EEAT.
One more note about this episode: We discussed what EEAT should be called, and I was surprised that Elizabeth didn't call it “Double EAT.” That's what she called it in the blog post announcing the addition of the second E, and that's what I've been calling it ever since. 🙂 Personally, I like “Double EAT,” and I think it's better than the other options.
I've covered this before, based on a previous PDF published by Google (screenshot below), but when talking about EEAT, Elizabeth explained that there is no ranking signal that matches EEAT one-to-one. However, as an example of a character that *matches* PageRank, which is a ranking signal, pic.twitter.com/4s7p7D4Q8V
— Glenn Gabe (@glenngabe) June 27, 2024
The photo above comes from an interview with Elizabeth when she was a data scientist at Google.
“Every time I chat with Elizabeth, I learn something,” John Mueller said on LinkedIn.
Forum discussion on X.
Sources 2/ https://www.seroundtable.com/how-google-search-quality-is-measured-elizabeth-tucker-37639.html The mention sources can contact us to remove/changing this article |
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