Latest / The SEO Podcast with Fexingo: Search Engine Optimization, Google Rankings, and Organic Traffic / How Google Uses User Engagement Signals for SEO in 2026
Transcript
- Lucas: So, Luna, there's a phrase that keeps buzzing around the SEO community: 'user engagement signals.' Everyone's got an opinion, but nobody really knows what Google does with them. Let's unpack that. Luna: Yeah, it's like the wild west—everyone's chasing clicks and dwell time, but is that actually a ranking factor or just a symptom? Lucas: Exactly. And the distinction matters because if you optimize for the wrong thing, you could be chasing your tail. Let's start with the basics: what do we even mean by engagement signals? We're talking about click-through rate, dwell time, pogo-sticking—that's when someone clicks your result and immediately bounces back—and even things like scroll depth and repeat visits. Luna: And all of that data is sitting in Google Analytics and Search Console, but does Google actually use it to rank pages? I've seen so many conflicting studies. Lucas: Right. Some SEOs swear by it, others say it's correlation, not causation. But here's the thing: Google has repeatedly said they don't use engagement metrics as a ranking factor. But they also say they don't use domain authority, and we all know that's not the whole story. Luna: So what changed in 2026? Is there something new? Lucas: Well, the March 2026 core update seemed to favor sites with strong engagement—higher dwell times, lower bounce rates—at least based on the chatter from site owners. But correlation isn't proof. Still, Google's patents and job listings hint they're looking at user interaction data more than ever. Luna: So what's the actual evidence? I mean, there's that famous study from back in the day about long clicks and short clicks—how Google might treat them differently. Isn't that from a patent? Lucas: Yeah, the 'long-click' patent from around 2010. It described using the time a user spends on a result before returning to the SERP as a quality signal. But patents aren't necessarily implemented. Still, it shows they've been thinking about it for over a decade. Luna: And then there's the browser data angle. Google Chrome is the world's most popular browser—they have access to an insane amount of behavioral data. Even if they don't use it directly for ranking, they could use it to train AI models that assess content quality. Lucas: That's a really good point. In fact, I've seen speculation that Google's quality raters' guidelines are being supplemented by machine learning models that learn from engagement patterns. So even if the signal isn't a direct ranking factor, it might influence the algorithms behind the scenes. Luna: So how does that affect the average SEO? If I'm optimizing a blog post, should I be obsessing over dwell time? Lucas: Not obsessing, but you should be aware. The danger is over-optimizing for a metric like dwell time by adding fluff or slowing down the page to keep people reading. That's gaming the system, and Google is pretty good at sniffing that out. Luna: Yeah, and we've seen that with Core Web Vitals—they moved from speed to user experience because people were cheating the metrics. Lucas: Exactly. So the smart approach is to focus on the intent behind the query and deliver content that genuinely satisfies it. If you do that, engagement tends to follow naturally. And that's probably why Google rewards it—it's a proxy for relevance. Luna: But there's a flip side. What about queries where users bounce because they found the answer quickly? Like a definition or a quick fact. That's not a sign of bad content. Lucas: Right, and that's the nuance. Google can't just say 'low dwell time = bad' because for some queries, a quick answer is perfect. That's why they use context—they compare engagement patterns across similar queries to identify outliers. Luna: So it's not a simple threshold. It's relative. Lucas: Precisely. And that's where the machine learning comes in. They can create a model for each query type—informational, transactional, navigational—and see if a page performs better or worse than expected. That's a much more sophisticated approach than a blanket 'dwell time' rule. Luna: So what can we actually do with this? I mean, we can't see Google's data directly. Lucas: We can approximate. In Search Console, you can look at average position, CTR, and impressions. But you can't see dwell time or pogo-sticking there. You'd need to use analytics to track those on your own site, and even then, you're only seeing a fraction of the picture. Luna: But you can use it to spot patterns. Like, if a page has a high bounce rate but also high conversions, maybe it's actually satisfying users quickly. Or if a page has a low CTR but high dwell time, maybe the title isn't compelling, but the content is good. Lucas: Exactly. And that's the kind of analysis that can inform your optimization strategy. You're not trying to game a metric; you're trying to understand user behavior and align your content with it. Luna: Speaking of understanding user behavior, have you seen that new AI tool that predicts engagement based on content structure? It's getting a lot of buzz, but I'm skeptical. Lucas: I have, and yeah, skepticism is warranted. It's basically a predictive model trained on engagement data, but the training set is limited and biased. It might be useful as a heuristic, but I wouldn't base your whole strategy on it. Luna: So, let's talk about the elephant in the room: Google has been saying for years that they don't use engagement signals as a ranking factor. But with the March update, it really felt like some sites got a boost or a hit based on engagement. Is that just confirmation bias? Lucas: It could be. We tend to notice the cases that fit our narrative. But there are also studies that show a correlation between engagement and rankings. The problem is correlation isn't causation. Maybe high engagement is just a byproduct of high-quality content that Google can already identify through other signals. Luna: So you're saying engagement might be a red herring? Lucas: Not entirely. I think it's more accurate to say that engagement is a signal, but not necessarily a direct ranking factor. It's like a symptom of underlying quality. Google might use it to refine their algorithms, but it's not a simple 'if dwell time > X, rank higher' switch. Luna: That reminds me of something I read about the Quality Rater Guidelines—they talk about 'satisfies the query' or 'fails to satisfy.' Engagement data could be a way to validate those human ratings at scale. Lucas: Absolutely. And that's probably the most likely scenario. Google uses engagement data to train and validate their machine learning models, which in turn influence rankings. So it's indirect, but it's still influential. Luna: So what's the takeaway for our listeners? Should they be monitoring their engagement metrics? Lucas: Definitely. But not in a panic. You should be tracking clicks, dwell time, pogo-sticking—at least on your own analytics. Look for pages that are underperforming and see if there's a pattern. Maybe the title is misleading, or the content doesn't match the search intent. Use that to improve the user experience. Luna: And remember that engagement isn't just about time on page. It's about whether the user found what they were looking for. Sometimes a quick answer is the best answer. Lucas: Right. So focus on clarity, relevance, and satisfying the query. And if you do that, you're likely to see engagement improve, and that can only help you in the long run, whether or not it's a direct ranking factor. Luna: And it's worth mentioning that we're still in the early days of ai assisted search. With Google's SGE and other AI features, user behavior might shift dramatically. We might see new engagement signals emerge, like how users interact with ai generated summaries. Lucas: That's a great point. The way people interact with search results is changing, and Google is adapting. They're already using things like 'query refinement' and 'browsing depth'—we covered that in a previous episode. Engagement signals are just another piece of that puzzle. Luna: So, to wrap up, the key is to not get obsessed with a single metric. Instead, think about the holistic user experience. If you're creating content that genuinely helps people, you're probably on the right track. Lucas: And that's the most seo proof approach you can take. Google will keep tweaking their algorithms, but if you're focused on the user, you'll weather the changes. Thanks for listening, everyone—we'll catch you next time.