Google AI Mode appears to be showing more organic products for ecommerce queries. Previously, searching the same keyword in AI Mode returned fewer product suggestions, but in recent days, AI Mode has been showing more product carousels within its results.

Here is a video I took today.

Showing more organic products is a positive shift for site owners relying on organic visibility. This also ties into another recent test we covered, where Google was mixing sponsored and organic products together within AI Mode.

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Google is testing another new loading animation for sponsored results. We previously covered a different loading animation where Google showed logos while ads loaded, but today we spotted yet another variation. In this version, when a user searches for something, the sponsored results load using an animation similar to how AI Overview results load.

Here is a screenshot.

Have you seen this new loading animation for sponsored results in your own searches?

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Google Free Listings has made another change recently. We previously spotted the blue “More” label carousel, and today we’re seeing another update the free listing grid now shows a “Visit site” button alongside the price and website name. This looks new to us, with both the website name and the “Visit site” button being clickable. Below this, Google shows sponsored results, followed by all stores.

Here is a screenshot of how it looks.

Adding a “Visit site” button is a solid update, since it gives users a clear, direct action right within the product listing, which could help increase CTR for the websites featured there.

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Source:: searchenginewatch.com

Wikipedia is preparing an experiment with Google Preferred Sources as it deals with a steady decline in traffic coming from Google.

The idea is simple: when someone arrives at Wikipedia from Google on a mobile device, Wikipedia would show them a small notice asking them to add the site as a Preferred Source.

Then Wikipedia will see whether they come back more often.

The experiment has not started yet. Wikimedia’s Future Audiences team says it wants to run the test in late September or early October, initially for about two weeks.

There is a fairly obvious reason for the timing.

In the proposal, Wikimedia Foundation product lead Maryana Pinchuk said Wikipedia received about 138 million fewer clickthroughs from Google during the last week of August and first week of September compared with the same period last year.

That works out to a 17% year-over-year decline for that comparison period. Around 75% of Wikipedia reading sessions historically start with a search engine, and roughly 90% of those search sessions come from Google.

So Wikipedia is going to ask Google for help dealing with less Google traffic. Sort of.

Preferred Sources becomes a retention tool

Google Preferred Sources lets signed-in users tell Google which websites they want to see more often.

Google originally launched the feature around Top Stories, but has since expanded Preferred Sources into AI Overviews and AI Mode, where selected sites can receive a Preferred Source label.

Google says people are twice as likely to click through to a site after selecting it as a Preferred Source. In August, Google also released a button publishers can place directly on their own websites to make the process easier. More than 600,000 unique sources had been selected by users at that point.

Wikipedia wants to find out whether that translates into something more useful than a nice badge.

The proposed test would split logged-out mobile visitors arriving from Google into treatment and control groups. One group would see the Preferred Sources prompt. The other would see Wikipedia as usual.

Wikimedia plans to measure pageviews per user, click-through rate on the prompt and, more loosely, AI Overview impressions. Its Phabricator documentation describes the goal as testing whether the CTA increases pageviews generated by those users.

That makes this more interesting for publishers than another button Google would like them to install.

Wikipedia is effectively testing whether publishers can use the Google traffic they still receive to create a preference that helps generate more Google traffic later.

AI Overviews are part of the backdrop

Separately, Wikimedia’s September research newsletter highlighted a University of Washington preprint estimating that Google’s rollout of AI Overviews reduced external search referrals to English Wikipedia by roughly 4.8% to 5.5%, depending on the comparison group used.

That figure should not be confused with Wikipedia’s recent 17% year-over-year Google referral decline.

The study looks specifically at the estimated effect of AI Overviews using 2024 data and a statistical comparison between language editions. The 17% figure is a direct year-over-year comparison for a recent period and could reflect several changes in Google Search, user behavior and demand.

The preprint has also changed considerably during development. Earlier versions estimated a much larger effect before the researchers changed both their methodology and data source. It has not yet been peer reviewed.

Wikipedia’s experiment may give publishers something more immediately useful: an actual test of whether Preferred Sources can bring readers back.

If it works, expect that little “add us as a Preferred Source” button to become considerably harder to avoid.

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Reddit is valuable because people tell you what actually happened to them. Its AI search may be sanding some of that away.

A new study from researchers at the University of Illinois Urbana-Champaign audited Reddit’s AI search using 10,000 queries run three times, producing 30,000 answers that researchers traced against 14.68 million comments.

Search Engine Journal spotted the study first, and the headline finding is already interesting: comments that were highly rated, prominent in a thread and written more formally were disproportionately likely to make it into an AI-generated answer.

But the more interesting part is what happens to Reddit’s human voice once the AI starts summarizing it.

Reddit turns experience into advice

The researchers found that comments containing stronger markers of personal experience were less likely to be selected in the first place.

Then the AI flattened much of what remained.

First-person singular language, words such as “I” and “my”, accounted for 3.3% of tokens in the source comments. In Reddit’s generated answers, that fell to just 0.06%, a 98% reduction.

The researchers describe this as a two-stage effect: personal experiences are less likely to be selected, then the experiences that do survive are rewritten into a more generalized voice.

That distinction matters on Reddit.

“This happened to me” is not the same kind of evidence as “this is what you should do.” Yet an AI summary can make both sound like authoritative advice.

Popular Reddit comments get another popularity boost

Reddit’s existing ranking signals also appear to carry into the AI layer.

A one-standard-deviation increase in a comment’s score percentile within a thread was associated with 2.88 times the odds of being selected. Top-level comments were also nearly twice as likely to appear.

In other words, comments Reddit users have already pushed toward the top get another chance to dominate when Reddit’s AI builds its answer.

That does not prove Reddit’s AI deliberately rewards popularity. The study is observational, and the researchers explicitly warn against interpreting these relationships as causal.

Small communities can get drowned out too

The effect is not limited to individual comments.

Reddit AI frequently builds an answer from multiple communities. For queries originating in the smaller communities studied, roughly two-thirds of retrieved posts came from larger communities.

The researchers also found that already-visible questions were easier for the system to recover.

So a question asked in a niche community does not necessarily produce an AI answer dominated by that community’s expertise. Reddit may pull the discussion back toward larger parts of the platform instead.

There is one more warning buried deeper in the paper.

Researchers separately examined 2,000 claims generated by Reddit Answers using two verification methods. 8.7% were classified as unsupported by both. The two verifiers disagreed substantially, so the authors say the true rate cannot be established from this experiment, but they consider the overlap evidence that some generated claims cannot easily be traced back to the sources Reddit presents.

Reddit without the Reddit?

This is the awkward part for Reddit’s AI strategy.

Reddit originally pitched Reddit Answers around quickly finding the “human perspectives” buried across its communities. Yet this study suggests the AI layer can favor comments that already look authoritative, reach into larger communities for answers and turn first-person experiences into generalized advice.

None of that makes Reddit AI search useless.

But if you’re using Reddit precisely because you want messy, conflicting accounts from actual people, the AI summary may not be a neutral shortcut to the discussion.

Sometimes the mess is the useful bit.

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Source:: searchenginewatch.com