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Digital Sleuthing: How to Find and Decipher Google’s Patents, Leaks, and PR

Francine Monahan — Thu, 29 Jan 2026 12:00:00 +0000

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When a multi-billion-dollar corporation sits at the center of the entire SEO industry, it can be tough to believe everything they say. Constant press releases with talking heads giving vague quotes can throw the industry into a tailspin in an instant, but this doesn’t always have to be the case.

There’s truth in them there hills. You just have to know how to find it.

From patents and leaks to official PR, there’s a lot to filter through, but there are many ways to parse through the information Google releases. This blog will show you how to decipher the real meaning and separate fact from vague corporate untruths.

Understanding Google Patents

For years, well-known SEO researcher Bill Slawski was at the forefront of analyzing Google patents. Since his passing in 2022, the torch hasn’t so much been passed but rather divided between a number of SEOs trying to pick up the slack.

Patent watcher and leak analyzer Mike King still touts Bill’s work and recommends that anyone new to patents should read his work at SEO by the Sea and familiarize themselves with it. That way, you’ll start to understand and recognize the terminology Google uses.

“The difficulty is they’re always going to be dense writing,” Mike said of the patents. “They’re not written to be readable.”

Patents are written that way intentionally, with vague phrasing and broad descriptions to cover all of Google’s bases legally.

Mike started looking into patents years ago after hearing many engineers and Googlers using terminology that he didn’t understand at first. Then he searched through patents for those same words to learn what everyone was talking about.

Most recently, Mike did a deep dive into the AI Mode patents and how it all works.

In the SEO world, experts make discoveries and share them at conferences. Mike says that Google does the same thing with its research by sharing papers and information at conferences for engineers.

“All of these people are sharing their ideas with each other and building upon them,” Mike said.

Now that we know what to expect, let’s look into where to find patents and how to read them.

Where to Search for Patents

There are a few main locations where you can easily find patent applications and their statuses:

Google Patents: The most user-friendly interface. This is your primary hub that indexes global filings and offers the most intuitive search interface.
Google Research: Where you can find official product and research releases directly from Google.
USPTO & Espacenet: These are official government databases with the most up-to-date legal statuses.
arXiv.org e-Print archive: A directory for white papers.

Be sure to filter your search with certain key phrases. If you’re using a site that’s not Google’s official patent directory, add the search operator assignee “Google LLC” to narrow it down, for example.

You can also use CPC (Cooperative Patent Classification) codes like G06F 16/00 (Information Retrieval) to find patents grouped by technology rather than just keywords.

“I don’t browse randomly,” said Metehan Yeşilyurt of AEO Vision. “I usually start from an observed behavior in search and work backwards. My main tools are Google Scholar (citation chains matter more than single patents), arXiv to understand the research roots, and advanced Google searches like “filetype:pdf” combined with ranking or retrieval terms. I’m looking for patterns, not one document. I’m also using consensus.app, recently.”

SEO expert and consultant Marie Haynes said she doesn’t really have a solid process for finding interesting papers and patents – she just keeps her ear to the ground.

“I have an RSS reader that I vibe coded that finds me the latest Google blog posts and more,” she said. “I pay close attention to this page: https://research.google/pubs/.”

She also scours X (formerly Twitter) for interesting papers that people are talking about.

“Most of what I find simply comes from me doing research as interesting scenarios come up,” she added.

How to Read a Patent

You don’t need a law degree to be able to read a patent, but you might need a few tips to read them efficiently.

First, don’t read from top to bottom. Focus on this order instead:

The Abstract: Read this first. It’s a 150-word summary of the problem and the solution. If the Abstract mentions “improving resource relevance based on user context,” you’re likely looking at a ranking signal.
The Claims: Found at the very end. The claims define exactly what Google owns. If a specific ranking factor isn’t in the claims, they don’t legally own that specific method.
The Drawings & Flowcharts: Look for Fig. 1 or Fig. 2. Google engineers use these flowcharts to show how data moves from a user’s query to the final result.

Keep in mind that terms like “entity” or “resource” are used as catchalls for a person, place, or a brand to keep the patent’s scope broad. Remember, Google purposely keeps their patents from being too specific.

“I mentally strip legal padding and reduce everything to inputs, transformations, scoring, and constraints,” Metehan said. “Constraints (latency, decay, thresholds, fallbacks) usually matter more than features.”

A patent does not always equal a finished product either. Google patents thousands of ideas that never see the light of day as an actual product. In fact, Google frequently files “defensive patents,” which are ideas they may never use, to prevent competitors or what they refer to as “patent trolls” from using them.

We know that the language isn’t simple for everyone to understand because it’s written through the lens of information retrieval and not SEO (which is why Mike says they’re able to get away with obfuscating information), but we now have tools to help us make sense of these patents. You can upload the PDF of the patent to NotebookLM and ask it questions or generate a podcast explaining it.

Gemini has obviously indexed all of Google’s research so you can ask it questions, too. If the information hasn’t been made public yet, you can at least give it whatever information you have and it can analyze what it all might mean based on the facts.

“It’s all a lot more accessible now than it’s ever been,” Mike said.

Sometimes, Google will publish updates or expansions, so make sure you’re looking at the right date. A patent usually lists three:

Priority Date: The most important date. This is when Google first claimed the idea. It tells you exactly when they were thinking about this technology.
Filing Date: When the formal paperwork was submitted (often months or years after the Priority Date).
Publication Date: When the patent became public.

If you see a patent published in 2026, but the Priority Date is 2021, you aren’t looking at a new invention but something Google has likely already been testing for five years.

The amount of patents Google applied for has dropped 13% since last year, though, which is interesting to see. The company was granted 1,782 patents in 2025, down from 2,054 in 2024.

Aufgesang’s Head of SEO and AI Search Olaf Kopp monitors new patent publications from Google, Microsoft, and OpenAI every week and manually filters out those that could be interesting.

“My analyses focus primarily on general information such as status, countries/regions where the patents were published, claims, and detailed descriptions,” he said. “Patents that have been published for multiple regions are more exciting, as it is more likely that the methods will also be used in practice.”

Navigating Google Leaks

In May 2024, over 14,000 internal ranking features from Google’s Content Warehouse API were released by an automated bot. Mike King was one of the first to see these leaked documents after Rand Fishkin shared them with him (after Erfan Azimi shared them with Rand).

Finding these leaks is only half the battle, though. The real skill is knowing how to read them without jumping to false conclusions.

How to Verify a Leak

To ensure what you’re hearing about Google is true, you could cross-reference with official sources such as court testimony, like how the DOJ vs. Google trial confirmed the existence of Navboost and Glue before the leak even happened.

You could also look for deprecation markers. Some leaked features are marked as “deprecated,” meaning Google used to use them but doesn’t anymore, which is crucial to avoid chasing ranking factors.

“Leaks are partial snapshots, not documentation,” Metehan said. “I map internal terms, look at defaults, check pipeline order, and cross-validate against real-world behavior and older patents. I never treat leaks as a checklist.”

Metehan also warns against optimizing purely for patents or leaks.

“I look for invariant behaviors that survive multiple re-rankers, versions, and query types and test those,” he said. “I’m using Gemini APIs a lot, models, embeddings, layout parser, model garden and Vertex AI with grounding, etc. It’s a multimodal world.”

Google has been sharing pretty much everything research-wise these days, so it’s up to us to find what’s important. Because when it comes to Google’s official information releases, that’s a different story.

“Google has been far more forthcoming about how things work on the research side than they have on the PR side to the SEO community,” Mike said.

Reading Between the Lines of Google PR

Official communications from Google (via their blogs, social media, or spokespeople) typically serve a specific purpose: to encourage behavior that makes their search engine better while discouraging “gaming the system.”

To find the truth, you have to decode the Google-Speak.

Google often uses a linguistic technique where they deny a specific term but not the concept to make it “technically truthful.”

For example, multiple Googlers like John Mueller and Gary Illyes have said that Google does not use a Domain Authority score. But the 2024 API leak revealed a metric called siteAuthority.

Google was “truthful” because “Domain Authority” is a trademarked term by the SEO company Moz. They don’t use that specific tool, but they certainly use their own internal version of the same concept.

And most recently, Danny Sullivan declared that no one should be “chunking” their content – a statement that didn’t really make much sense because it’s been an SEO and UX best practice for years to break up walls of text into easy-to-read sections.

But again, Google doesn’t use the specific word “chunking” when making content recommendations so, sure, I guess they’re technically being truthful. It still seemed like a silly statement to make, though, and got a lot of people up in arms.

These are the times when it’s important to think hard about why they’re saying these things and how it all would benefit Google financially, because that’s Google’s main concern.

When reading a release about Google, ask yourself these questions:

Is the denial hyper-specific? If they say “We don’t use [Metric X] for [Task Y],” they might still use it for Task Z.
Does it contradict sworn testimony? Always prioritize information from the DOJ vs. Google trial over a tweet. In court, off-the-record chats are evidence while on X (Twitter) or Reddit, they are PR.
Are they saying to do as they say and not as they do? Google PR often tries to scare people away from manipulation and those evil Black Hat SEO methods like buying links, even when their own systems like PageRank still rely on them.

Always keep your reporter hat on when listening to Google, even if you never actually spent three days driving around town trying to get a comment from an avoidant local politician for $12 an hour like some of us did.

Now, where can we find official information about Google?

Reliable Primary Sources for Official News

To analyze the spin yourself, go directly to the source:

The Search Central Blog: For official algorithm naming and policy changes.
The “Search Off the Record” Podcast: Where engineers often let slip technical nuances that don’t make it into the formal blog posts.
Sworn Court Exhibits: The Justice.gov Antitrust Exhibits are a big source of truth considering that lying there has legal consequences.

“It’s a combination of research and evidence,” Mike said. “You also have to be mindful that when Google is speaking to the community, they’re speaking to the average person, not the experts. They’re creating something that answers the question for most people.”

Mike emphasized that there are three different things to look at to figure out the actual truth: your research, what’s in the wild, and what Google is saying.

Googling the Truth

Overall, just remember that Google is a massive corporation that is not here to help SEOs be more successful and get more clients. Google is here to continue to be massive and rich. Everything they say should be viewed through that lens, no matter how much their statements happen to align with a point you’re trying to make at that moment.

Also, none of these sources are the whole truth on their own. Look at multiple sources, official documents, legal documents, and general research to come to a conclusion.

“Patents don’t tell you what to do,” Metehan said. “They tell you what Google struggles with and cares about. That’s where the real insight is. Think from a reverse and relevance engineering perspective.”

As we move further into 2026, where still-pretty-inaccurate AI Search has become the norm, these detective skills will be more valuable than ever. Google may obfuscate the truth to protect its bottom line, but the paper trail left by their engineers and leaks will always provide a roadmap for those willing to look.

Don’t just wait for the next Helpful Content update to tell you what to do. Go beyond the headlines and find the real story yourself.

Need help becoming more visible online?

Read about Relevance Engineering

The post Digital Sleuthing: How to Find and Decipher Google’s Patents, Leaks, and PR appeared first on iPullRank.

Local Visibility in AI Search: Findings from 6.9M Citations

Francine Monahan — Tue, 16 Dec 2025 12:00:00 +0000

“The funnel as we know it is moving,” says Christian Ward, Executive VP and Chief Data Officer at Yext. Thanks to AI, it’s moving off your website and into a chatbox (or in various forum discussions online), and marketers in the local business space need to pay attention.

It’s vital to ensure that the right people find your business wherever they’re searching without having to filter through too many irrelevant results. Like with Relevance Engineering, your brand strategy must be omnimedia and span social media, YouTube, Reddit, and other places.

Although some studies point out that Google is still the top source for search right now, there’s a lot more nuance to that.

“That’s like measuring a baseball player by the number of swings at bat,” Christian said. “That’s not how you measure search. Search has to be around the time you spend on a platform because that’s where the money is made, and it’s got to be measured on outcomes.”

And while AI outcomes aren’t that great yet, they are slowly getting better.

Yext performed a citation study on 6.9M citations, asking 1.6M questions across three models (ChatGPT, Gemini, and Perplexity) to find the impacts of AI Search on local visibility. This article will go through the data and findings.

The Impact of Search Fragmentation

Search is fragmenting. People are starting their searches on LLMs, Reddit, TikTok, and other places, and often moving to Google later on in the process to fact-check or make a final purchase. AI Search is decentralizing the search process.

Christian created the below chart two years ago. It’s evolved, yet still highlights how people use a wide range of platforms to search, but Google still dominates the market and sits in the middle (especially for fact checking).

Even if TikTok is your first stop for research, eventually the platform will add an LLM of its own. And while users are starting exploration in AI but going to Google to execute, that won’t last so we need to be prepared.

“That’s gonna stop really soon as AI models add more executions,” Christian said.

The Growth of AI

In just 2 years, ChatGPT acquired as many users as the entire internet did in 13 years.

Unlike with old-school dial-up internet, when no one in the house could use the phone while you were online, there’s no cognitive burden to AI. You can just use it easily.

And with the creation of AI Mode and constant improvements to Gemini with each release, Google will clearly be focusing its attention on AI.

“I don’t see Google just continuing to do search,” said Christian.

As search continues to fragment and more partnerships pop up with AI companies, we’ll see changes in how we measure success. Direct purchases within LLMs will impact traffic and clicks.

Walmart’s deal with ChatGPT for in-app purchases contributes 20% of Walmart’s referral traffic. This partnership with OpenAI means that Walmart can’t capture all the metrics that it used to, but at this point, they don’t even care. They just want the customer to check out, regardless of whether it’s on Walmart’s site or in ChatGPT.

In fact, traffic to many sites is down, but many businesses are still getting relevant clicks because visitors to their sites likely did extensive research before arriving.

“If they play their cards right in how they are cited and the knowledge they provide, I think they’re going to have phenomenal business outcomes,” Christian said.

However, this brings up another question. Should sites develop two types of content: one for machines and one for people? Or is a combination of the two the way to go?

“There are so many strategic applications for that for business,” said Garrett Sussman, Director of Marketing at iPullRank.

There’s a lot of data we still need to see to truly understand all of AI’s impacts on search fragmentation, but that probably won’t happen, and Christian says we need to just get used to that. There will be discomfort around monitoring, strategy, and search behavior as AI Search becomes a more integrated part of the way we search. We’re not going to get all of the data that helps us determine resource allocation and return on investment.

But some changes will have a more positive impact, like improvements to memory and personalization in LLMs. Memory will be the step that solidifies where and how we search.

The Evolution of Memory

Memory and personalization will be a huge part of the future development of AI systems, according to Sam Altman of OpenAI who has said that ChatGPT-6 will be all about improving its memory.

The main issue for Google and OpenAI is that with more memory in search, there is an impact on ads and a company’s ability to show you valuable ads at the right stage in the search journey. Memory context and location will have a huge impact on how different the search results are for everyone.

“The reality is, if I can’t have the right to show you steak restaurants because you’re a vegan, that’s a problem for the available ad space,” Christian said.

Memory in AI shrinks the ad reach because there’s only a limited number of products or services that make sense. You can’t deliver broad ads because people will stop asking broad questions. At the same time, it increases the value of the ad itself because you’re further down the funnel to your target.

“It’s a better user experience for us,” Garrett added.

But how does this play out next year?

Every so often throughout the evolution of computer technology, we’ve seen inventions jump from compute to memory improvements, and OpenAI is heading toward a memory jump.

If ChatGPT can master memory, it will have a huge advantage in the market.

“If it starts getting to that level, I think you will see a very big upswing in the value proposition to the consumer,” Christian said.

The Impact of Experience Fragmentation

An AI company’s greatest risk is users not trusting them because they can switch to another LLM so easily. If you ask one of the AI models a question, and it answers it wrong, you will probably go use another model. Google’s built up brand trust over decades. They have more at stake to get it right. AI introduces a complex risk to that trust due to the probabilistic nature of generative output.

For users, there is no cognitive burden when using LLMs for search. You don’t have to learn a whole new system because they’re all pretty much the same and very easy to operate.

There’s not going to be a one-size-fits-all solution to this, but accurate citations will have an impact. And how you format your content will control your chances of being cited.

“I think AI has a trust problem,” Christian said. “If trust is the currency by which AI will be judged and scored, then citations are the receipts.”

Citations. That’s why Christian is obsessed with where they fit in the puzzle. They are critical to the LLM-to-internet ecosystem.

Citations are dependent upon: the [QUESTION], the [CONTEXT], the [LOCATION], and the [MODEL].

The above example of a query shows the various ways people can find your business due to how your company is talked about online.

Subjective qualifiers like “best” typically come from review sites.
Categories like “Indian restaurant” come from listings and directories.
Locations like “Soho” come from maps and local pages.
Objective facts like “late night dining” or “patio seating” come from websites and pages.

“Every element on this page has a different level of potential verification by a probabilistic large language model,” Christian said.

If a fact is shown only on your site and nowhere else, that makes it seem less trustworthy in the eyes of AI. But if it also appears in reviews or on other sites, the higher the probability that your business will show up in an answer.

AI typically utilizes location, context, and memory during a search. Currently, we analyze AI visibility from the brand level down, which is not typically how a consumer uses search or AI.

Christian posits that AI Search results heavily depend on location. Every search is impacted by location in some way.

A Starbucks in the suburbs of Georgia will see different business than one located in midtown Manhattan. If you own a burger restaurant in a small town, your competition likely isn’t tons of other burger joints but rather the two or three other restaurants in town.

Mentions also have an impact here. Along with structured data, these are important to the customer journey. Common page structures, such as neighborhood, region, state, city, or any geography, need a dedicated page on your site.

Christian emphasized that we need to stop thinking globally about brand and focus instead on the consumer’s perspective regarding what’s showing up and being cited. If you’re a plumber, odds are that you want more leads for bathroom remodels than 2 a.m. calls for a clogged toilet, so your content needs to reflect that in order to be properly cited.

There are some factors you can control and that is where you should focus your marketing efforts.

What Can You Control?

Understanding that local AI Searches are probabilistic, but location has an overwhelming impact, the sphere of influence is physically reduced significantly. But of those potential citations, what can you actually influence?

A number of citation source control categories can impact visibility:

Websites
Listings
Reviews and social
News and forums

You can’t really control what people say in reviews or on social media and forums such as Reddit, so Christian says you shouldn’t spend all your time worrying about those. In fact, he describes the current environment as “an existential threat” for review sites. You can see reviews of products anywhere now, from TikTok and Instagram to Reddit, so there’s no need for people to go to specific review sites anymore.

You can control what’s depicted on websites, third-party directories, and local websites.

Local websites with subdomains are a large percentage of what’s cited because AI doesn’t have to compute all the folder structures. There’s just a concise and specific page from which to gather information.

And although Google doesn’t specifically cite Google Business Profiles, that doesn’t mean it’s not a source of data; they simply don’t cite it. You should still make sure your profile is updated and accurate.

According to Yext’s data, OpenAI, Perplexity, and Gemini are not far apart when it comes to the percentage of total citations for each citation category. And for the most controllable sources, websites and listings, citations show up very often in those models. This means there is a lot of opportunity for local businesses to control how they’re cited and found by prospective customers.

Local Search Takeaways

Location is everything. The data from Yext shows that websites are leading the citation race and that lead is expanding. Online profiles and directories also serve as crucial verification points for AI models, reinforcing what you’re saying about your business across the web.

Interestingly, Yext has seen social and review citations decline from where they were just three months ago. This shift means the controllable sources (your website, listings, and structured data) matter even more than they did before. The power is back in your hands to shape how AI models understand and cite your business.

It’s all about omnimedia strategy these days. The LLMs will pick up information about your brand from all different sources such as YouTube comments, Reddit forums, TikTok reviews, etc. You need Relevance Engineering to make sure your brand is showing up in a positive way everywhere people search.

While many sites are scrambling to block crawlers because they’re worried about giving away their content, that’s the wrong move. If you block AI from accessing your information, you’re essentially removing yourself from the conversation happening in these models and opting out of future search visibility. Your local business needs to make it easy for AI to find, understand, and cite it accurately, or you’ll be left behind.

Want to learn more about omnimedia strategy?

Read about Relevance Engineering

The post Local Visibility in AI Search: Findings from 6.9M Citations appeared first on iPullRank.

AI Mode Impacts on Local Search: Researching Local Health Clinics

Francine Monahan — Fri, 03 Oct 2025 11:28:37 +0000

“This is kind of an AI Mode fail.”

That’s what an Oregon man said after trying to search for Kaiser urgent care clinics near him. Some of the results were not close to his home at all:

He then followed up with his zip code to make it more specific to his location, but one of the results provided was a medical office and not a clinic:

Further down the page, another result popped up that wasn’t a Kaiser facility either.

“That shouldn’t have come up,” he said.

Overall, the experience caused frustration for the man.

The majority of people in this study were looking for a quick answer in an easy-to-read list, preferably in order by distance so they could instantly decide where to go and with additional details so they didn’t have to click on a website. They wanted to see a map with a list of urgent care clinics close to their home, so they would often skip over the sponsored links and scroll directly to the “Places” area of the SERP.

But there were quite a few features people hoped to see in AI Mode (like hours of operation or an option to schedule an appointment), and were left disappointed.

However, AI Mode did succeed when it came to very specific searches, like finding a clinic that offered a particular service.

Reactions to AI Mode varied in our study, performed by Farrah Bostic of The Difference Engine, to learn the search habits of average people. She surveyed 100 participants, spoke one-on-one with 23 users, and watched them perform searches in real time.

Participants ranged in age from 18 to 75 with a balanced mix of ethnic backgrounds, genders, education levels, and locations across the country.

Each user performed five different queries:

Find out which credit cards offer the best loyalty programs.
Find out which kinds of breakfast cereals are healthiest for children.
Find out the top news or sports headlines in your local area.
Find a health clinic in your area.
Find a pair of shoes to wear indoors for under $75.

Watch the webinar replay:

Today, we’re looking deeper into the fourth search task where we asked participants to perform: finding a health clinic in their area. Will AI Mode have an impact on local search? If it becomes the default in the future, how will users be able to get what they need from it? Let’s take a look.

Overall Data from the AI Mode Study

Task #4 of our AI Mode study showed us some interesting info:

29% were shown AI Mode as an option
2% of those who were shown AI mode used AI Mode
3% engaged with AI Overviews and <1% unfurled them
Average number of links clicked: 1.09
Average time to complete the task: 56 seconds
Average score for ease: 4.49 out of 5
Average score for satisfaction: 4.19 out of 5

Here are some stats regarding search terms the participants used:

Search terms emphasized locality, so users tended to use words and phrases like “local” or “near me”, as well as using zip codes and city names to narrow the search.
Some chose to distinguish between different types of health clinics, including “health clinic”, “urgent care”, “general practitioner”, “health care providers”, “primary care”.
Some had specific use cases in mind, using terms like “Find nearest ENT doctor’s office”, or “women’s health clinic near me”.
And some had specific brands of health clinics in mind like City MD, Care Now, or Minute Clinic.

Overall, users wanted maps with locations, hours, reviews, and ways to book appointments. However, AI Mode results lacked specificity and buried the maps farther down the page (if they included them at all), so trust remained higher in Google Maps and direct clinic websites.

Some saw value in refining queries with additional questions, mostly on mobile with voice.

In general, most skipped AI Mode altogether, finding it unhelpful for local searches.

AI Mode User Search Patterns

“Since I’m searching for something specific and local, I would probably do a regular Google search.”

That’s how a 33-year-old from Idaho would search for an urgent care clinic in his area. He didn’t consider using AI Mode for this particular query.

When it comes to finding something local, he wanted to see a map and ratings right away at the top of the page:

AI Mode lacked those features, as it just sent him a list of locations, some of which weren’t that close to him, and many were the same as the Google search results.

“It looks like it’s giving me some relevant results, but at the same time, I’m seeing the same information,” he said.

AI Mode often provides more information than a person is looking for, with detailed summaries and sections featuring additional information and tips. This can be helpful in some cases, but when performing a local search, that’s not always needed.

“For me, I’m looking for a list,” said a 43-year-old woman from Fresno, CA. “I’m not looking for ‘the best’ healthcare clinic near me.”

Another user prioritized reviews. Aside from location, those were a top concern for her. When she tried AI Mode, she was disappointed that there were none in the summary:

A 41-year-old participant from the Bay Area in California also valued ratings above all else and began his search in Yelp.

“I use Yelp a lot for more than just restaurants,” he said.

One study participant from Minnesota added “in Minneapolis metro” to his search terms to narrow it down:

After trying it in AI Mode, he realized that he should have specified that he lives in northern Minneapolis because some of the options were a little far for him. But after comparing the AI Mode results to the traditional Google SERP, he found they were very similar aside from the order in which they presented the results and the location of the map (which is at the bottom in AI Mode).

When another participant searched for a walk-in clinic, there were no maps in the results, and he was one of the only participants to receive an AI Overview, which he liked:

When he tried AI Mode, he liked the map, even though it was located at the bottom of the result:

“That’s definitely helpful,” he said.

For a 74-year-old in Orlando, it didn’t occur to him to use AI Mode for this type of query, but he wasn’t too pleased with his traditional Google search result. There was no map when he searched with his zip code, and he didn’t like the options provided.

“Some of these I don’t recognize,” he said.

After trying AI Mode, he liked how the results were formatted in a concise list.

“This would’ve been a better way to do the search, to see it laid out like this,” he said.

Another study participant also used his zip code in his very specific prompt asking if any clinics accepted his particular insurance.

This is showing us that the more specific the query, the less likely you are to get Places and a map in the Google results. He even received an AI Overview:

AI Mode gave a similar list of results. But when he refined his search to confirm his copay, he was essentially told to check with his insurance. It’s also interesting to note that AI Mode still answered even though he spelled copay wrong.

More Specific Results from Conversational Search

AI shifting search to a more conversational format gives searchers the ability to refine their queries and go deep into specifics.

A 50-year-old North Carolina woman thought it would be helpful if AI Mode could tell you what each clinic specializes in so she could avoid wasting time.

“I’ll go sit in the lobby waiting to be seen and they don’t even do what I need help for,” she said. So, she performed a specific search regarding x-rays that she found helpful (and her preferred way to do that is through voice prompting, hence the addition of “oh”):

A 35-year-old man in Long Island also specified the service he needed in his prompt when using AI Mode, which is another example of conversational search providing more specific answers.

“For specific ones, I would definitely ask AI,” he said, like searching for help with back pain:

A woman from Boston said she would like to see a lot more information like wait time comparisons, or a comparison of services like blood work, scans, or things that are not offered everywhere.

“I might go a little bit deeper,” she said.

One 31-year-old user found her traditional Google search results for a CVS MinuteClinic “a little overwhelming” but liked the bar at the top that provided an “open now” filtering option:

She broadened her search to just “walk-in health clinics” and that seemed to help. AI Mode impressed her with how responsive it is to how she enters prompts, but she worried that could cause issues.

“I feel like that’s a pro and a con,” she said. “You have to be specific about what you’re putting in because the AI Mode will reflect EXACTLY what you put in.”

She entered a follow-up prompt asking about closing times, further proving that people want to see hours and other pertinent information directly in the results. AI Mode provided today’s date so she knew it was accurate, and even included hospitals and emergency rooms, which she actually found helpful (even though others didn’t like that):

A 35-year-old from Florida said his first stop was his insurance plan’s website to see which clinics were covered.

Because this topic is considered “more serious,” another participant said he didn’t necessarily trust Google for this.

“Something like this I’d probably want to get more of a recommendation from somebody first,” he said. Then he’d check to see if his insurance covered the facility. So when he did a Google search, he wasn’t impressed.

“This is not really doing much for me,” he said.

However, when he used AI Mode, he specified that he wanted clinics that were open on the weekend and liked the information provided. Conversational search gives users the opportunity for a more specific search result:

Negative Reactions to AI Mode

The main complaints from survey participants were that the results AI Mode provided weren’t close enough to their homes, and some of the results were hospitals and doctors’ offices rather than clinics.

One 42-year-old user from Virginia didn’t like the response she received from AI Mode.

“I’ve lived here for about 15 years,” she said. “It just pulled up ones that I have never heard of.”

Many of the options were actual doctors’ offices as well. She said that out of all the options given, she would only consider the one at the bottom of the list.

A 52-year-old Nevada man said he only has two clinics in his small town so he didn’t feel the need to use AI Mode, but tried it anyway when prompted.

However, the clinics were not listed in order of distance, which he didn’t like. He also thought some of them were not close enough for him to consider “near him.”

“Those are another 15 miles away,” he said.

Another participant said he “wouldn’t go to AI Mode for this” because Google gave him everything he needed, including an option to schedule an appointment:

A 54-year-old from Philadelphia didn’t use AI Mode either. Instead, she went straight to Google Maps to find a clinic (a technique that I frequently use):

A 29-year-old from Virginia thought the AI Mode responses were not timely or up to date.

“The thing with AI Mode that I see a lot is that it’s not necessarily as time relevant as I want it to be. It always feels like there’s some sort of delay,” he said.

He also agreed with many other study participants that things like phone number, address, hours, and reviews were all important and should be included in the AI Mode response:

AI Mode Considerations for Local Search

This study showed that when it comes to local health clinic searches, most users still prefer traditional Google features like Maps, Places, and direct links to clinics. While AI Mode occasionally provided helpful information like specific services and hours, it often fell short by surfacing results that were too far away, not clinics at all, or missing the details people care about most like reviews, ratings, and insurance acceptance.

At the same time, there were glimmers of potential in AI Mode. Some participants liked that it adapted to very specific queries, such as asking about weekend hours, x-ray availability, or insurance coverage, and they appreciated the conversational follow-up prompts. This suggests that if AI Mode can better integrate maps, filters, and clinic-specific data, it could eventually complement or even enhance local search experiences.

However, the majority of users still bypassed AI Mode altogether, relying instead on Google Maps, Yelp, or their insurance websites to get the most reliable information quickly.

Much of this speaks to the importance of the content on your Google Business profile. Ultimately, people expect all of the business attributes front and center. There’s a way for AI to do that effectively, but AI Mode actually makes the results worse. For people to choose AI Mode over Maps or traditional SERPs, it needs to create a better layout with the information that people want, presented in the way that they want it.

Read the previous articles in this series:

The post AI Mode Impacts on Local Search: Researching Local Health Clinics appeared first on iPullRank.

AI Mode Impacts on Publishing: Researching Local News and Sports Headlines

Francine Monahan — Thu, 25 Sep 2025 12:24:18 +0000

“It didn’t occur to me to use AI Mode.”

That’s what a 74-year-old Orlando man said when prompted to use it to research local news in his area instead of his usual sources of Fox News, ABC News or the Drudge Report (yes, it’s still around and it looks exactly the same).

Nearly all of the participants in this search did not initially consider using AI Mode until they were prompted to because they all had their own favorite sources for local news and sports. Local news stations, ESPN, social media, and Reddit topped the list of preferred news sources.

They were also concerned that AI Mode was not accurate or timely with its information, so there was some skepticism about the credibility of the summaries.

There were many interesting reactions to AI Mode in our study with Farrah Bostic of The Difference Engine to learn the search habits of average people. She surveyed 100 participants, spoke one-on-one with 23 users, and watched them perform searches in real time.

Participants ranged in age from 18 to 75 with a balanced mix of ethnic backgrounds, genders, education levels, and locations across the country.

Each user performed five different queries:

Find out which credit cards offer the best loyalty programs.
Find out which kinds of breakfast cereals are healthiest for children.
Find out the top news or sports headlines in your local area.
Find a health clinic in your area.
Find a pair of shoes to wear indoors for under $75.

Today, we’re looking at the third search task we asked participants to perform: researching local news and sports headlines. We’ll see if any interesting search habits pop up so those in the publishing industry can get a better grasp of the future of search for news.

Overall Data from the AI Mode Study

Here are the overall findings from task #3 from our AI Mode study:

38.24% were shown AI Mode as an option
2% used AI Mode, but none of them used it unprompted
18.6% engaged with AI Overviews and 75% unfurled them
14% of those who unfurled AI Overviews clicked on the links
Average number of links clicked: 1.09
Average time to complete the task: 56 seconds
Average score for ease: 4.1
Average score for satisfaction: 4.39

These are the typical search terms the study participants used:

Terms that would ensure locality of the results, like “near”, or a specific city or county name as part of the search string
Words that would yield timely results like “today” or “breaking”, indicating they were searching for current, up-to-date information
The word “stories”, which might indicate either a desire for narrative/articles over stats and headlines
Refinements to search specifying geographic locations, adding town/city names or zip codes to the search string

Some clicked on the News tab in Google then engaged with the Top Stories there, and while some engaged with the AI Overviews, many were concerned that the information was not timely or current.

Many bypassed searching altogether by going straight to their local TV station websites, or ESPN, Fox Sports, or other sports-specific websites if their interest was more in sports news. Some also preferred to go to social media or Reddit for news. One ChatGPT user found the LLM’s news inaccurate.

AI Mode was mostly seen as generic, less visual, and less trustworthy for current events.

Using AI Mode to Research Local News and Sports

No matter how many of these recordings I watch, I will always see someone do something I’ve never tried before. A 43-year-old participant from Fresno, CA, said she typically selects the Google News page from the menu on the right. I never even noticed that option in there before:

She then clicked the local news feed on the right to see the article headlines:

When prompted to use AI Mode, she thought it was much easier to simply click the News tab in Google rather than type out a prompt because that involved extra steps.

“I didn’t like that, to be honest,” she said.

Though AI Mode gave her different results, she thought they were still good. However, she wished there were more links within the summary (aside from the ones on the sidebar).

Another user had a different way of searching local news that I hadn’t seen before, either: he entered his zip code into the search.

When prompted, he tried AI Mode but decided “it’s more generic to me.”

One participant prefers to visit her local Facebook page for news, but overall tries to avoid the news if possible.

“I don’t watch the news because that’s just too much negative information for me,” she said.

She prefers to look up sports news for her favorite teams, the Phillies and the Flyers. Typically, she would enter “Phillies schedule” or “Flyers news” into Google to find out scores or game dates.

Oddly enough, unprompted, she said: “I would actually like it if the AI tool gave a summary of what’s been going on instead of having to look at all these different headlines.”

Well, she’s in luck, because that’s exactly what AI Mode does. But although she thought its summary was good, she didn’t think there were enough links and didn’t trust the content.

“Where are they getting this information from?” she asked.

She wasn’t the only user looking at their local Facebook group for news, though. A 45-year-old from New Jersey said that’s the first place she’d look for news, but she decided to give AI Mode a try.

She searched specifically for “body in Schuylkill,” which is apparently such a common occurrence that AI Mode showed a list of all recent times they found a body in that particular river, and even included a warning at the bottom emphasizing that these were separate instances/bodies:

Another participant would check her local NBC affiliate first for local news, but would consider checking Google and AI Mode for any follow-up questions. She said she liked how AI Mode gave a summary of the main headlines:

We can’t discount Bing, because someone in this study uses the Bing app to see top news headlines from Microsoft. She also checks social media for breaking news.

“It’s in my algorithm,” she said.

Many users tend to look at social media first for breaking news.

“I usually go on social media apps like Instagram, Twitter, Reddit,” another user said.

She has tried clicking the News tab on Google but said, “It’s never been appealing to me as an option,” explaining that the times she’s used it, the results have “been somewhat random.” After trying AI Mode, she was pleased with the results.

“This AI Mode actually is better than a lot of other news update features I’ve seen recently. Way, way better than the News tab.”

Reactions to AI Mode and its Format

One study participant specifically visits X for news, “just to see what people are talking about,” but tried AI Mode to look up sports news in Minneapolis and liked the results:

“It gives a good summary of each team,” he said, because it lists the key points so you don’t have to hunt for them. He added that he likes using LLMs like ChatGPT, Grok, and Gemini for in-depth analysis, but when it comes to just searching for quick info like this, he’d probably just use the Google search bar.

Another user who was less than keen on reading the news prefers to read video game updates. He tried AI Mode to see if it was up to date with the latest Xbox layoff news (he didn’t expect it to be) and the result surprised him.

“This does seem to have some of the recent news information in it,” he said.

But he didn’t enjoy the layout and the lack of images and graphics in AI Mode:

A 29-year-old participant from Virginia also disliked the layout pretty strongly. When he used AI Mode to find the top news headlines, the block of text he received didn’t feel impactful to him.

“Whenever the information is like this, it makes me not want to read it,” he said. “It’s not how I want to consume this information.”

However, another user actually liked the layout of AI Mode because he was looking for text to read rather than visuals. When he looked up sports headlines in NYC, he said he liked how the summary was divided by the different sports and they weren’t all “jumbled together.”

“It’s definitely showing me a different way of searching right now,” he said.

The AI Mode layout pleased a 29-year-old from Boston, who said: “There’s nothing wrong with my current workflow, but if I were really just looking for, like, a two-minute general rundown like this, I could see myself using it.”

While another user would typically do either a traditional Google search for local news stations or look at Fox News and ABC News, he was open to trying AI Mode to see the results.

He liked how it summarized the headlines for him in a clean format. “This is a much better result for me,” he said.

One study participant is on various work-related listservs and receives news updates every morning. He also gets news from X and LinkedIn, only clicking on articles that look interesting.

However, he noted that these days, articles are often behind paywalls and you need a subscription to read them. So if he wants to look up specific sports news, he tends to go to ChatGPT where it’s more direct and laid out point by point.

When he tried AI Mode, he was impressed:

“This is much better than the typical Google search,” he said. “This is much more helpful.”

He even tried a follow-up query for more specifics:

Skepticism for AI Mode

A 41-year-old from California tried AI Mode to look up stock news and liked the results. He was concerned that stock news in a Google search is not up to date, but he liked how AI Mode displayed dates.

“I actually like this. It gives you a pretty good summary of anything you search about,” he said. “It’s timely and it’s not based off something else years ago, months ago.”

When one user searched for local news in Idaho Falls, he noticed a few articles on the side panel that had dates, but it was hard to know the timeliness of the news in the AI summary.

“They are relevant I guess, I just don’t know when they happened,” he said.

He also didn’t think the top stories were very interesting.

“It says they’re top stories and urgent alerts but is this something I would consider a top story? Probably not,” he said.

Ozzy Osbourne had just passed away at the time of this study, and one participant said when he heard about it on social media he Googled it and saw all the news stations carrying the story, so that proved to him that it wasn’t fake.

AI Mode also knew about it, but since it just happened there wasn’t much to say about it yet. It just took the same info from other articles:

But when the user looked up a video game he liked, there was much more information for him:

AI Mode Considerations for the Publishing Industry

When it comes to local news and sports, AI Mode isn’t winning over the crowd just yet. Most people still fall back on their familiar habits, be it social media, local news sites, or going straight to ESPN for sports news. But what we did see was curiosity and an openness to try AI Mode for news.

Some participants appreciated the quick rundowns and clean summaries, helping them get the news in one place rather than clicking around to various articles. Others found it too wordy, too generic, or too out of date for breaking news stories.

The tension between convenience and trust, and speed and credibility will define how AI Mode grows in the news space. Users aren’t closed off to AI summaries, but they want them to feel timely, transparent, and useful. Until then, AI Mode is more of a supporting act than the main stage in the publishing industry.

Read the previous articles in this series:

The post AI Mode Impacts on Publishing: Researching Local News and Sports Headlines appeared first on iPullRank.

AI Mode Impacts on Ecommerce: Researching Healthy Breakfast Cereals

Francine Monahan — Wed, 17 Sep 2025 19:25:19 +0000

Three “wow’s” in a row were the reaction of one participant in our AI Mode study who was using AI Mode for the very first time.

“It’s like a search within a search engine,” she said.

She enjoyed asking follow-up questions to her query for the healthiest breakfast cereals for children, like which of them included strawberries. Though unsure at first how AI Mode would contribute more than was already provided by AI Overviews, she’s officially been converted and will be using it more in the future.

“I am pleasantly surprised,” she said.

We saw many interesting reactions to AI Mode in our study with Farrah Bostic of The Difference Engine to learn the search habits of average people. She surveyed 100 participants and spoke one-on-one with 23 users specifically about AI Mode and watched them perform searches in real time.

Participants ranged in age from 18 to 75 with a balanced mix of ethnic backgrounds, genders, education levels, and locations across the country.

Each user performed five different queries:

Find out which credit cards offer the best loyalty programs.
Find out which kinds of breakfast cereals are healthiest for children.
Find out the top news or sports headlines in your local area.
Find a health clinic in your area.
Find a pair of shoes to wear indoors for under $75.

Today we’re looking at the second search task: finding the healthiest cereals for children. For those in the ecommerce industry, the patterns emerging may give you a taste of what the future of search will look like for your prospective customers.

Overall Data from the AI Mode Study

These are the general findings from task #2 in our survey:

33% were shown AI Mode as an option for this search
2% used AI Mode in the unmoderated task; no one in the live interviews used AI mode unprompted for this task.
33 seconds was the average dwell time in AI Mode
47% engaged with AI Overviews
76.6% of those who engaged with AI Overviews unfurled them
20% of those who engaged with AI Overviews clicked on links within it
Average number of links clicked: 1.96
Average time to complete the task: 2 minutes, 7 seconds
Average score for ease: 4.05
Average score for satisfaction: 4.05

Here are some typical search terms participants used in this study:

9% of participants phrased their search as a question
Users also refined their search terms with more specific keywords like “best” or “good” (as opposed to healthiest /healthy /most healthy), or “kid-friendly”
Some also specified qualities like “with protein” or “organic”

Overall, AI Mode was considered useful for summarizing nutritional guidelines and recommending brands for healthy cereals. Users also appreciated being offered a way of thinking about what constitutes a healthy breakfast cereal for kids, noting characteristics like fiber, low/no sugar, and no food dyes.

Users consistently noted that for groceries like cereal, they would typically shop in person at a grocery store rather than purchasing online through search results. However, participants valued AI’s ability to synthesize information from multiple sources (blogs, articles) to provide a comprehensive answer, saving them time.

Three participants in the live interviews felt the most likely scenario for them in a search like this would be to compare options in-person at a grocery store rather than searching online. And almost all participants said their most likely next step would be to purchase cereal in-store rather than online.

Using AI Mode to Research Breakfast Cereals

One participant in the study who typically uses ChatGPT decided to use AI Mode first to search for the healthiest breakfast cereals for children. She believed that AI opens up a wider and broader search, and is more reliable.

“I know it’s going to scan the research to give me the information that I’m looking for versus if I just would have Googled it,” she said.

However, she was disappointed because she had to scroll pretty far down in AI Mode to get to the actual cereal brand names. And even then, it only offered her five results, which she thought wasn’t enough:

Another user agreed and also didn’t like having to scroll far down to reach the actual products. He would’ve preferred the order to be reversed. He did like the information it provided, though, saying “I could engage with this more.”

One user liked the practical tips for choosing healthy cereal, saying she found them helpful.

“This is more interesting to me,” she said.

However, other users saw branded products show up first in their search results, showing the unpredictable nature of AI Mode and how different everyone’s results can be. One user said she was pleased with the number of results suggested, even though there were still only five:

Another participant found it interesting that the cereal links on AI Mode took you to another Google page that had product and shopping information:

One participant wondered if the AI results were less “SEO-influenced” than traditional search results. He believes that you’re often seeing a biased version of the results you want on Google, so he thinks optimization might be impacting the cereals that appear in the results.

“There’s obviously something on the backend that Cheerios is doing to make them pop up first, even if what they’re saying is true,” he said.

AI Overviews vs. AI Mode

Much like the previous task in this study, some users expressed confusion about the difference between AI Overviews and AI Mode results, but many seemed to agree that they found AIOs helpful.

“Whenever I see this AI Overview pop in, I generally look at it,” one user said. And if he has additional questions he will click “dive deeper” and ask AI Mode follow-up questions.

Another user said there was some overlap between AI Overviews and AI Mode, but AI Mode is more detailed. It even divided the cereal options into low sugar and high fiber, and gave more advice on what to pick:

When AI Overviews show up, another user said she always looks at them first. Instead of just getting a list of links to webpages, she now gets explanations and descriptions.

She also likes using AI Mode on her phone through voice commands because it’s “like asking a really smart friend.”

When she searched for cereal on AI Mode, however, she thought some of the articles on the right were a bit too old to trust, but said she would probably click on the most recent one:

Another user agreed that AI helped take some of the work out of searching. Instead of querying and then having to read a bunch of top 10 listicles and making comparisons himself, AI Mode could handle that for him.

However, he said he wouldn’t use AI Mode for quick facts, like researching the population of a country or the age of a celebrity, because Google still has that perfected.

User Search Preferences

A number of participants said they would typically skip this type of query in favor of an in-person visit to the grocery store to compare ingredients. Or they would just do minimal research first before going to the store.

“I would probably just research this and then make a mental note for the next time I’m at the grocery store,” one user said.

Some would even go to their local grocery store’s website or Instacart instead. One user said he goes to Amazon and reads reviews, focusing on the negative reviews because he feels those are the most honest.

One user shared that he would go to Reddit and visit the parenting subreddit and search there.

“I’d probably come to actual parents for that, not necessarily the robot,” he said.

Another interesting search habit was the user who has had his Google set to Advanced Search for years simply because he likes the option of adding words and phrases for filtering.

“It’s just second nature to me,” he said.

AI Mode Considerations for the Ecommerce Industry

There are so many ways that people shop online these days. Some perform deep research before making a purchase, while others just head over to Amazon and click whatever has good reviews. And with the addition of AI Mode, shoppers have a new way to find products, even if the information displayed doesn’t always feel natural or follow the format of how people shop.

Ecommerce teams should consider the growing importance of comprehensive product information that can be easily parsed by AI systems, as users increasingly rely on AI to filter through multiple sources and compare products. However, the study also highlights that despite AI’s ability to provide detailed product insights, the purchase journey for many food products still culminates offline.

While AI Mode shows promise, the reality is that most users still prefer the experience of in-store shopping for everyday items like groceries. Will that change as people become more familiar with these AI Search platforms? It’s difficult to determine. But only a certain type of person would jump through these research hoops to find a healthy breakfast cereal.

The unpredictable nature of AI Mode results also shows the importance of strong SEO fundamentals alongside emerging AI optimization strategies, especially as users begin using AI Mode more often.

For the one participant using AI Mode for the first time in this study, even though using Google is still a habit, she may start using AI Mode from now on.

“The AI Mode tab is definitely intriguing me after today a little bit more,” she said.

The post AI Mode Impacts on Ecommerce: Researching Healthy Breakfast Cereals appeared first on iPullRank.