AI (Artificial Intelligence) Insights from Seer Interactive

Re-imagining AI Visibility KPIs in a Query Fan Out world

Admin — Fri, 02 Oct 2026 16:30:48 GMT

Wil, take me right to the KPI for long term sustainable GEO visibility!!

SaaS Marketers - Promote your Claude & Codex connectors & win in AI search

Admin — Mon, 28 Sep 2026 20:30:29 GMT

Claude and I had a 12,000 word back and forth on how to use Cloudflare and GA4 data to answer a hard question. If you were a SaaS marketer what would you do with all that context to make better answers?

AI Citations Aren't Your Top KPI: ChatGPT-5.6 Luna Runs More Targeted Searches

Admin — Thu, 24 Sep 2026 19:36:11 GMT

TL;DR

We ran a direct comparison of 346 matched prompts to see whether ChatGPT-5.6 Luna behaved differently from GPT-5.5
GPT-5.6 Luna used web search more often but ran fewer queries, resulting in little movement on the number of fan-out queries compared to GPT-5.5
Domain-target searching increased drastically (more than 3x), while consulted sources and inline citations dropped
Our take: Luna is getting better at finding information and needs fewer resources, so brands should pay more attention to the full retrieval process to measure AI search visibility

How Do ChatGPT-5.5 and GPT-5.6 Differ?

We’ve researched ChatGPT-5.5 extensively, including a deep dive into fan-out patterns. Now that GPT-5.6 Luna is the default model as of July 9, 2025, it's the model people get when interacting with ChatGPT and the model brands will be reporting on through AI visibility trackers.

With that in mind, we wanted to know how the two models compared. Specifically:

How did the retrieval process change across domains and citations?
Does GPT-5.6 Luna search similarly, or were there notable differences?
Did fan-out query behavior shift or stay the same?

We compared GPT-5.5 and GPT-5.6 Luna across 346 matched prompts from six industries.

Spoiler alert: At first glance, the two models looked very similar. Across the 346 matched prompts, they ran almost exactly the same number of fan-out queries. The difference is how targeted Luna's searches are. It used the site: operator in 76% of its fan-out queries, up from 22% with GPT-5.5.

That leaves far fewer open searches for everyone else. So if Luna isn't already searching your site directly, your barrier to showing up is higher than it used to be. Check out our top findings below.

1. GPT-5.6 Luna Uses Web Search More Often, But Runs Fewer Queries Per Search

GPT-5.6 Luna turned to web search more often than GPT-5.5. Across the six industries, Luna searched on 85.2% of calls, up from 80.8%. But each time it searched, it ran fewer fan-out queries: 3.42 per search, down from 3.63.

Those two changes almost exactly cancel each other out. Luna searched more often but ran fewer queries each time, so the total number of fan-out queries barely moved. GPT-5.5 ran 733 and Luna ran 729, a difference of just four.

We thought there would be more fan-out queries after the model update, especially given the increase we saw when GPT-5.5 was released. Instead, the total stayed the same, and the change showed up in how Luna searched.

Our hypothesis is that Luna needs fewer queries per search because its queries are more targeted. When a fan-out query goes straight to a specific website (more on that in the next finding), one query can do the job that used to take several broader ones. So the two changes balance out in volume, but not in effect. More prompts now send ChatGPT to the web, and each search covers less ground.

2. Domain-Targeted Searching More Than Tripled, Especially on Non-Brand Prompts

GPT-5.5 had already begun using the site: operator (a search command that limits results to a single website) in fan-out queries to target specific brand sites for answers and, in our opinion, prevent low-quality responses. GPT-5.6 Luna elevated this retrieval method even further.

GPT-5.5 conducted site: searches in about 22% of its fan-out queries, while Luna did so in 76%.

On branded prompts, third-party sites (publishers, review sites, research orgs, etc.) appeared at roughly the same rate with both models: 26.6% with GPT-5.5 and 24.4% with Luna. So even when a user asks about your brand directly, ChatGPT still looks beyond your website.

That means the perception of your brand outside of your website matters just as much as the narrative you share on sources you control.

The actual jump came from prompts that didn't mention a brand. Non-brand prompts saw a rise in site: searches, from 20.6% in GPT-5.5 to 77.3% in GPT-5.6. That means Luna was the one to decide on a domain to search even when the user didn’t specify a brand or website.

Since ChatGPT is getting more targeted with its retrieval, the overall number of consulted sources (the sources ChatGPT pulls in while searching, before it decides which ones to cite) fell 43%, from 6,134 with GPT-5.5 to 3,481 with Luna.

This presents a unique opportunity for brands launching AI search programs. If GPT-5.6 Luna is already targeting your site with site: searches, make sure the information it's looking for is easy for both people and AI to find.

If your brand isn't one of the sites Luna searches directly, you may see fewer citations now that it's the default model. Open searches, the ones any site could appear in, fell from 575 to 175, so getting results will likely take more work.

Look at every stage of retrieval, from fan-out queries to consulted sources to citations, to see how and where ChatGPT finds information about your brand.

3. Inline Citations Fell 13%

We know Luna searched in a more targeted way and consulted fewer sources. In the final answers, it also gave fewer inline citations (the sources linked in the answer itself).

Across all 346 matched prompts, GPT-5.5 produced 2,054 inline citations, while Luna produced 1,790, a decrease of 12.9%. Searching more often didn't translate into more citations.

Our take is that Luna has gotten better at knowing where to find information, so it needs fewer sources to back up its answers.

This matters for any AI search program that uses citations as a KPI or as the success metric for an experiment. If your citations dropped after Luna became the default, that may have nothing to do with your strategy or the tests you have running.

Think of it like a Google algorithm update: the platform changed, and performance shifted with it. Mark the switch to Luna in your reporting so a platform-wide drop doesn't get read as a failed experiment.

So What Should You Do Now?

How can you apply these findings to your AI search strategy? Here are my recommendations:

Look further down the retrieval process when you’re measuring AI search visibility. Most AI visibility trackers only report citations, the bottom line of the retrieval process.

The bigger benefit comes from the layers behind them: the fan-out queries ChatGPT runs, the domains it targets with site: searches, and the sources it consults before deciding what to cite. That's where you'll see why your citations moved, not just that they did.

Pay closer attention to the connections the models appear to make between brands and topics. Luna often decides which sites to search before it retrieves anything, so being recognized as a relevant source for a topic matters before any page gets retrieved.

Run a base set of nonbrand prompts you’ve been monitoring to capture the fanout queries and sort the site: searches by topic. Which topics does ChatGPT search your domain for, and which does it search your competitors' domains for instead?

Compare across models or over time, and you'll see where you're gaining ground and where a competitor owns the association. The topics your competitors own are where you should focus next: both in your own content, and in your coverage on publishers, review sites, and research organizations.

Ready to level up your AI search strategy but don’t know where to start? The Seer team has extensively researched what works and what’s a short-term trend, and we can recommend where to put your resources based on your industry, budget, and team size. Chat with us to learn more.

Our Most Valuable Blogs of 2026: According to Our Readers

Hannah Cooley — Tue, 22 Sep 2026 21:00:18 GMT

What's my favorite horror movie? When I patted myself on the back for setting up an ~autonomous workflow~ that kept our newsletter subscriber hygiene clean by automatically unsubscribing anyone who hasn't opened any of our emails in the past 12 months.

Google Is Not Going to Stop Ranking Your Claude-Assisted Content

Admin — Fri, 04 Sep 2026 18:24:31 GMT

TL;DR

Claude’s watermark only flags that Claude was “likely involved,” so it can’t tell a fully AI-drafted piece from a human draft Claude lightly edited
It’s an EU compliance requirement (Code of Practice on Transparency of AI-Generated Content). This is not a new Google ranking signal.
Google has run its own version (SynthID-text)on Gemini for two years and never used it to rank anything
The real traffic risk is thin, templated content and not the watermark. Sites that scaled content off a copy-the-template approach saw more than half those lose 30%+ of peak organic traffic
What still matters: unique inputs and a human accountable for the final piece

Anthropic started watermarking Claude's text output.

AI Visibility Is Lying to You: There’s No One-Size-Fits-All AI Search KPI

Admin — Mon, 31 Aug 2026 19:59:48 GMT

TL;DR

Everyone measuring AI search is defaulting to the same KPIs, but there is no one-size-fits-all AI search KPI
New research shows 54% of AI search categories lack a clear category owner, and those categories represent 89% of all AI search demand
If someone else owns your category, you should stop chasing visibility and instead focus on accuracy: when you do show up, does the model describe you the way you actually want to be described?
Accurately measuring AI search KPIs requires a brand canon, a living document of your brand’s claims, positioning, facts, and more

Your Visibility Score Can Be Perfect and Still Be Wrong

AI can mention a brand in every prompt you track, but that brand can still be losing.

How we built an agentic loop to improve every skill in our company, instantly

Admin — Thu, 20 Aug 2026 18:48:49 GMT

TL;DR

I reviewed our traffic-decline-analysis skill's and found four real problems: a traffic number from the wrong source, a real drop mislabeled "stable," no way to trace where a number came from, and no long-term trend view
I gave that feedback in a 9-minute recording and an agent picked up my feedback and fixed it the same day, and it shipped to everyone at Seer.
I found another problem the skill was picking which checks to run instead of running all of them, every time
An offhand idea from that same review became a new feature days later. The tool now runs off a simple spreadsheet export instead of needing live client data

Here’s how it all happened…

What Is AI Saying About Your Brand? Develop a Brand Canon and Find Out.

Admin — Mon, 17 Aug 2026 16:37:16 GMT

TL;DR

Brands are measuring AI visibility without tracking if the perception of their brand is even accurate
We recommend building a brand canon, which tracks facts, differentiators, brand claims, what your brand wants to be known for, and what you don’t
Once you’ve created your canon, you can use it to compare what you want AI to say about your brand versus what it actually says (and fix the output by tracing claims to their source)
Learn how to build your own brand canon, how to measure the accuracy of claims made by AI, and how to prioritize fixing falsehoods and inaccuracies

What Happens if AI Shares Inaccurate Info About Your Brand?

A potential customer asks AI what your company does, and the answer comes back about 70% right (per Seer's analysis of 28,123 responses about our brand across 6 AI models). But nearly 30% of the information is wrong or outdated, or the model declines to answer.

Our Early View of ChatGPT Ads: 5 Initial Observations - Updated July 28, 2026

Admin — Tue, 28 Jul 2026 04:00:00 GMT

When we first published this on July 15, we were working from three days of ChatGPT ads data. Revisiting the data this week, our main takeaways haven't changed, but ecosystem is evolving. Share of responses with ads rose significantly, a wider set of brands is now buying them, and early patterns are sharpening.

The updated numbers below now reflect about 2 weeks of data. With that, we advise you treat this as a developing study. It's still early and we are prepared for this to change fast.

OpenAI officially launched the ChatGPT Ads pilot on February 9, 2026, rolling the placements out more widely as of May. While we've been tracking how ads work, tests and usability through our own pilot and other studies, we have not had a view into how often they show up, what types of prompts they’re shown for, and how well they align with those responses that they are served under.

That changed this week when ads started appearing in our AI tracker.

How to Use AI to Enhance Client Relationships (Without Losing Your Competitive Edge)

Admin — Fri, 10 Jul 2026 04:00:00 GMT

This blog was originally published on December 4, 2023 and was updated on July 10, 2026.

Is Your Brand Considering a Reddit Strategy for AI Visibility? Here’s What to Do.

Admin — Wed, 08 Jul 2026 17:11:36 GMT

Brands have heard that Reddit matters for AI visibility. Many of them are adopting the mindset of “we need to be on Reddit” without thinking the strategy through.

Can a prompt undo years brand building? Our AI interview tests say yes

Admin — Wed, 01 Jul 2026 17:11:04 GMT

TL;DR: We interviewed 28 people across almost 100 tasks, having them use AI to solve a product selection problem, and we ask them what brands people intend to buy, before using AI, then we check what brand they considered after.

One AI research session cut GE's purchase consideration in half while lesser known brands like Rheem surged.

The questions we wanted to answer:

When someone has a task, what brands do they think would solve their problem before they search or use AI?

The Proof: ChatGPT 5.5's fanout patterns reveal the importance of brand

Admin — Thu, 25 Jun 2026 17:04:44 GMT

If you've been looking at the whole "do I have to do listicles" thing and throwing up in your mouth a little, this post is for you.

Your AI Traffic Is Hiding: A Practical Guide to Tracking ChatGPT, Claude, and More

Admin — Mon, 22 Jun 2026 04:00:00 GMT

This blog was originally published on December 2, 2024 and was updated on June 22, 2026.

⚠️ AI Tracking Is A Moving Target

The AI tracking landscape evolves rapidly. Since our original publication, Google launched its native AI Assistant channel (May 2025), ChatGPT shifted from 'citations' to 'sources,' Claude added embedded links capabilities, and ChatGPT introduced advertising. Methods described in this blog represent current best practices as of the last update date, but we encourage you to validate these approaches yourself as platform behaviors continue to change.

Are you trying to better understand how searchers are using ChatGPT, Gemini and other AI platforms to find your websites? We sure are!

Selecting the right prompts for AIO / GEO tracking could use a human touch

Admin — Tue, 16 Jun 2026 19:19:49 GMT

The Stats

We compared the earliest UX reports we did against the most recent one we did, the data is messy, but here is what we're seeing in terms of how people seem to be changing how the prompt from 1 year ago, the data is limited to only 7 studies but its something to start learning from:

300% increase - In the frequency of people putting personal information into their AI prompts.

270% increase - In what we categorize as delegation prompts (i.e. do this thing for me).

83% decrease - in prompts that look more like keyword searches, than structured thoughts.

25% increase - in median prompt length

Here's the full contrast from July 2025 to June 2026, in one frame:

Question your AI prompt selection status quo:

Ask yourself these questions relative to your GEO brand tracking efforts:

Allow GPTBot to Crawl Your Site | Seer Interactive

Admin — Mon, 15 Jun 2026 04:00:00 GMT

Editors Note: This post was originally published in August 2023, shortly after OpenAI announced GPTBot. Our core instinct in response to this update was: don't block your way out of visibility, and we still support that. However, things have changed significantly since then.

We've added 2026 updates throughout this post where our thinking has been refined, corrected, or made more specific, and a full update at the end on our thinking. But we have preserved our original post to really show what's changed.

A couple weeks ago, OpenAI, the creators of ChatGPT, released information about their web crawler GPTBot.

How to Prioritize Your Work 2.0: How AI Changed Everything in My Fruit Bowl

Admin — Tue, 09 Jun 2026 04:00:00 GMT

This post was originally published on May 18, 2023 and was updated on June 9, 2026.

A few years ago, I wrote about treating your to-do list like a bowl of fruit.

Lemons were your dreaded tasks, apples were big focus blocks, oranges were chunked-up projects, and grapes were your quick wins.

I still think about the framework every day. But now that AI has entered the picture, it’s changed both how I “eat” my fruit and what's actually in the bowl.

If you didn’t read the original post, no worries; I'll give you a quick refresher. But if you have, buckle up, because we're doing a 2.0.

6 Ways AI Can Improve Your User Research (& 3 Things to Watch Out For!)

Admin — Mon, 01 Jun 2026 04:00:00 GMT

This blog was originally published on February 12, 2025 and was updated on June 1, 2026.

UX research is powerful—but slow. Finding participants, analyzing responses, and making sense of data can take weeks.

From Launchpad to Seer: Meet the Interns Behind Our AI Optimization Academy

Bryan Gunawan — Fri, 29 May 2026 04:00:00 GMT

Earlier this spring, we launched our AI Optimization Academy in partnership with Launchpad, bringing three Philadelphia interns into Seer to do real GEO research and testing alongside our team

What It Takes To Rank In Google's AI Overviews in 2026 Isn't What You Think

Admin — Thu, 28 May 2026 20:00:00 GMT

AI Overviews (AIOs) now appear on nearly 65% of question-based searches, which are the same queries informational content is built to win. The citations inside the AIOs represent one of the most meaningful positions in the SERP, as they are the closest element we have to a first position link or a featured snippet. It's the new position zero. And that makes it prime real-estate for Google search visibility.