AI Is Talking About Your Brand. Are You Measuring What It Says?
Google's AI Now Speaks for Your Brand
Branded search used to be the safe zone. Not anymore.
What's the News:
Google AI Overviews now appear on more than 80% of branded searches, up from roughly 26% at the start of September, according to DemandSphere data reported by Search Engine Land. The surge hit late in the month, peaking at 90.48% on September 27. Separate testing of 100 enterprise brands found AI Overviews for 93 of them. Google hasn’t announced a change.
Why It Matters:
Branded terms are now AI territory: AI Overviews aren’t new, but for most brands, they were only a focus for non-branded terms. Now that they’re present for the majority of branded terms, they have the potential to significantly impact performance.
Google is summarizing your brand for you: The first thing a customer sees when they search your name may now be Google’s take on your brand, not your website. Google decides what that summary says and which sources it pulls from, and an unflattering one can send a ready-to-buy customer to a competitor.
The click impact is still unknown: Neither study measured click-through rates, which means brands that aren’t tracking this themselves are flying blind.
It all comes back to your measurement framework. From an organic search standpoint, branded terms haven’t needed to be a focus because you’ll likely rank for them regardless. Now it’s no longer about how you rank for those branded terms; it’s about how your brand is portrayed. Without the right measurement approach, you could be portrayed negatively and not even know it.
Marketers Should:
Track which branded queries trigger AI Overviews and what those summaries actually say about you.
Build a set of direct branded prompts to monitor how AI describes your products, reputation, and value.
Add brand vs. competitor prompts to measure sentiment where purchase decisions actually get made.
Check which sources Google cites in your branded AI Overviews. Those pages are now shaping your first impression.
Measure on a recurring cadence, not once. Branded AI Overview presence nearly tripled in a matter of days.
Google Just Defined Quality Content. Most Content Won't Pass.
Effort, originality, skill, and accuracy are now the bar for what ranks.
What's the News:
Google quietly updated its guidance on creating helpful, reliable content, stating that the quality of a page’s main content is “one of the most critical factors for assessing page quality,” as reported by Search Engine Land. The update defines main content broadly across five categories (text and media, interactive tools, user-generated reviews, tabbed sections, and even titles and headings) and lays out the four attributes Google’s search quality raters are trained to judge: effort, originality, talent/skill, and accuracy.
Why It Matters:
Google is telling you, in writing, what separates a page that ranks from one that doesn’t: whether a human actually did work on it. Pages built on templated copy, auto-generated product descriptions, or thin AI drafts with no original analysis are exactly what this guidance flags as low effort.
The bar is higher in regulated verticals: For brands in health, finance, or other YMYL (“Your Money or Your Life”) categories, content must be highly accurate and consistent with established expert consensus.
Expect volatility: This lands while a Google spam update is actively rolling out. Content teams should expect this to show up in ranking volatility, even if Google won’t confirm the two are connected.
Marketers Should:
Audit your highest-traffic pages against these four criteria now: effort, originality, talent, accuracy. If a page fails two or more, it’s a target, not a bystander, in the next update.
Stop shipping content that could have been written by anyone with a keyword list. Raters are explicitly trained to distinguish original analysis from mass-produced AI text with no human oversight.
Push harder on original data, proprietary research, and first-hand experience in your content calendar. That’s what “originality” means here, not a different adjective in the intro paragraph.
For YMYL brands, put a real subject matter expert’s name and credentials on the page, not a generic byline. Google now explicitly ties accuracy on these topics to expert consensus.
Treat tabbed sections, calculators, and interactive tools as main content, not decoration. Google just told raters to evaluate them the same way they evaluate your body copy.
Watch your rankings through the spam update rollout and map any losses back to these four criteria before you touch a single page. Guessing wastes a sprint you don’t have.
ChatGPT Ads Are Going Visual
The first test looks more like display than search.
What's the News:
OpenAI is introducing a new visual ad format in ChatGPT, using images to show product inspiration, product usage, and the experiences a brand makes possible. Testing begins later this month in the U.S. with an initial group of advertisers, starting during image generation for users on ChatGPT’s Free and Go plans. Ads will be labeled and kept separate from the generated image, and OpenAI says they won’t influence ChatGPT’s answers. With ChatGPT reaching 1.2 billion people weekly, that’s a significant new visual advertising surface.
Why It Matters:
This isn’t a feed: It’s a creative environment that looks fundamentally different from social or display, which means simply repurposing Meta or display creative may not be enough. Marketers will need to learn which visual concepts add value in context, and how creative should change when the audience is actively creating, researching, or imagining rather than passively scrolling.
The first placement has low commercial intent: Someone generating an image is using ChatGPT as a tool, not researching a purchase. As Eric Seufert points out at MDM, that likely means targeting relies on advertiser conversion data (Pixel and Conversions API) rather than conversation context, and that chatbot ads may end up closer to a feed or video ad than a search ad.
This is the first sign ChatGPT ads may behave more like a display or social channel than a search one, which changes how marketers should plan for it. The same principle driving performance creative on social applies here: more context should lead to more relevant creative, not more generic creative at scale.
Marketers Should:
Resist the urge to resize existing assets. Build creative for the context, not the placement.
Test imagery, messaging, and value propositions against different moments of intent to learn what actually earns attention here.
Plan for it like display or social, not search. Creative, audience quality, and first-party data signals will matter more than keywords.
Keep conversion data clean and CAPI-ready now. It’s too early to build around, but you’ll want to move quickly if it proves out.
ChatGPT Ads Won't Be Judged by the Last Click
OpenAI is building measurement around the question that matters: did the ad create new business?
What's the News:
OpenAI announced new measurement capabilities for ChatGPT Ads, including Pixel and Conversions API support, third-party attribution partners, geo-based incrementality testing, and early-stage brand lift measurement. Early results are notable: one geo-lift study by WorkMagic estimated 2.3x more incremental orders for wellness brand Dose than last-click attribution captured.
Why It Matters:
People do not use ChatGPT like they use search or social: They may research, compare options, and work through a decision without immediately clicking an ad. OpenAI’s own early data shows 52.7% of eligible one-day view-through conversions happened within an hour of an ad impression, with no click at all. That makes click-based attribution an incomplete view of performance.
OpenAI is building for this early: Rather than bolting on measurement later, the platform is launching with incrementality and view-through measurement from the start.
ChatGPT could influence a decision without driving the final click. The real question is whether the ads created additional leads, sales, or revenue that would not have happened otherwise. That should be the standard for every channel.
Marketers Should:
Get conversion signals in order. Clean Pixel and Conversions API data will matter for both optimization and measurement.
Separate attribution from incrementality. A conversion after an ad does not automatically mean the ad caused it.
Test incrementality. Use geo tests, holdouts, and MMM to measure the net-new business impact of ChatGPT and other channels.
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