Original AI-generated illustration for Flonci. Conceptual artwork, not a product screenshot.
Morning Consult's new State of Influencer and Celebrity Marketing report, drawn from 6,283 U.S. adults surveyed in September 2026, lands on a result that should change how creator budgets get argued about: smaller creators and famous ones produced the same share of claimed purchases, 44% each. Fame still wins affection. It no longer wins the checkout.
Every marketing organization carries an informal theory of fame. It sounds like this: if we are going to spend real money on a creator, spend it on the biggest name we can afford, because reach is the one input we can count in advance. The theory has always had a measurement problem, since reach is counted by platforms and revenue is counted by finance and the two never meet. What it has not had, until recently, is a direct consumer-side test large enough to trust.
The 2026 edition of Morning Consult's State of Influencer and Celebrity Marketing report provides one. The findings have been summarized in detail by trade coverage drawing on the report's published charts, and they deserve a careful reading, because several of them cut against the industry's defaults at once. Smaller creators convert as often as famous ones. Audiences name 1,787 different creators as their favorite. The traits that move claimed purchases are product use, honesty and expertise, while fame and attractiveness trail far behind. And creators now sit four points behind online search as Gen Z's leading way to find new products.
This article reads the survey the way a marketing decision-maker should read any large self-reported dataset: with respect for its scale, attention to what its questions can and cannot measure, and a hard line between what it proves and what it suggests.
What this survey actually is
The report draws on a survey of 6,283 U.S. adults, fielded September 17 to 22, 2026, with a reported margin of error of plus or minus one percentage point on the full sample. Morning Consult has tracked influencer attitudes in the U.S. since at least 2019, which is what gives the new edition its trend lines on trust. The report also rates 90 celebrities and creators on favorability and purchase lift, and asks an open-ended question about respondents' favorite influencer.
Three properties matter for interpretation. First, this is claimed behavior: respondents report what they bought and why, which is not the same as observed transactions. People are imperfect historians of their own spending; they over-attribute some purchases and forget others. What claimed-incidence surveys do reliably is compare groups, because the same memory biases operate on everyone, which is why the parity result below survives the self-report caveat better than any single percentage does. Second, the sample is U.S. adults only; Israeli, European or Asian creator markets have different platform mixes and different maturities, and the figures should not be exported to them as numbers. Third, the full report is gated. The figures discussed here are as published in coverage reproducing Morning Consult's charts, and Morning Consult's own public description confirms the survey's scope and sample. That is good grounding for a directional read, and it is not campaign performance data. Both things will matter below.
One design choice deserves explicit credit. Rather than asking whether influencers work in the abstract, the survey asks respondents to report their own purchases, name their own favorites, and rank what would change their own behavior. That produces data about the audience's actual decision process rather than its opinion of an industry, and it is what makes the findings usable for planning rather than only for arguing.
The parity result
The headline finding deserves to be quoted precisely. Among all U.S. adults, 44% said they bought a product in the past year because a well-known influencer or creator endorsed it. The same share, 44%, said they bought because of a smaller influencer or creator. Among Gen Z the figures are 67% for well-known creators and 65% for smaller ones, a gap inside the subgroup's margin of error. Celebrity endorsements land in the same band: 65% of Gen Z said they bought because of a celebrity on social media, 62% because of a celebrity in an ad.
Read that against the industry's pricing structure. Creator fees scale steeply with follower count, roughly an order of magnitude from micro to mega tiers. The survey says the claimed purchase incidence does not scale with it at all. Whatever fame is buying, it is not showing up as a higher share of consumers who say they purchased.
The careful caveats: claimed purchase incidence is not revenue per dollar, and the survey does not observe order sizes, margins, or frequency. A famous creator's 44% may contain bigger baskets. But the parity finding aligns with campaign-side evidence, including Israel's Humanz 2026 benchmark, where micro-tier campaigns posted returns comparable to celebrity-tier ones. When consumer-claimed behavior and campaign ROI data point the same direction from opposite sides of the market, the direction deserves to be taken seriously.
The fragmentation finding
The open-ended favorite-influencer question produced the survey's most structurally important number. Of 3,202 adults who named a favorite, the responses scattered across 1,787 distinct names, and 1,482 of those names were mentioned exactly once. The most-named creator, MrBeast, collected 316 unweighted mentions; second place had 107.
It is worth pausing on what a distribution like that means statistically. In a mature mass medium, attention concentrates: a handful of properties hold most of the audience, and the planner's problem is choosing among few. The favorite-creator data describes the opposite geometry, a market where the tail is not a niche but the bulk of attention. Roughly 83% of named favorites were named once, which means that most of the audience's stated creator loyalty lives with creators who are, by any national standard, obscure. Obscurity at national scale is not obscurity at community scale. A creator named by one respondent in a survey of thousands may be the single most trusted voice inside a fifty-thousand-person community that shares a hobby, a neighborhood, or a diagnosis.
Two implications follow. First, there is no shared creator canon anymore. A decade ago, a media planner could cover most of the relevant audience with a shortlist of names recognizable in any boardroom. A market where the top name captures under 10% of mentions and the median favorite is named by a single respondent does not work that way. Second, the audience itself is segmented in ways that resist generalization: men's favorites concentrate far more tightly, with 33% of male respondents naming one of the ten most-cited creators against 15% of women, and 94% of men's picks naming a man. The average creator does not exist. Planning as if one does produces average results.
The gender asymmetry in that concentration data is a planning fact in its own right. If a third of men's creator attention pools around ten names while women's spreads twice as wide, a brand whose target skews male can still buy reach with a shortlist, while a brand whose target skews female cannot. The survey does not explain why; it does establish that the two halves of the market have different attention structures, and any plan that treats them identically inherits the error.
What actually moves the purchase claim
Asked what makes them more likely to buy a product an influencer recommends, respondents ranked the authenticity markers far above the fame markers. Among all adults: actually using the product, 62%; seeming honest and trustworthy, 61%; having category expertise, 60%. Being very famous or popular moved 40%, and physical attractiveness 39%. Among Gen Z the spread widens: product use 75%, honesty 76%, expertise 75%, against 54% for fame and 54% for attractiveness.
Now hold that against the survey's most quoted skepticism figure: 64% of adults agree that endorsers only say good things because they are paid. A naive reading says the audience does not believe creators. The full reading is sharper. The same audience that assumes payment also reports buying, and 56% of Gen Z and millennials say an endorsement makes them more willing to try a new brand. The resolution is that the audience is not gullible or cynical; it is discriminating. It prices in the payment, then asks whether the creator demonstrably uses the product, sounds honest, and knows the category. Those are checkable signals, and the audience is checking them.
The discovery shift underneath everything
Context for why these numbers matter now: among Gen Z, creator posts are the leading way to find new products for 33% of respondents, against 37% for online search. A four-point gap between creators and search engines, on the question of how the next generation discovers what to buy, would have been unthinkable five years ago. YouTube remains the deepest creator channel by far, followed by 78% of Gen Z, and the following is heavy: 44% of Gen Z follow 50 or more creators, and 13% follow more than 300.
The heavy-following figures matter as much as the channel figures. A cohort where 44% of people follow 50 or more creators, and 13% follow more than 300, is a cohort that has normalized creator content as ambient media rather than as an occasional endorsement encounter. In that environment a single sponsored post is not an interruption; it is one item in a long, continuous feed of recommendations the viewer has already opted into. That is good news for the channel's durability and bad news for lazy executions: an audience that fluent in creator content has seen every template, and its skepticism score of 64% reflects exactly that fluency.
Product discovery is the top of every funnel the industry measures. If a third of the youngest adult cohort's discovery now runs through creator content, the question of which creators, chosen on what evidence, stops being a campaign tactic and becomes channel infrastructure, with everything that implies for how rigorously it should be run.
Trust is converging, and skepticism is rising with it
The trend lines are the survey's quietest and most consequential data. Trust in influencers among Gen Z and millennials has risen 13 points since 2019, from 51% to 64%. Trust in celebrities rose 18 points, from 40% to 58%. Over the same period, trust in friends and family fell from 84% to 78%. The gap between a friend's recommendation and a creator's has narrowed from 33 points to 15.
The simultaneous rise of the paid-mouths skepticism figure is not a contradiction. It is the signature of a maturing channel. Audiences are extending more trust to creators in aggregate while applying more scrutiny to individual endorsements. Both numbers rising together is what discernment looks like in survey data, and it predicts the next phase: trust will keep consolidating toward creators whose behavior survives the scrutiny, which is precisely the product-use, honesty and expertise cluster that drives the purchase claims.
Where fame still wins
The survey is not an obituary for fame, and treating it as one would be its own misreading. On raw favorability, traditional celebrities still dominate: the highest-ranked creator in the 90-person rating, Sean Evans, posted a net favorability of +16, behind 46 conventional celebrities led by Denzel Washington at +55. MrBeast, the most-named favorite influencer by a wide margin, scores +11. The affection gap is real.
The correct synthesis is a division of labor. Fame buys familiarity, fondness and efficient mass reach, and it remains the right tool when the job is awareness among a broad public. What the parity result says is that fame does not buy a conversion advantage, even in claimed behavior. A marketing manager who needs the nation to feel warmly toward a brand should still consider the famous face. A marketing manager who needs a specific audience to act should buy the authenticity markers, which are available at every follower tier and priced far below fame.
The synthetic sidebar
One more signal deserves a brief note, because it corrects a fashionable bet. The share of adults at least somewhat likely to follow an AI-generated influencer fell from 36% in August 2025 to 30% in September 2026, with the steepest decline among millennials, from 54% to 43%. At the same time, 39% of adults say they trust AI chat recommendations, within five points of the 44% who trust their favorite celebrities, and 9% of adults already name an AI assistant as a main discovery channel. The appetite is moving away from synthetic people and toward synthetic advisors. Brands that bet on AI influencers as a substitute for human trust are swimming against the only trend line in the survey that is going down. The more defensible reading is that audiences are sorting synthetic content into two buckets: people they follow, where they want the human to be real, and advice they consult, where they are increasingly comfortable if the source is a machine that knows the catalog. Those are different jobs, and the market is assigning them to different tools faster than most strategy decks have noticed.
What parity changes in practice
A market where small and famous creators convert identically, where attention is scattered across thousands of names, and where audiences actively check authenticity markers is a market that rewards process over instinct. Three operating changes follow.
First, brief for the markers, not the tier. If product use, honesty and expertise are what move claimed purchases, the creative brief and the vetting process should be built to verify them: does the creator demonstrably use this kind of product, does their audience believe them, do they know the category. None of those questions requires a large follower count, and a large follower count answers none of them.
Second, plan for fragmentation. With the median favorite creator named by a single respondent, coverage of a target audience is a portfolio problem by construction. The relevant skill is evaluating many unfamiliar names quickly and consistently, because the perfect-fit creator for your segment is likely someone your team has never heard of.
Third, measure per creator, per outcome. Claimed parity across tiers does not mean every small creator outperforms; it means tier is not the variable. The variance is between individual creators, which is exactly the variance a per-creator measurement discipline exists to capture. In practice this means tracking each collaboration to the outcome that matches its job, comparing creators on that outcome rather than on their audience size, and renewing or cutting on the evidence. The survey's fragmentation data makes one more demand: because the right creators are numerous and unfamiliar, the measurement system has to be cheap enough to run across dozens of partners at once, or the portfolio strategy collapses under its own administration.
Where Flonci fits
This survey is a consumer-side photograph of the principle Flonci is built on: the unit of value in creator marketing is not reach, it is a credible recommendation from a creator whose audience believes them. Finding those creators inside a market of thousands of single-vote favorites, verifying the authenticity markers audiences actually check, and measuring each creator on outcomes rather than tier, is the work Flonci exists to make systematic for marketing teams. The survey does not name Flonci and did not test it. What it does is measure, at national scale, the buyer behavior that makes that approach the rational one.
Conclusion
The fame theory of influencer marketing said that bigger audiences produce more buyers, and it priced creator tiers accordingly. A 6,283-person national survey now reports that claimed purchase incidence is identical across fame tiers, that the audience's favorites are scattered across nearly two thousand names, and that what moves people is use, honesty and expertise rather than fame and looks. Trust in creators keeps rising toward word-of-mouth levels while skepticism about paid praise rises with it, which means the winners will be the creators who survive scrutiny, not the ones who avoid it.
Fame still has its job: affection at scale. But the checkout does not care about fame, and a budget that assumes otherwise is paying for the wrong variable. The measurement era of creator marketing is not coming. As of this survey, it is being answered by the audience itself.
Research notes and sources
All survey figures in this article come from Morning Consult's State of Influencer and Celebrity Marketing report, based on a survey of 6,283 U.S. adults fielded September 17 to 22, 2026, with a reported margin of error of plus or minus one percentage point on the full sample; subgroup margins are larger. Morning Consult's report page confirms the survey's scope and sample of more than 6,000 adults. The full report is gated; the specific figures quoted here are as published in detailed coverage reproducing Morning Consult's charts, principally netinfluencer (October 21, 2026), with independent corroboration of the discovery and influencer-founded-brand figures by eMarketer. Readers should treat the numbers as claimed, self-reported behavior from a U.S. sample, not observed transactions, and trend comparisons rest on Morning Consult's repeated questionnaire since 2019.
The campaign-side comparison referenced in the text is the Humanz 2026 Israeli benchmark at benchmark26.humanz.co.il, a vendor's own measurement of campaigns run in its system, cited here as a directional cross-check rather than independent verification. Nothing in this article is a verified FLONCI client result or a commitment to an outcome. The cover image is an original AI-generated illustration, not a product screenshot.
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