The figure is real. A June 2021 white paper reports that 76.7% of B2B advertisements scored one star out of five on a creative testing scale, and states in prose that a B2B ad is 154 times more likely to score one star than four or five.
It also measures declared emotion in a test rather than any commercial outcome, was applied to B2B using a model the document admits had never been analysed on B2B advertising, and was produced by two companies that both sell something to advertisers who believe it. None of that is disclosed anywhere in the paper.
This page gives the numbers accurately, then everything you need to cite them honestly.
What the paper actually reports
Worth getting the source right, because two documents from the same publisher get conflated constantly.
The right document. A white paper published in June 2021 by a professional network’s B2B research arm, on creativity and profit. Four named authors, all employees of that network.
Not the other one. A separate 2021 report on B2B effectiveness, covering 435 award-winning cases from two industry effectiveness databases between 2010 and 2021, contains no star-rating distribution at all. If someone cites that one for the 77%, they have not opened it.
The prose version, verbatim. That 77% of B2B creative is 1 star, supporting the contention that creative is in crisis; that powerful creative does exist but is exceedingly rare; and that only 0.5% of 1,700 B2B ads scored 4 to 5 stars, or put another way, a B2B ad is 154 times more likely to score 1 star than 4 to 5.
So the 77% is the paper’s own rounding of 76.7%, not a press distortion. On that narrow point the citation chain is clean, which is rarer than it should be.
The sample, verbatim. A custom analysis of 6 B2B categories with 1,700 ads, drawn from a testing database described as holding more than 40,000 ads across all sectors, predominantly consumer.
What the document does not disclose. The countries. The collection period. The number of human respondents. For a study whose entire output is a percentage derived from human responses, the absence of a respondent count is a real gap.
This is where the claim and the method part company, and it is not hidden. It is simply not mentioned in the same breath as the percentage.
The protocol. Respondents are shown an advertisement and asked to indicate how they feel about it. They select one of seven basic emotions, or neutral, from a pictorial scale, drawn from a well-known psychological framework of universal emotions.
What that produces. A measure of declared emotional response to an ad viewed out of any purchasing context. No respondent buys anything. No commercial outcome is observed.
The scale. 1.0 is described as Low, 2.0 Modest, 3.0 Good, 4.0 Strong, 5.0 Exceptional.
What the testing company claims for it. That the star rating predicts long-term brand growth based on an ad’s creative quality, calculated by measuring emotional response.
The word doing the work. Predicts. Not measures. The rating is an input to a model, and the model is where growth appears.
Why this matters for a B2B advertiser. A B2B purchase involves a buying group, a procurement process and a months-long evaluation. Whether an individual felt an emotion while viewing an ad in a testing panel is a long way upstream of that, and the distance is not addressed.
The growth numbers are modelled, not observed
The most quoted consequence of the 77% is that most B2B advertising drives no growth. That specific claim comes from a model, and the model has an assumption in it.
The published relationship. 1 star drives 0% market share growth. 2 stars 0.5%. 3 stars 1.0%. 4 stars 2.0%. 5 stars 3.0%.
The assumption attached. Those figures assume 10% excess share of voice in the category. Change that assumption and the growth numbers change with it.
Where the relationship comes from. A general database of more than 40,000 advertisements, overwhelmingly consumer.
The sentence in the document that should be quoted more often. That there was no specific analysis of B2B ads before this study. The star-to-growth relationship was therefore established elsewhere and applied to B2B, not derived from it.
What that makes the headline conclusion. A consumer-derived model, applied to a B2B sample, generating a B2B growth claim that was never validated against B2B commercial results.
What would settle it. Following those 1,700 advertisers and observing what happened to their market share. That study does not exist, and no version of it is published.
A percentage that changes when the sample changes is a description of a sample, not a property of B2B advertising.
January 2021. Trade press reported 1,600 B2B ads shown to a sample described as 6 million people worldwide over the past four years, with 75% scoring one star or less. This is the only version that gives a panel size, and it is not the version in the white paper.
June 2021. The white paper: 76.7%, on 1,700 ads across six categories, with no panel size given.
August 2022. A representative of the same institute, speaking at a conference, described a most recent analysis of over 600 B2B ads in which 71% scored one star.
What that spread tells you. The database is live and the percentage tracks whatever is currently in it. Three numbers, three samples, eighteen months.
How to cite it honestly. As roughly three quarters of tested B2B ads scoring lowest on one company’s emotional response scale, in samples of several hundred to a couple of thousand, between 2021 and 2022. That is defensible. “77% of B2B ads fail” is not the same statement.
And what does not change across all three. The direction. Whichever sample you take, the overwhelming majority score at the bottom. The finding is unstable in its second digit and robust in its shape.
Not a hidden conflict. An undisclosed one, which is different and in some ways worse.
The two parties. A professional network that sells B2B advertising inventory, and a company that sells creative pre-testing. The white paper is a joint production.
What the paper recommends. Investing more in creative that is tested and reworked continuously. That recommendation is the pre-testing company’s product, and the growth it promises is delivered on the network’s inventory.
What the paper discloses about this. Nothing. Searching the full text for funding, sponsorship, disclosure, limitation or caveat language returns no results. There is no statement of interest and no statement of methodological limits anywhere in the document.
How far the pattern extends. The best-known B2B split of the long-and-short budget research, which produces the 46% brand and 54% activation figure for B2B, was commissioned by the same network. One of its executives described the motivation directly: seeing an opportunity to popularise the researchers’ recommendations among their client base by commissioning a B2B cut of the data.
And the 95:5 rule. Its author, an academic at an independent institute, notes on his own page that he wrote it for the same network in 2021, thanking two of the same executives for prompting him. He also writes that the 95% figure is not meant to be a precise rule and that it is a heuristic to get the idea across.
The honest summary of the field. The underlying case databank is genuinely independent, built from award submissions since 1980. Every B2B analysis of it that anyone cites was commissioned by a company selling B2B advertising.
Being sceptical about the evidence is not the same as disagreeing with the conclusion.
The observation matches what you can see. Open a feed and look at ten B2B ads. Most are indistinguishable, most name a category rather than a customer, and most would work equally well for a competitor with the logo swapped. You did not need a star rating to notice this.
The mechanism is plausible. An ad nobody remembers cannot influence a purchase considered months later. That does not require an emotional response scale to be true.
The advertisers behind the tested ads chose those ads. So the 77% is also a measurement of what B2B marketing departments approve, which is a governance finding as much as a creative one.
Where I would not go. From “most B2B ads score low on an emotion test” to “your ads produce no growth”. The second statement needs the modelled link, and the modelled link was never validated on B2B.
The reasonable posture. Treat the finding as a strong prior that your advertising is more forgettable than you think, and then test that on your own account rather than accepting a percentage as a verdict.
Two checks worth more than the star rating
Both are free, both take an afternoon, and neither requires buying a test.
The logo swap test. Take your ad, replace your logo and name with a competitor’s. If it still works, it is not your ad. This catches the single most common failure in B2B creative, and it catches it in seconds.
The five-second recall test. Show the ad to ten people outside marketing for five seconds. Ask two questions: who was that from, and what were they offering. If most cannot answer both, distinctiveness is your problem, not budget.
Why these are defensible. They test the two things everyone agrees are necessary: that the ad is attributable to you, and that its offer is comprehensible. No model, no scale, no assumption about excess share of voice.
What to measure after that. Cost per meeting held. If the fixed version of the ad does not move that, the diagnosis was wrong and you have lost a week.
And the trap to avoid. Buying a creative testing subscription because a paper published by a creative testing company said your creative is bad. That may still be the right purchase. It should not be that paper that decides it.
Attributable to you, and comprehensible. No model, no scale, no assumption about share of voice. Source : Method (2026)
A June 2021 white paper reports that 76.7% of 1,700 B2B ads scored one star on a creative testing scale. The figure is real and published. What it measures is emotional response in a test, not any commercial outcome.
What does the star rating actually measure?
Declared emotion. Respondents are shown an ad and select one of seven basic emotions, or neutral, from a pictorial scale. The rating is calculated from those responses.
Was the scale validated on B2B advertising?
No. The document itself states that no specific analysis of B2B ads existed before this study. The relationship between star rating and market share growth comes from a mostly consumer database and was applied to B2B.
How large was the sample?
1,700 ads across six B2B categories, drawn from a database of more than 40,000 ads. The number of countries, the collection period and the number of human respondents are not disclosed in the document.
Has the figure been consistent?
No. The same institute has published 75% on 1,600 ads in January 2021, 77% on 1,700 ads in June 2021, and 71% on 600 ads in August 2022. The percentage moves with the sample.
Who funded the research?
It was produced jointly by a professional network that sells B2B advertising inventory and a company that sells creative pre-testing. The document carries no disclosure of this, and no statement of limitations.
Does that mean the finding is wrong?
No. It may well be broadly right, and the underlying observation that most B2B advertising is forgettable matches what anyone who looks at a feed can see. It means the number should be cited with its provenance, not as settled fact.
So what should I actually do about my ads?
Judge them on whether anyone can tell who they are from and what is being offered, then on cost per meeting held. Both are available to you, and neither requires a star rating you would have to buy.