The evidence underneath Applied Fandom.
Thirteen pages, one per pillar of the method. Each one answers a single question completely and carries the published work that holds the pillar up, including the strongest objection to it and the point where the evidence stops.
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Pillar 1 of 13 . Propensity over demographics
How strong is the evidence that behaviour predicts better than demographics?
Strong, and the gap has been measured. In supermarket data, demographics explained seven per cent of the variation in how price sensitive a shopper was. Watching one shopping trip beat every demographic on file. Behaviour predicts behaviour.
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Pillar 2 of 13 . The lens
Does spending longer defining the problem actually produce better answers?
Yes, and it was measured in an art studio in 1971. The students who spent longest deciding what the picture would be about produced work judged more original. Problem formulation correlated with rated originality at .54.
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Pillar 3 of 13 . The map
When can you trust what your team already knows about your audience?
Under two conditions, and confidence is not one of them. The environment has to be regular enough to contain learnable cues, and the person has to have had long practice with fast, clear feedback. Everything else is a hypothesis.
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Pillar 4 of 13 . The room
Can you trust what customers tell you about their own reasons?
Not about reasons, no. People sincerely report explanations they never used. In one study shoppers picked the rightmost of four identical items by almost four to one, and when asked whether position had influenced them, virtually all denied it.
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Pillar 5 of 13 . Fanatics
Why do the most committed fans take a brand's decisions personally?
Because they are not consuming the thing, they are using it to hold their own self-image together. Students displayed their university's colours more after a win than a loss, and the effect was strongest among those who had just personally failed.
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Pillar 6 of 13 . Enthusiasts
Does influencer marketing actually work, and if so which part of it?
The part that works is not the influence. Simulations found large cascades are driven by a critical mass of easily influenced people rather than by an elite. What moves is high arousal content, and the smallest influencers return the most.
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Pillar 7 of 13 . Casuals
What does the evidence say about where brand growth actually comes from?
From people who barely buy you. Across UK panel data on roughly 12,400 households, almost all of a brand's growth potential sat in its non-buyers and light buyers. For large brands, current heavy buyers held 17 per cent of it.
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Pillar 8 of 13 . Indifferents
How many times can you show someone the same thing before it stops working?
Fewer than most media plans assume. Repeated exposure does produce liking, but pooled across 208 experiments the effect falls from r = .365 under ten exposures to r = .069 above a hundred. Familiarity has a ceiling.
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Pillar 9 of 13 . The base
Why do launches with enormous reach sometimes produce no adoption?
Because some things need to be heard from several people you know before you will do them. In a controlled experiment the same behaviour reached 53.77 per cent of clustered networks against 38.26 per cent of well connected random ones, and spread four times faster.
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Pillar 10 of 13 . Belonging
Can an online community give people a real sense of belonging?
Only if it meets both conditions. Belonging needs frequent pleasant interaction and a stable framework of mutual care. Either one alone fails, which is why a quarterly newsletter to a global list is a mailing rather than a community.
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Pillar 11 of 13 . The portfolio
Does tailoring the message to different groups actually work?
Yes, and by less than the industry assumes. Across 57 studies and 58,454 people, tailoring produced r = .074. Against one generic message rather than against nothing, the advantage is about half what the headline suggests.
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Pillar 12 of 13 . The engine
Why don't brainstorms produce good ideas?
Because while one person is talking, everybody else is waiting, and waiting loses their ideas. Remove that one constraint in the laboratory and output roughly doubles, matching what the same people produce working alone.
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Pillar 13 of 13 . What the Cone is not
How is the Cone different from Rogers' adoption curve?
Rogers sorts people by when they adopt one innovation. The Cone sorts them by how much a whole domain matters to them. Which is why the same person is a Fanatic on one map and a Casual on another, in the same week.
How to read this set
Every page is built to be arrived at cold. No page assumes you have read another one, and every house term is explained the first time it appears.
These are other people’s findings. What is ours is what we do with them. Where the evidence stops sits on the page in the same type as the finding, and the strongest published objection is named with its author and answered rather than ducked.