Know the reaction
before you ship it.
Put a message in front of a real audience before it exists. Every cohort is compiled from accounts that already posted, followed and reacted — so the split you get back is anchored to behaviour, not to a demographic guess.
Stimulus
“A 30-second spot for a carbon-neutral grocery range, priced the same as the regular one.”
Would you stop scrolling?
n=942 · 95% CI- Would stop scrolling41 [34–48]
- Would keep scrolling34 [28–41]
- Would comment16 [11–22]
- Would share it9 [5–14]
Where the cohorts disagree
- us-10High-reach TikTok entertainers52%
- us-33Budget-conscious home cooks38%
- us-67Healing & recovery creators24%
Built from
- 4
- platforms reconciled
- 197B
- recorded follow edges
- 3.3M
- people resolved
- 485
- cohorts compiled
- 485
- persona cohorts
- each ≥100 accounts
- 265K
- real accounts
- resolved, not sampled
- 311K
- recorded reactions
- observed comments
- 9.9K
- voice exemplars
- indexed for tone
The difference
Most synthetic audiences are invented. Ours were observed.
The network is a guess
Simulation platforms generate a plausible-looking graph and populate it with personas inferred from demographics — so the personas answer like the stereotype of a segment rather than the segment itself.
Ours was recorded
Every cohort is compiled from accounts that exist, connected by follows we observed, described by content they posted — with the counts attached.
Which makes it checkable
Because we hold longitudinal history, a prediction can be scored against an outcome that already happened. Backtesting is structurally unavailable to a platform whose graph was generated.
Nodes placed on a grid and wired at random. Everyone has the same number of connections, so there are no communities for an opinion to travel through — and nothing to check a prediction against.
Follows we recorded. Dense clusters, a heavy tail of high-reach accounts, and a handful of bridges between communities — the structure that decides whether a message spreads or stalls.
How a study runs
Four steps to a distribution you can defend.
typical run · 40–90s
- 01
Define the audience
Describe who you need in plain language, or filter the catalog directly by market, reach and topic.
- 02
Hydrate the cohort
Each persona loads its evidence pack: observed topics, behavioural distributions, and verbatim voice.
- 03
Propagate
Reactions spread across the real follower graph over successive rounds, so opinion shifts the way it does in the wild.
- 04
Read the split
A distribution with confidence bands and representative quotes — not one confident sentence.
The substrate
What every cohort is actually made of
People resolved across platforms
TikTok, Instagram, YouTube and X reconciled to one human with several handles. Cross-platform identity is the part competitors cannot buy, and it is what makes a cohort a group of people rather than a list of accounts.
Recorded reactions
Real comments on cohort members' content, so a persona knows how its audience responds.
Verbatim voice
Exemplar captions per cohort, semantically indexed, so tone is retrieved rather than imagined.
US accounts
The deepest market coverage we hold, matched at cohort level rather than estimated.
Evidence packs
Cohorts carrying a full behavioural pack: distributions with counts, provenance and stated limits.
What we will not claim
A simulation is worth exactly what its validation is worth.
Accuracy figures are easy to produce and hard to earn. Ours are reported against trivial baselines and held-out splits, with the nulls shown at the same prominence as the wins. Where a cohort is thin, the platform says so on the cohort.
A claim, reported our way
held-out split · n=1,204 · baseline 0.50
- 01Every cohort is an aggregate of at least 100 real accounts — never a single person, and never a conversational twin of one.
- 02Packs state their own limits. Creator cohorts are labelled as skewing toward performers, because they do.
- 03Personas describe genuine splits with proportions instead of collapsing to one confident answer.
- 04Predictions are scored against outcomes we already recorded, not only against a control we designed.
Test the reaction before you commit to the decision.
Bring a message, a concept, or a campaign. Get back the split, the reasoning, and the confidence band — in the time it takes to brief an agency.