Approach

A mixture of analysis. Not a black box.

We don't believe AI replaces taste. We believe it makes taste defensible — by widening what one human team can see, and forcing every claim to be backed by something more than a hunch.

01 — The stack

Four layers, every brief.

No single layer makes the call. Together they constitute a recommendation we'll defend on the record.

L · 01

Audience graph

We model the actual audience behind every creator on the table — not the follower count, but the people. Demographics, geographies, behavioural clusters, the overlap with your existing customer base and your competitive set. Where the audience lives in the network, who they listen to, and who they don't.

InputsFollower-level data · Comment graphs · Cross-platform identity signals · First-party CRM overlap (where licensed)
L · 02

Brand affinity

Years of a creator's output read by language and vision models — tone, themes, recurring values, what they've endorsed, what they've quietly declined. Mapped against the brand's own corpus — guidelines, comms history, competitive positioning. We find the fit no one was looking at, and surface the misfit no one wanted to admit.

InputsMultilingual NLP · Visual classification · Brand-corpus embedding · Competitive-set mapping
L · 03

Commercial signal

Where the audience converts and where it doesn't. Historical campaign data, observed purchase intent, search and price elasticity reads. The unsexy work of moving from "they like this" to "they buy from this person, in this format, at this price, in this window".

InputsCampaign performance · Search trend reads · Sentiment-to-conversion modelling · Pricing benchmarks
L · 04

Cultural read

Where the model stops and we begin. A creator who's about to break through, a category that's about to cool, the post from six months ago that everyone forgot but the internet didn't. Brand-safety nuance. Trend judgement. The human call that turns a "good fit" into the right move now.

InputsEditorial judgement · Trend tracking · Risk & reputation review · Client-side context we don't try to model

→ Every recommendation comes with the working — the signals, the weights, the dissent. If a layer disagreed with the final call, you see that too. Black-box answers don't survive in a boardroom, and shouldn't.

02 — Principles

Six rules we don't break.

01

Signal over reach.

A small audience that converts is worth more than a large one that doesn't. We work to that arithmetic.

02

Models inform. People decide.

No campaign, no contract and no public statement is signed off by a machine.

03

Show the working.

If we can't explain why we recommended something, we don't recommend it. Plain English, defensible reasoning.

04

The creator is the asset.

We protect voice, audience trust, and long-term value over short-term campaign yield. Always.

05

Honest about measurement.

Some of this work is straightforwardly attributable. Some isn't. We say which is which.

06

Long horizons.

We're trying to build creator businesses and brand relationships that outlast a platform cycle, not a quarter.

A model can rank a thousand creators. It cannot tell you which one to bet on. That, still, is our job.

Bring us a brief

If this is the methodology you've been trying to articulate in your last three agency reviews — we should talk.