We are not a traditional agency. We price sponsorships with a documented valuation model, structure the deal around it, and measure what it returned. The reasoning is visible at every step.
Creator sponsorships are mispriced by default. We built the infrastructure to fix that.
Rates start from published industry data rather than a number someone felt was about right. Our pricing draws on Modash, Influencer Marketing Hub, Impact.com and other creator-economy sources, applied through a fixed model instead of case by case.
Creator selection runs on defined criteria: niche alignment, audience geography, engagement quality relative to platform average, and brand safety. The same checks apply to every candidate, so the shortlist can be explained rather than defended.
Valuation, negotiation, contracting, briefing and reporting run through the same internal stack. Nothing is handed between disconnected tools, which is where scope drift and delays usually start.
Every rate we quote can be traced back through the model that produced it. If you disagree with a number, you can see which input to argue with. That is a very different conversation from haggling.
Candidates are assessed against niche alignment, audience demographics, engagement quality and brand safety signals. Only creators who clear the threshold go forward, and the scoring is shown to the brand.
Pricing is produced by the SponsorCraft model: reach normalisation, base value, quality multipliers, placement rate, then any deal add-ons. Five steps, all visible, no ballpark figures.
Negotiation, contracts, briefs, revisions and payment run through the same infrastructure. Post-campaign analytics arrive as structured data you can query, not a slide deck.
SponsorCraft is the pricing model we run every deal through. It is also sold as a standalone app, so a brand or creator can check our maths against the same tool we use.
Where SponsorCraft decides what a partnership should cost, CampaignCraft measures what it did. Four layers, structured the same way on every campaign, so results can be compared rather than described.
UTMs, creator analytics access and platform-specific signals are set up before anything goes live. Attribution added afterwards is guesswork.
Metrics are read against engagement and media-efficiency benchmarks for the niche, not against a flattering baseline chosen after the fact.
Findings come back as data you can interrogate, with the method attached, and feed into how the next campaign is priced and staffed.
Sets valuation and deal structure. Every rate comes out of the five-step model, with the inputs on record.
Measures what the partnership returned across the four layers, and turns it into something the next brief can use.
Together they answer the two questions that actually matter: what should this partnership cost, and what did it do.
We represent a small roster of creators and take them to brands through the same engine we use on the buy side. Your floor is set by the model before a brand makes an offer, which changes who is anchoring the negotiation.
Currently reviewing applications from long-form YouTube creators in tech and review categories.
Apply for representation →Whether you are a brand looking for precise creator placement, or a creator ready to be represented on defensible numbers, tell us what you are working on.