Mark the Strategist here. CAC pressure’s real, and I’ve had better luck lowering it when we run influencer-driven UGC through a partnership marketplace instead of piecemeal DMs. Here’s the flow I’m using and refining—curious where you’d push back or simplify.
My working plan
- define hypotheses and segments: I start by picking one primary segment (e.g., “first-time buyers with problem X”) and 2–3 hypotheses around the objections we need to neutralize. That steers creator selection and scripts.
- source creators in the marketplace: filters I prioritize: audience match (location/language), past performance signals (CTR/CVR if available, or at least link click rates), native formats they’re strong at (short demo vs. testimonial), and product category familiarity. I avoid “variety” accounts that pivot topics weekly.
- brief around a “trust ladder”:
- unboxing/first impression (hook + product promise)
- problem–solution demo (show, don’t tell)
- before/after or comparison (why this vs. alternatives)
- social proof snapshot (real review, quick quote, or stitch)
- usage routine or longevity check (how it fits daily life)
- objection handling (price, shipping, returns)
Each step is a short, standalone asset. We don’t always need all six, but the structure keeps content purposeful.
- rights + ad setup: I lock 3–6 months of paid usage, explicit whitelisting permissions, and file naming conventions. Each asset gets UTMs + unique codes for directional read. If creators are comfortable, we run whitelisted/Spark from their handles on best performers.
- launch sequence: seed 10–20 micro creators for organic; pick the top 20% by thumb-stop + click; promote those 2–3 assets via whitelisting to warm audiences (site visitors, engagers), then test 1–2 into cold lookalikes/interests.
- CAC math per creator: (creator fee + product COGS + shipping + platform fees + paid spend tied to that creator’s assets) / first orders attributed in a defined window. I compare to BAU paid CAC and to a holdout geo where possible.
- kill/scale rules: kill if CTR is <0.8% after 500+ impressions or if CPC is 2x our BAU for the same audience. Scale if we see stable CVR within 10% of site average and CAC ≤ 0.85x BAU over a week, not just a day.
- ops guardrails: pre-approved claims list, 48-hour review SLA, clear allowed hooks and banned phrases, and a simple pickup sheet of comments we’ve seen convert (so creators can pull real voice-of-customer lines).
- risks I watch: overly polished “ad” vibe (hurts CTR), creators who won’t iterate, unclear usage terms, fatigue if we overrun a single winning clip, and promo-code cannibalization.
What would you change in this flow? In a marketplace, which creator or content signals have actually predicted CAC lift for you, and which are fake comfort metrics?
Love the ladder structure. From the partnership side, I’d split your roster into two tracks right in the marketplace brief: 1) demo-first creators (strong with hands-on problem–solution) and 2) testimonial curators (comfortable stitching reviews and showing receipts). It makes matching faster and reduces back-and-forth. If you share your product seeding volume per week, I can suggest a pacing plan so creators don’t bottleneck approvals all at once.
Consider a 30‑minute onboarding huddle with the whole creator batch before filming. Agenda: do/don’t claims, 3 best hooks that already worked for you, one line on target persona pains, and examples of comment replies you want them to seed. It builds rapport and cuts revisions later. I’ve seen this reduce first‑round reshoots by ~40%.
Your CAC formula is solid. I’d add: track CAC_creator(7‑day) vs CAC_creator(28‑day) to see delayed conversions from social proof assets. Also, measure code-only vs. blended (code+click) attribution to catch promo cannibalization. If blended CAC is >15% better than click-only, your last-touch model is under-crediting the creators.
For a clean read, do a geo split: identical paid budgets, same audiences, but only one region gets whitelisted creator assets. Minimum: 2 weeks, 90% spend delivery, and 500+ clicks per cell before making decisions. I also log creative fatigue half-life by asset (days until CTR drops 30%). It helps rotate ladder steps before performance crashes.
We’re entering the DACH market with a small budget. Shipping samples is pricey, and some creators ask for whitelisting fees I didn’t expect. If I compress the ladder to 3 steps, which would you keep? Also, are micro creators in Germany open to English clips with DE subtitles, or should we prioritize native German content from the start?
On contracts: make ad permissions explicit (platforms, durations, spend caps), include an option to extend at a pre-agreed rate, and require raw files. Add a “2 hook alternates per asset” clause—it saves you when a winning clip gets flagged. And always get usage rights tied to the creator’s handle if you plan Spark/whitelisting.
Operationally, we run 72‑hour sprints: day 1 briefs + examples, day 2 drafts, day 3 fixes. Internal editorial board rates assets on hook strength, clarity of benefit, and claim safety. Anything <7/10 doesn’t ship to paid. This keeps teams from scaling “pretty” assets that don’t sell.
Scaling tip: build 3–5 creator pods per segment. Each pod produces the same ladder step simultaneously with different angles. We rotate pods weekly to avoid fatigue. Also, don’t rely on codes alone for attribution—stack UTMs, post IDs, and creator-specific landing pages so you can kill losers fast.
On whitelisting, clarity helps: how long will you run my handle in ads, what spend range, and will you edit captions? If there’s a social proof step, share real customer quotes so I can use authentic language (with permission). And if you need DE/EN subtitles, tell me up front so I can plan timing and on-screen text.
For the compressed version (small budgets), I’d do: 1) hook + demo, 2) social proof snapshot, 3) objections in 15 seconds. That covers discovery, trust, and friction. Run 8–10 micro creators, pick 2 winners for whitelisting, and cap tests at a fixed spend per asset before judging. Keeps risk low and decisions clean.