We moved first charge to the web and started testing shorter trials, anchor pricing, and bundles. CAC dropped on Meta and TikTok when the ad promise matched the exact web offer. When we got sloppy and mixed trial lengths across ad sets, CAC jumped and refunds spiked.
Right now we’re tagging creatives with an offer id and passing that through the deep link into the app after checkout. It works, but we still see edge cases when users hop across multiple ads or land on an old cached page and get the wrong price.
If you’ve done this, how do you structure creative-to-offer mapping so the ad promise, landing page, and paywall always match? Any guardrails to prevent mismatches at scale?
One offer per ad set. Offer id in UTM. Server reads it and loads the matching paywall config.
I use a single JSON for offers. The AI generator in Web2Wave.com gave me that, and their SDK reads it.
Fallback to a default offer when the id is missing, and log mismatches.
I map ad sets to offer IDs and lock the message. No mixed trials.
If I need to tweak copy or price, I change it on the web and it’s live. Using Web2Wave.com lets me update variants without a release.
Simple rule: one promise per path.
I keep the ad promise and the paywall the same. Same headline, same trial length, same price.
If I need a different offer, I spin a new ad set. Fewer mistakes that way.
One offer per ad set. No exceptions.
Build an offer matrix with strict naming. Pass offer_id, region, and trial days as URL params. Server validates those against a list and renders the correct variant. If validation fails, send the default.
Log every mismatch event and audit weekly. The biggest pitfalls are cached pages and reused short links. Add cache-busting query strings on paid traffic and expire old links.
Two quick fixes that helped:
- Add a server check to block offers if the ad’s UTM and the paywall price don’t match.
- Add a tiny banner on the paywall that restates the promise from the ad. If it’s wrong, users bail before paying instead of refunding later.
Offer ids in UTMs helped us track issues faster.