A mental health app · B2C · Thomas Petit client
Tell ad networks which users reported high anxiety, since they pay far more
What they did
In their words
Signal Engineering: Strategic Data Filtering for Better Ad Performance — Thomas Petit, Independent Consultant
Thomas Petit… but now that I have the bit modifier, I can tell Facebook that the sub-25 are 30% less valuable, I don't need to do all this filtering of trials." I'm like, I prefer to hammer from both sides personally, [laughter] but sure, like it's it's kind of a potential replacement, but it's not available everywhere. The low-hanging fruit is probably going to be unqualified trials, because it's such a common factor. But it doesn't mean it's for everybody.
Thomas PetitAnd one is a hard factor, and the other one is soft factor. And the soft factor is something the user does. The most common is a question at the onboarding that somebody answers and that filters. Maybe they declare this interest and not this one. Like, I have a mental health app where when people say they have a high level of anxiety, they're so much more valuable than when they say something else. And so, we we factor this question. The next level, the very sophisticated level would be to actually add questions at the onboarding that creates this variance, and that's what you're looking for.
Thomas PetitSo, the the low-hanging fruit is looking at in a regression of the value based on questions like this. And in revenue, for example, I was working on with somebody who was like super committed, "Yeah, I need I need to do something very sophisticated with my revenue, send to the ad platform, I've got a whole team of experts of data analysts and engineers that we can put some predictive LTV back to Facebook," and so on. "Yeah, let's look at your …
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More from this episode
- Check that Meta and Google receive the same event counts as your own analyticsGaps of 30-50% are common; fix anything above 10% before touching ads
- Send trial starts, direct purchases, trial conversions and renewals as separate eventsDefault SDK mapping often lumps them all into one event; guest says fix it first
- Send ad networks only the trials likely to pay, as their own eventGuest's go-to first step when paid trial quality lags; no numbers given
- Tell Meta to value some users more or less instead of excluding themKeeps cheap under-25 reach instead of cutting it; no numbers given
- Report each user's expected value at month 13, not what they paid on day oneGuest's main advanced lever; no numbers given
- Look up each conversion's value from a server so you can change it without a releaseAvoids app releases for every price or currency change; says it makes a big difference
- Send your conversion signal within a day, waiting a few hours to see early useVoyantis showed timing matters; guest says signals after 24 hours are nearly useless
- Keep at least 10 conversion events per campaign per day before filteringUnder ~10/day optimization breaks; well above it, fewer better events win
- Report low-value users as worth less and high-value users as worth morePushes delivery toward top users but hides true ROAS; has backfired when overdone
- Send every event to every ad network, then pick a different signal for each
- Compare the value you report with real revenue by country, not just in total
- Send Google only the trials that look likely to payGoogle trials converted at ~15% vs ~40% elsewhere; the fix moved the needle
- Count a business user's yearly plan as worth 5 weekly consumer plansWorked at first; went stale after 18 months of price changes and needed fixing
- Change which events you send to ad networks, even as a young appBig uplift per the guest; details saved for a blog post
- Put all spend behind one channel and one optimization signalGrew from 0 to eight figures in two years, then had no fallback when it broke
- Let a signal specialist filter and send your ad events, and test itOne of two tests looks good, the other doesn't; not conclusive
- Treat users who rush a 30-screen onboarding in under a minute as low valueHeld for one app; another app found its fastest finishers were its best users
- Change what you report as user value when cash matters more than long-term LTV
- Sell $5-10 top-up credits on top of subscription tiers
- Send buyers to web checkout once the store fee jumps from 15% to 30%Works for them, per the guest; no numbers
- Report a $1 value for non-payers who look likely to stick around
- Report your biggest spenders as mid-value so Meta doesn't stop early
Tags: signal-engineering, onboarding-questions, qualified-trials