GTM Sauce

Sizzle AI · B2C · AI learning app

Switch ads off and on to measure real sales lift; compare every attribution source

Real purchases usually about double what the ad platform reports

Workedanalytics-attribution

What they did

Compare in-app analytics and own database with platform-reported numbers. Run lift studies: switch ads off completely to see how much sales fall, then back on. Compare 1-day vs 7-day windows (at least 10% of purchases arrive later), SKAN vs platform-reported (another 10-20%), and App Store Connect analytics by source (another 10-20% spillover from people who saw an ad then searched the store). Use the gap to justify scaling ads that look marginal in-platform.

What happened

Real purchases are usually about 2x reported; the extra confidence lets him scale ads further.
Stage
growth

In their words

Yev Marusenko - How I Grow Viral Apps to 1M+ Downloads (just copy me)

Play from 22:44

Yev Marusenko… what's attributing or not, and then versus like everything we're tracking inside just our own database and trying to confirm. What I do is just making sure looking at all of the different attribution types of like metrics and periods. I know there's a lot of data and then like gut feeling that if you run a ad and you have 10 purchases reported or 100 purchases, what does that actually mean? Are is the real data where it's like double that?

22:44

Yev MarusenkoSo, I think there's like a good insight where it's usually like double that, and then I'm doing like different lift studies where I completely turn off ads to see how much sales go down, and then I turn them back on to see how much sales go up to get estimates of these lifts. And then um the same thing, when I'm looking at some of these ads, time period for any ad, knowing how many are coming in right away, kind of like 1 day versus 7 day or beyond, to know that at least 10% of the purchases are coming in later that aren't relatively instant. Then also looking at SKAN versus uh what's other reported purchases, knowing that another over 10 to 20% of the purchases are coming in through these other attribution methods.

23:19

Yev MarusenkoAnd then I'm actually in Apple Connect looking at analytics like based on platform, knowing that another 10 to 20% of purchases are coming in from spillover types of attribution that are happening. Like somebody sees an ad, and then they just go search for it, and then they like end up like installing and and purchasing. So, there's all of these different attribution sources that then give me more confidence on being able to scale ads because I know what's being reported in the actual ad. So, this is making sure that you have some sort of funnel steps view.

23:45

Yev MarusenkoNot only like on onboarding, you might know like how many people you're dropping off at each different step, but within the ads as well. Whether it's as simple as setting up the columns, but just seeing that order of how many people you have from install, there's like I have like hundreds of ads, actually like thousands of ads. I'm just kind of showing a very like refined example. From like install, registration, kind of different engagement, and …

Get tactics like this every Monday

New tactics from the week's founder interviews, each linked to where it was said.

More from this episode

Tags: meta, tiktok, app-store, attribution, lift-test, skan, attribution-windows