GTM Sauce

Sizzle AI · B2C · AI learning app

Add columns showing each ad's step-by-step drop-off from install to paywall

Surfaces ads and journeys with 10x higher purchase conversion

Workedanalytics-attributionpaid-social

What they did

Set up ads-manager columns in funnel order: install, registration, engagement events, then each paywall step, plus custom metrics expressing step-to-step conversion as percentages so ads and ad sets can be compared directly. When scanning ~20 ads for outliers, look for higher step conversion and lower drop-off, not just cost per purchase. Same view by in-app journey: users who start with a particular product convert ~10x better than those who roam the app.

What happened

Makes the top-10% outliers visible; some ads, targeting and in-app journeys show 10x differences in conversion to purchase.
Stage
growth

In their words

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

Play from 23:45

Yev Marusenko… 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 then different paywall steps. So, I want to make sure to see that so you know what the drop-offs are just so when I'm looking at 20 of these looking for outliers, I see which ones have higher percentage of conversion, lower drop-off, and actually making custom metrics, making sure that it's percentage-wise comparison as well.

24:20

Yev MarusenkoThat way, it's much easier to split test. And then when I was talking about the TikTok example, where there's creative, but then there's many different ad sets with different targeting, knowing which one is leading to lower percentage of drop-offs, just so it's much easier to tell on what the percentages of like from one step to the next, from the install, using the app, different steps of the paywall, being able to measure that, because that's where you end up seeing outliers, like these top 10% where from going into the purchase, there's these 10X differences on some of the ads, some of the targeting, depending on the journey they took inside of the app.

24:52

Yev MarusenkoSo, there's like different types of products, and some of them start using a particular product and end up purchasing, and it's 10 times higher conversion than kind of just like roaming through throughout the app.

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Tags: custom-columns, funnel-metrics, ad-reporting