GTM Sauce

Practitioner pattern · Thomas Petit (Sells consulting services and runs a paid signal-engineering workshop at App Growth Annual; works with Voyantis)

Send ad networks only the trials likely to pay, as their own event

Guest's go-to first step when paid trial quality lags; no numbers given

Workedanalytics-attributionpaid-social

What they did

When trial-to-paid from paid traffic trails other sources or its own past, run a regression on non-converting trials. Hard factors: device, OS version, language. Soft factors: onboarding answers (stated goal, intent, e.g. 'just browsing'). Keep the raw trial event unchanged; engineers add a new event (e.g. mapped as 'subscribe' or 'purchase') fired via the MMP (Adjust, AppsFlyer, Singular) or platform SDK only when a trial meets the criteria, and campaigns optimize to that. Most predictive factors across apps: age, goals, and consumer vs prosumer/solopreneur vs business. Advanced: add onboarding questions designed to create this variance. Exclusion is a last resort; skip it if trial quality is already fine.

What happened

Guest calls it the most common low-hanging fruit; no specific numbers.

In their words

Signal Engineering: Strategic Data Filtering for Better Ad Performance — Thomas Petit, Independent Consultant

Play from 54:14

David Barnard… kind of gone into and given a lot of what I would guess were are kind of more advanced signal engineering practices, but let's step back, and like once you get your data right, or believe you have your data right, what's the low-hanging fruit in signal engineering? Like, where would you say are the first kind of few steps folks should take to start changing the default mappings of how these SDKs operate by default? Like, what's the first step?

54:14

Thomas PetitSo, we mentioned that that's a what's the second step, because the first step is the is monitoring that the events are passing properly, which is not a given. But the second step for me would be either going to what we call qualified trials or filtered trials, and typically, that would be when you see that the your free trial rates are either not as good as other networks, or not as good as what they used to be. And also because you don't need huge engineering around revenue prediction, and so on, to do this,

54:43

Thomas Petitlike, so basically make a regression of, okay, let's analyze this free trials that are not converting. Sometimes, is a combination of like what I call hard factors, which are like the device itself, maybe the language, like not something the user has told me, but something that is like in the hardware itself. It's well known that the most recent device converts much better, and so maybe I'm going to filter all these very old iPhone.

Thomas Petit… "Oh, I'm just browsing around, I don't really have the intent." Like, this is basically what I'm they're telling you. And those I'm probably going to want to exclude. In this case, either you've got the platform SDK, so like, or typically you're sending it through an MMP, more rarely through like a custom API. A custom API, you send whatever you want, so like, I mean, you filter the events yourself, you send it, but it's the least common case.

1:01:08

Thomas PetitThrough the MMP, what I'm doing is actually asking my engineers, I'm going to want to add a new event. I'm not going to filter the existing event. The free trial is going to remain a free trial. Okay, if there is a free trial, and the answer to this question is this, then send it to Adjust, AppsFlyer, or Singular as being subscribe, or whatever. And then, Facebook is going to start receive it, and I'm going to have it. It works the same in the Facebook SDK, like it just can have the default configuration,

1:01:38

Thomas Petitbut then you can set up your own events. I'm not talking about custom events, it's just you can force But that's done on the engineering side. That's something the marketers are not doing. That's something that requires to open the code and actually do it. So, I know marketers are getting smarter with code these days, but And this is one thing where I call it signal engineering, because there's engineering behind it, in the sense of, I'm actually …

Thomas Petit… types of users. They would have like more pure consumer users, like full B2C, but then they would have small teams, a lot of solopreneurs, people with a Shopify shop, or influencers, who are actually they're a one-person business. Like, and there's a lot of them. If you manage to identify who are like these small business, one-person business, solopreneurs, they typically have a completely different Of course, if you're improving their business,

1:08:16

Thomas Petitbecause their post gets seen more, or the video are higher quality, or whatever, yeah, the the price sensitivity of this, because it's their business, is obviously very different from somebody who's just trying to make their photo look better. And this is one that is one of the most common things, like, so yeah, age, goals, and I don't know how to define this, like typology of users between like consumer, and prosumer, and real businesses, like and big businesses. Like, this one is a very big one.

1:08:45

David BarnardYeah. I know you talked to the MMPs a a lot, and have some limited insights into some of these ad networks. Is this something you think the MMPs and ad networks could do better? Like, should, you know, AppsFlyer and Adjust and Singular, you know, should they be building these kind of signal engineering tools into their tooling to to make this easier? And then, you already mentioned the like the bid multiplier and things like that that Meta's …

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Tags: meta, google, tiktok, signal-engineering, qualified-trials, onboarding-questions, mmp, regression