The post-attribution playbook: Eric Seufert on fixing measurement and scaling growth

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What’s the best way to optimize your ROAS when marketing your app? This is the perennial question in app marketing, and there’s no one right answer. But people like Eric Seufert can help you find the right approach for your app business.

Eric is a quantitative marketer, media strategist, investor, and author who advises app businesses on the latest trends and tools in app marketing, helping teams optimize their ROAS and business growth. On this week’s episode of Sub Club, we asked Eric your burning questions about how to effectively measure ad performance, avoid common pitfalls in app marketing, and interpret the results of creative testing.

How risky is it to put 80% of ad spend into Meta and Google?

You may think putting most of your ad spend into one or two big ad channels is risky, but according to Eric, diversity for diversity’s sake isn’t necessarily a good thing. “I think people feel compelled to diversify because they have this sort of abstract notion that being totally concentrated in one or two channels is a bad thing,” he said. “And yeah, there’s risk there, but the reality is that diversifying adds a lot of overhead.”

Eric’s advice? If you want to diversify your ad spend, do so strategically. Don’t just optimize for ROAS, but for spend-adjusted ROAS. And follow a waterfall method to allocate your ad spend:

1. Max out the biggest channel until it hits your ROAS threshold. 
2. Max out the second-biggest channel (which has a smaller spend limit) until it hits your ROAS threshold.
3. Max out the third-biggest channel (which has a smaller spend limit) until it hits your ROAS threshold.
4. And so on.

This approach minimizes overhead and complexity, while allowing you to diversify across ad channels with less risk.

What’s the biggest pitfall you see across growth teams right now?

According to Eric, the biggest problem facing growth marketing teams today is what he calls measurement disorganization. “The thing that I see most commonly is a very chaotic approach to measurement, just lacking any sort of coherency,” he said. “I see people using competing tools, essentially not really knowing which one to trust or how to interpret the output of one relative to the other, [or people] having a bunch of tools that aren’t working in concert — they’re just a couple different data points, I don’t know how to interpret them as an ensemble.”

Unfortunately, the solution for this problem isn’t an easy one: it involves sitting down with stakeholders and coming up with a measurement plan that satisfies everyone. As Eric puts it, “Your measurement system is essentially the heartbeat of the company — everything flows from that, and you really need to be doing it correctly and in a way that … everyone understands and appreciates.”

How do you balance speed versus accuracy and make confident decisions with incomplete data?

Eric’s advice on this one is pretty straightforward: “The way I approach creative testing is trying to identify losers as quickly as possible. The winners take time to prove out, but the losers are pretty quick to prove out,” he said. So what does that look like?

Especially in the early days after launching an app, it’s impossible to know terminal LTV or incrementality — so the best approach is to slowly, methodically increase your ad spend in the right places as you gather more data. If a certain creative is obviously not a winner, kill it immediately (at best, it will perform at the average, but it won’t grow your ad spend), and let the apparent winners age to see how they perform over time. Track ROAS for each cohort at day 20, 30, 50, and so on, and increase your budget frontier as it makes sense. This data-driven approach takes the guesswork out of ad spend decision-making and lets teams iterate quickly on what works.

Conclusion

These are just a few of the great questions listeners submitted. To hear our full conversation with Eric, listen to the full episode wherever you get your podcasts.