Built With Science · B2C · science-based fitness coaching app
Judge ads by how many trials pay, not by how cheap the trials are
Clickbait ads brought cheap trials but a huge drop in trial-to-paid
What they did
What happened
In their words
Scaling Meta Ads from zero to $100K a month — Ethan Ethier, Built With Science
David BarnardYeah. You mentioned earlier the trust side of things and how important trust is and the research that Jeremy's involved in that lends trust to the YouTube channel and to the app ultimately. But how do you think about the creatives and the way they shape the perspective of people coming into the app as far as over-promising or things that are going to get people to convert, but then maybe quickly churn or whatever?
Ethan EthierThat's a big reason why we decided to actually do Meta in-house rather than choose an agency is because we felt like we needed someone who really understood the product and was very passionate about the product and ultimately could promote the app in a way that isn't faking anything. So we wanted to make sure that whatever we put out there actually relates with what the product actually does. I'm sure you've probably seen a lot of companies that over-promise what we can actually deliver. And for us, we just wanted to make that experience from marketing to the product handoff as seamless as possible.
David BarnardAnd have you seen certain ads perform poorly based on that hypothesis or have you sometimes seen the opposite where you see an ad really take off and then you're kind of like, "It's doing really well, but I'm not sure that's the message we want to send?"
Ethan EthierYeah, definitely. We've tested a lot of ads that are more like, I guess, click baity-style or encourage a click and encourage someone to start a trial, but we can quickly see from the trial to paid that this is not the user that resonates the best with the app. So we'll see a huge drop in trial to paid, whereas maybe we think a lot deeper about who this person we're trying to target is, what their pain points are, and then how the app uniquely solves those pain points, that brings in a much higher quality of traffic. So it's definitely a balance of, "Okay, we want people to start the trial at the cheapest cost, but also we don't want just anyone to start the trial."
David BarnardWhat are you targeting against and what kind of data are you sending back to Facebook or Meta for the targeting?
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More from this episode
- Spend a year fixing trial-to-paid and retention before buying any adsFounder says it lifted the floor for every channel; paid traffic later converted at 25%
- Hype the app launch to your YouTube viewers, course members and email listA launch spike, then a steady trickle; not a growth engine on its own
- Mention the app softly mid-video, and tell user transformation storiesStory videos bring more trials than broad educational ones; old videos give steady monthly trials
- Hire clippers to post long-video clips on Reels and TikTok, then reuse winning hooksSome clips go viral; their hooks now shape new long videos
- Scale Meta ads without the famous founder: B-roll, testimonials and AI image adsScaled from zero to ~$100K/month (host figure); 25% trial-to-paid
- Spend the first month of ads just learning your paid trial-to-paid rateTook about a month to get a baseline to set the allowed cost per customer
- Build a dashboard that confirms which trials came from Meta, and send Meta your best users
- Send ad clicks to a long personal quiz on your website, not the App StoreQuiz beat direct-to-store; now gets ~90% of traffic; same quiz in the iOS app did worse
- Sell the app as a trainer in your pocket, not a tracker, at $189 a yearKept $189/year since launch; 35-40% organic and ~25% Meta trial-to-paid
- Offer 15% off each if users add a workout buddy to their plan15% of trial starts add a buddy; higher order value and better retention
- Build free calorie and macro calculators that rank in AI search and lead to the quizWorking well, founder says; tools convert slightly better than blog posts
- List every reason a page fails before brainstorming fixes, and write each test down~70% of tests fail first time; written notes turn failures into later winners
- Release new features quietly, and announce only once usage proves themFounder says it gives cleaner reads than email-hyped launches; no numbers
- Build an AI coach trained on the creator's videos that reads each user's own dataOne of customers' favorite features, founder says; no numbers
- Team up with researchers and run studies with your own app usersFounder says it adds credibility; no numbers
- Show only the yearly plan first, with a day-by-day trial timeline and reminder promiseAnnual picks rose from ~60% to 75-80%, with no price change
- Add more explanation to the pricing page to make the value clearerHurt conversion; extra text overwhelmed buyers who were ready to start
- Offer 20% off to pay now, with a toggle back to the 14-day free trialQuite negative, even with a 30-day money-back guarantee
- Make both the free trial and the pay-now discount sound goodVery strong lift after a few weeks, vs the version that shamed the trial
- Film a months-long science experiment video with real people in a rented studioOne of the year's top videos; decent but not major app conversion
Tags: meta, creative, clickbait, trial-quality, in-house