How Reframe Scaled to $10M+ ARR

Approached small online communities that already helped people cut back on drinking (e.g. groups for moms) with the pitch: instead of only giving your members strategies, here is a science-based tool with everything they need. Not all said yes; a few did, and persistence mattered. Partner communities got discounts for their members, and some co-created programs for their community with Reframe under a revenue share. At the time (2020-21) communities and influencers were a largely untapped channel.

After recovery centres passed, the team went direct to the community: posted on Reddit and talked about the app in other places. The early product was a few tools packed together, which the guest says was the wrong form factor.

With a research-based product built with Emory researchers, the team pitched people in recovery centres on giving it to patients going out. Initial reactions were very positive, but when the pandemic hit in early 2020 the centres tabled everything.

In mid-2021, against warnings that the existing community would leave, the founders moved Reframe from 'quit drinking' to 'cut back' (drinking is fine if you choose it). They made the message consistent end to end: changed ads, onboarding, the core product loop and the program, checked with their research partners that the tools still applied, and rebuilt everything from first point of entry to the program in about a month.

Launched as 'Digital Sponsor', a name that spoke directly to people who had tried AA, so little explanation was needed. Later renamed to Reframe because the name would not scale. Guest adds that names rarely make or break an app.

Early adopters were very passionate (20+ got Reframe tattoos) and posted about it to friends; friends noticed the change and asked how. Without knowing long-term unit economics, the goal became 'get as many users as possible' because each user referred others. Revenue was not enough for a big push, so they raised funds to spend on marketing (expanding into Meta and similar channels) and on R&D.

Founders actively reached out to users and lined up interviews constantly: 500+ users, more than 10-15% of the early user base. Both co-founders also personally responded to everyone who wrote in, spending a large part of their time on support. Guest warns that the most vocal users don't represent the whole audience, so combine talking to users with judgment and usage data.

Showing new users Reframe's whole toolkit didn't land. Instead users start with the drink tracker; a few weeks in they are shown a couple of tools, and once they use one or two, more tools follow. The aim is one habit at a time; asking for several tools on day one leads to zero, and 'I'll come back tomorrow' means they won't.

Knocked on many doors and recruited researchers from Emory University in Atlanta to design the toolkit and check that tools still fit after the cut-back repositioning. Research methods assume people show up and do the work, so Reframe added the engagement layer itself. Reframe now has more people flowing through it than research labs combined, and builds on that data.

Reframe had kept prices low to stay accessible, but needed more revenue to fund a growing team and services (users were also spending far more on drinking), so it raised prices. Guest's rule: if conversion holds steady as price rises, you are undercharging; past some point, higher prices trade users for revenue.

Early on Reframe cut its price to about a third (also said 40%) of the launch price because it lacked subscribers. That brought users but lower commitment and engagement. They later returned to the original price, which worked much better. Guest advises big moves until results stop swinging, then smaller steps; when you think you're undercharging, make a bold leap.

To cover other dimensions of 'peak human condition', the company built and pushed out several more apps while the team was small. Guest says focus on one thing matters; only with a bigger team can they now support multiple apps.

Reframe's store name ('Drink Less and Thrive') leads with brand and mission rather than keyword optimization; the guest says the 'Thrive' keyword is not useful for search and that they never treated ASO as a main lever.

Host cites an App Masters client in the iPad space making about $2M a year, $1.4M of it on iPad. He says ASO is somewhat easier on iPad and most kids have iPads, so kids' apps should think through the iPad version.

An App Masters client with an app similar to a flashcard app (different industry) tried to make a subscription model work. Host recommends a lifetime offer or unlocking decks one by one for this kind of app.

One of the host's apps ranks #1 for its primary keyword in the Netherlands with the same search score as the US, but downloads lag the US. He is A/B testing different, lower prices there.

After a previous guest (Chris) talked about icon testing, the host started A/B testing app icons on a couple of his apps. Recommends icons that clearly show the category (e.g. a sleeping baby for a baby sleep app) rather than being too different.

For each app's ASO, the host picks 6 to 10 different keywords, treats each as a hypothesis, and rotates between them. Next step is localization into markets with search volume. If ASO doesn't work, run Apple Search Ads to get rankings and test the funnel.