98.4% Decrease Growth Costs

Jointly is a VC-funded CannaTech startup out of Los Angeles, CA. The platform they built helps consumers understand what type of cannabis they should use for their specific use case. With AI, it assesses the consumer's goals, such as sleep, reduce anxiety, focus, etc. and provided them the best recommendation possible. However, while Jointly wasn't a cannabis company itself, they face the same restrictions on advertising and marketing that a dispensary would. They needed a creative solution for marketing at scale and at a much lower cost.

While Jointly is simply a tech platform, they couldn't advertise on any platform without quickly getting shut down due to the fact "cannabis" was part of their branding. That led them to incredibly high costs per new user and even that wasn't stable. The company had tried many different tactics to get their name out there, but they were all too expensive to sustain. Jointly had maxed out it's growth at just 3,000 users. Without simply raising million more in funding, the startup was at a crossroads. How would it scale without being able to advertise?

Within 3 months, Revenue Institute decreased the acquisition cost of a new user from $83 down to $1.35. The defining solution, proven through R&D in tandem with Jointly, was a mix of new digital properties and advanced AI analytics. Jointly's ads would get flagged because their main website, as well as their iOS and Android Play listings had the word "cannabis" on nearly every page. However, if a landing page was "cleansed" of that word, ads would run fine. After a series of tests, Revenue Institute helped build micro-site on a new domain that enabled the company to run ads at scale. However, the next problem was attribution.

Jointly was running ads to consumers to download their app. To send someone from a Meta ad to a landing page and then to the iOS store wrecked any chance at attribution. With the data team at Revenue Institute, the company developed an AI, inference based attribution model. With a simple pixel on a landing page, the new algorithms would digital fingerprint a visitor and track the click. Attribution fell off when they proceeded to download the app from Android Play or iOS. However, connected with the Jointly app itself, the algorithms could analyze the digital fingerprints of every new sign up, as well as date, time, etc. and map it back to the previous visitor captured with 93% accuracy.