Case Studies/Jointly
Cost Reduction

98.4% Decrease in User Acquisition Cost

$83 → $1.35

Cost Per User

98.4%

CPD Reduction

66.7×

User Growth

93%

Attribution Accuracy

Context & Challenge

Jointly is a VC-funded CannaTech startup building AI-driven cannabis recommendations for consumers - matching use cases like sleep, anxiety, or focus to the best products. While not a cannabis company itself, Jointly faced the same advertising restrictions as a dispensary. They needed a creative, scalable marketing solution at dramatically lower cost.

The Challenge

Jointly couldn't advertise on any major platform without getting flagged - the word 'cannabis' appeared throughout their website, iOS listing, and Android Play listing. This led to extremely high and unstable cost per new user. The company had tried multiple tactics but none were sustainable. Jointly had maxed out at just 3,000 users with a $83 cost per download. Without raising millions more in funding, the startup was at a crossroads - how to scale without being able to advertise.

Our Solution

Within 3 months, Revenue Institute decreased the acquisition cost of a new user from $83 down to $1.35. The solution: ad-clean microsites on a new domain where the word 'cannabis' was absent - allowing ads to run at scale without being flagged. The next challenge was attribution. Running ads from Meta to a landing page and then to the iOS store broke traditional attribution entirely. Revenue Institute's data team developed an AI inference-based attribution model using digital fingerprinting - tracking visitors through to app download with 93% accuracy, enabling Jointly to scale ad spend with full performance visibility.

The Results

Reduced CPD by 98.4%

Due to the new ad infrastructure and attribution model, Jointly decreased cost per user from $83 down to $1.35 - a 98.4% reduction that made scalable paid acquisition viable for the first time.

66.7× More Users

With $1.35 cost per user and working attribution, Jointly scaled from 3,000 users to 66.7× that volume - unlocking a growth trajectory that wasn't possible before.

AI Attribution at 93% Accuracy

Revenue Institute built an inference-based attribution model using digital fingerprinting that tracked users from Meta ad through to app signup with 93% accuracy - solving a problem no standard analytics tool could.

Key Results Achieved

  • Reduced CPD by 98.4%

  • 66.7× More Users

  • AI Attribution at 93% Accuracy

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