Project Overview
Dabbl rewarded people for watching bite‑sized brand videos. The idea was strong, the install curve was flat. We built a full‑funnel paid‑social engine—creative testing, look‑alike modelling, and automated bid rules—that moved Dabbl from obscurity to the top of the lifestyle charts, adding users at a pace the servers could barely handle.
Project Goals
Explode user base: Drive 500 000+ fresh installs while holding CPI under $1.50.
Boost stickiness: Lift daily active users (DAU) to 200 000 by turning rewards into a repeat ritual.
Validate revenue model: Prove to investors that ad‑view volume could scale profitably.
Challenges & Solutions
Crowded category: Competing with Honey and Rakuten for the same eyeballs.
Solution: Ogilvy‑style headlines—“Earn on the couch before your coffee cools”—paired with bright thumb‑stopping motion gave Dabbl a unique promise of instant gratification.Install decay: Early cohorts forgot the app after payout.
Solution: Sequenced retargeting that served “next‑reward” creatives at 24‑hour intervals until a seven‑day streak formed.Budget efficiency: VC funding demanded proof, not burn.
Solution: Automated rules that killed any ad once CPI crept 20 % above target, recycling spend into top‑performers every four hours.
Outcome & Impact
User surge: 556 314 net‑new daily users in six months, CPI $1.32 average.
Engagement: DAU/MAU ratio hit 42 %, tripling the pre‑campaign baseline.
Revenue lift: Ad‑view inventory grew 310 %, unlocking new brand partnerships and a Series A raise ahead of schedule.
Brand equity: Facebook’s own case‑study team featured Dabbl as a model for lean, data‑driven app growth.