Ocurate’s value-based optimization (VBO) solution leverages Machine Learning for customer value and integrations into advertising platforms to increase the Return on ad spend (ROAS) by 15%+.
Over the last years, Google, Facebook, and TikTok have built out capabilities to push data back into the ads APIs.
VBO leverages that technology by infusing the APIs with predictions of future per-customer revenues. Predictions are made immediately upon sign-up and exceed 90%+ accuracy.
The platforms can now allocate bids for ad impressions based on customer value as opposed to first purchase. The result: increasing ROAS without increases to the existing ad budget.
Below, we describe the process with Facebook with one of our customers ($80M beauty box), where our ROI is even higher (18%):
Goal: Allow Facebook Ads to optimize bidding toward acquiring customers with higher LTV.
Test methodology: VBB test
Planned timeline: This test will run for at least 5 weeks unless statistically significant results are garnered sooner.
Achieved Result: 18%+ increase in LTV:CAC
Significance: Increase first-year gross profit from acquisition media spend by 18%
Impact for every $10M ad spend: Increase annual returns by $3.2M, from $17.7M to $20.9M – a 18% incremental increase in 12 months gross profit