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 VBO process with Google non-branded search for one of our customers, a $150M D2C subscription box company in the beauty space , where our ROI is a reduction in CAC by over 23%:
Goal: Allow Google Ads to optimize bidding toward acquiring customers with higher LTV.
Test methodology: Matched Market Test
Planned timeline: This test will run for 8 weeks unless statistically significant results are garnered sooner.
Observed lift: 23.3% decrease in CAC
Significance: Company can acquire 50,000 additional customers in the next 12 months
Impact: $5.75M incremental gross profit increase; 4% increase in total gross profit