What if targeting customers with higher retention was possible?
Ipsy embraced Voyantis' value predictions and achieved a 27% ROAS increase on Meta ad campaigns.
"After we understood we have a significant lifetime value variance within our subscriber base, we worked with our Facebook and Voyantis teams to create a prediction model that uses the Conversions API to enable us to optimize our acquisition investment on Facebook for lifetime value and not just to first-time purchase value."
2. Both groups were set on the same Meta bidding strategy (Highest Volume) for a fair comparison. The control group focused on CPS (cost per subscription), whereas the test group was optimized for predicted LTV.
3. While Voyantis’ LTV prediction provides a continuous value, the input Meta requires is binary (high/low value only) so Voyantis and Ipsy set a value threshold to signal to Meta what customers are considered “high value”.
"Using this prediction model, we were able to improve the 12-month return on ad spend by 30%"
How does it work
Processing & AI prediction model
Voyantis developed a custom prediction model, utilizing Ipsy's distinct customer data from Ipsy's onboarding quiz and historical retention records to formulate precise Lifetime Value predictions..
Feedback to Meta
LTV predictions were sent via Voyantis’s Orchestration layer to Facebook CAPI to focus the campaign on high LTV users on Meta.
Voyantis crafted the ideal approach for transmitting predictive signals to Meta's Value-Based Bidding, ensuring early, accurate, and rich enough feedback to Meta.
The model is constantly tested and verified by the Voyantis AI engine to generate the highest accuracy of future predictions. Voyantis constantly update the model to meet Meta’s latest ad model upgrades.
The results of the pilot clearly indicate the advantage of using value predictions for improving campaigns outcomes.
Focus on better customers: Voyantis predictions identified those customers that are likely to have higher retention and therefore higher value, which increased the retention rate at the end of 9 months by 33%
Significant ROAS jump: By focusing on customers with better retention, the overall value of each customer is higher and with a similar CAC - ARPU increased by 15% and the ROAS jumped by 27%.