+70%
Higher ROAS
2.0× → 3.4× return on ad spend
Wellix PredictView assumptions: Wellix Predict
Business outcome. Evaluate acquisition decisions using customer value signals. This models a different acquisition outcome, not a model prediction or automatic campaign optimisation.
How Wellix helps. Predicted value, payback analysis and cohort evaluation can inform the client’s acquisition decisions. The client changes campaigns and evaluates the outcome.
Comparison: 2.0× → 3.4×. One month with $10,000 in advertising spend.
- Ad spend and traffic cost stay fixed at $10,000 for the same measurement period.
- Assume conversion increases by 25% and revenue per buyer by 36%: 1.25 × 1.36 = 1.70. These are inputs, not predictions.
- Use the same attribution rules and revenue window: attributed revenue changes from $20,000 to $34,000.
- ROAS = ad-attributed revenue ÷ ad spend. It is not ROI or profit.
Relative change = (scenario value − baseline) ÷ baseline × 100. Compare the same metric definition and the workload or population described below.
ROAS = ad-attributed revenue ÷ advertising spend. $20,000 → $34,000 revenue at $10,000 spend: 2.0× → 3.4×. Assumed conversion multiplier 1.25 × revenue-per-buyer multiplier 1.36 = 1.70. This is revenue, not profit or ROI.
The inputs are illustrative assumptions, not measured results or a forecast. Effects on the same purchases, subscribers or tasks must not be added together.