Value-based optimization (VBO) with real-time LTV: Google and Facebook with eSalon

The Challenge

eSalon is a company in the women’s beauty brand space trying to optimize its ad spend based on customer value.

The Results

Predictive accuracy

We look at a comparison of what each customer actually spent over the past 6 months and which per-customer revenues we predicted six months ago.  The average error was $3.54 over the last 6 months, and the median error was 0. For comparison: The company’s average LTV per year (measured in gross profit) is $49.

ROAS optimization and results

Together with Ocurate, eSalon integrated the real-time LTV predictions into the Google and Facebook bidding APIs.

In May, June, July and August, before VBO was deployed, the average 12-months gross profit of all customers acquired on Google and Facebook was $49.01, In September, October, November and December, after VBO was deployed, the average 12-months LTV of all customers acquired increased to $56.43 – a 15% increase.

Achieved Result: 15%+ increase in LTV

Significance: increase first-year gross profit from customer acquisition by 15%

Overall revenue impact: $590K increase in annual returns from $3.9M to $4.4M

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