Background: A leading retailer sees an increasing cost of acquiring customers via catalogs.
Challenge: Improve catalog mailing efficiency.
Measurement: CAC (Customer Acquisition Cost) = Marketing Campaign Cost/Total Customers Acquired per Campaign.
Benchmark: $300 per acquired customer (based on historical performance).
Method: Our team leverages data from past campaigns to build predictive models for selection of the best 500,000 leads from a prospect database of 5 million names.
Results: After predictive models are implemented, improved response rates drive lower CAC and translate to an expected incremental 36,000 new customers acquired over 9 campaigns every year, delivering an additional $36 million annually.