Retail · Predictive audience value

Rent-A-Center turns audience intelligence into 12X ROAS.

Consumer data and predictive modeling helped Rent-A-Center look beyond its customer file and focus acquisition on households most likely to convert.

incremental revenue

return on ad spend

The challenge

Find growth beyond the file.

Known customers offered a useful picture of value, but not enough room for the next stage of acquisition. Rent-A-Center needed to find more households that looked promising for the right reasons, not simply more people who fit a broad demographic description.

What Datasys did

Turn a seed into a market.

Datasys added proprietary household and market context to what Rent-A-Center already knew. Machine-learning scoring ranked the wider opportunity, and lookalike modeling expanded the audience around the characteristics associated with value. The customer file became a starting signal for finding more of the right market.

From known customers to economic value

01
Known-customer seed
Start with the traits associated with existing value.
02
Household context
Add proprietary consumer and market intelligence.
03
Ranked opportunity
Score and expand the audience around likely value.
04
$30M+
12X
Measure the result in incremental revenue and ROAS.

The results

$30M+ in incremental revenue.

The resulting acquisition programs generated more than $30 million in incremental revenue and a 12X return on ad spend. The result put an economic measure behind the audience decision, not just a larger addressable count.

incremental revenue

return on ad spend