Prospect Modeling

Increasing Store Foot Traffic and Revenue In-Store and Online

35%

In-Store & Online Sales Lift

400%+

Incremental ROI

3,000+

Person Increase in Store Foot Traffic

Aisle Rocket implemented a people-based approach to identify and target their best customers.

Challenge

Versace needed to target people who are most likely to buy their products online and in-store. The brand also needed to measure online and in-store purchases generated from these data-driven marketing campaigns in order to make their budget go further through highly effective spending.

Aisle Rocket delivered a 3,300 person increase in foot traffic and a 35% increase in in-store and online sales.

– Marti Crampshee, VP Marketing, Versace USA

Approach

Aisle Rocket analyzed the brand’s previous purchase data to understand their customers then used advanced analytics to build lookalike models to identify their best prospect audience.

Solution

We applied a Lifetime Value Amount to the lookalike models that was connected to offers that generated a higher average basket size.

To understand the shopping behavior of best non-customer and customer targets, we geo-fenced Versace’s locations and competitor locations, and executed display ads.

Through this people-based approach, Versace learned that people who viewed their online ads went to a store to make the purchase, and customers with higher net worth are much more receptive to direct mail than display ads.

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