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Increasing efficiency & revenue through data-driven models

Cataloger and online retailer, Ballard Designs, sought to strategically grow their brick-and-mortar footprint, while managing costs by reducing circulation. Epsilon data and modeling capabilities helped them identify the right Retail Trade Areas (RTAs) for profitable expansion.

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    lift in catalog performance in identified RTAs vs non RTAs
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    lift in demand by identifying unique audiences within the Trade Area
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    higher response from machine learning models vs legacy models

How We Did It 846

Identifying profitable Retail Trade Areas

Epsilon conducted a Retail Trade Area Analysis to identify the best markets for customer retention, activation and acquisition. We implemented prospecting models broken out by Retail Trade Area and Non-Retail Trade Area utilizing store affinity, luxury zip affinity and our newest machine learning model, Accelerate. And we developed direct mail marketing and contact strategies that maximized spend between direct mail and digital.

Ballard now has 12 retail stores in major markets including Boston, Chicago, Atlanta, Dallas and Nashville. They learned that catalogs perform better in Retail Trade Areas and which helps in managing circulation budget. Also the company now has more accurate attribution metrics: they can more effectively target customers and prospects within 10 miles of a retail store, can tie back to whether a customer received a catalog and can use the data to help inform future mailings.

Epsilon’s data and modeling strategies have helped us make better-informed decisions on where to expand our retail presence and how to effectively reduce circulation.

Brian Barga, Circulation Director at Ballard Designs
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