“Now is not the time to diminish the value of your stores.” That is a quote from a presentation that I gave several years ago at an industry event. As part of the discussion, I was highlighting the results of a cross-channel research project that we had recently conducted. The project’s objective was to gain a better understanding of a specific retail brand’s ecommerce performance drivers and the subsequent development of a strategy to grow digital sales. For this retailer, the findings could ultimately be summarized in two words: Stores Matter.
As our “Beyond Real Estate” series continues to highlight logical extensions of an Intalytics forecasting model, this edition focuses on model applications in support of cross-channel analyses.
At the core of a traditional real estate-focused sales forecasting model is the premise of distance decay, a term used to describe the strong correlation between sales and customer convenience. The best data source for measuring distance decay comes from a robust customer loyalty or membership database, ideally one that also includes customer address (for operators lacking customer address, Intalytics can provide reverse append capabilities using phone number and/or email address). Many organizations lack this level of detail and turn to supplemental sources such as massive mobile data (MMD), manual POS collection, or even customer intercept surveys. By comparison, an often-overlooked advantage when conducting an ecommerce analysis is the availability of phenomenal customer-level data. Each transaction record almost always includes the date, transaction total, products purchased, and address. When dealing with such pristine data, a retailer would be remiss not to conduct a spatial evaluation of these customers for comparison with the brick-and-mortar network.
Depending on the situation or objective, there are any number of analytical paths that an operator can explore. Specific business questions that can be addressed include:
- Do I generate more ecommerce sales from customers that live near stores, or from those less proximate to my existing locations?
- How can my ecommerce data inform my real estate growth strategy?
- What is the impact of opening or closing a brick-and-mortar store on ecommerce sales?
- Is there an ideal market-level store saturation threshold that will maximize overall market share?
- How do my in-store customers differ from my ecommerce customers?
- Are cross-channel customers more valuable than those who transact exclusively either in-store or digitally?
- Would a certain store prototype or service impact channel performance?
Intalytics has abundant experience addressing these types of questions on behalf of our clients. The methodologies we employ in the development of a forecasting model extend seamlessly to conducting cross-channel analyses which in turn support our client’s ability to make informed, data-driven decisions. For more information regarding our omnichannel solutions, please contact us to schedule an introductory discussion.