What is Customer Analytics?
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Predicting customer behavior

Through psychographic data analysis, Buxton is able to create in-depth, accurate profiles of any organization’s most profitable customers, or “best customers.” These profiles are customized to the business, so every “best customer” profile is unique. For example, the “best customer” characteristics for an upscale women’s boutique will obviously differ radically from those for a sporting goods store.

Once the “best customers” are fully profiled, Buxton can examine any trade area in America to find other people who share the same psychographic attributes – people who are very likely to respond to the products and services offered by the business. When many of these potential customers are aggregated in a single area, it indicates a fertile location for the company.

Buxton is also able to predict exactly how far a given customer will drive to a particular location. Traditionally, companies analyze trade areas by drawing concentric rings around a particular location. Buxton devised a model that is much more rooted in reality and far more effective: the Drive-Time Gravity Model. This model measures any trade area by the time it takes a customer to drive to an address within it.

By combining precise customer profiling with the Drive-Time Gravity Model, Buxton can predict the purchasing behavior of customers in any trade area in the United States. Even further, Buxton can actually put a dollar value on each household in the trade area, detailing what that household is likely to be worth to the new enterprise. With incredible accuracy, Buxton can also predict the total sales of a new store, restaurant, or health care clinic at any location in America.

Through customer analytics, companies can make decisions with much greater confidence and clarity because every decision is backed up by hard facts and objective data.

Applications for customer analytics

The technology involved in customer analytics is extremely complex, but the questions it helps organizations answer are simple ones. Where should I put my next location? Will this product or service sell well at this store? Which people are most likely to respond to my marketing message? Into which states should I expand?  The merchandising implications of customer analytics are the most far-reaching aspect of this new science.  With the knowledge gained by understanding who their customers are and how long they will travel to purchase goods or services, retailers are now able to cluster their stores with customers who behave similarly.  By understanding these clusters, retailers are able to put the appropriate merchandise in those stores and design the corresponding promotion for each cluster.

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