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Predicting the Future, One Customer at a Time
March 2008 Franchising World
Customer analytics can help improve site-selection efforts and uphold the reputation of your brand. As more franchises realize the hidden value in their data, it’s easy to predict the future of customer analytics. By Rich Hollander Allowing a franchisee to open a poor-performing location can be extremely costly for any franchise company in ways that go far beyond dollars and cents. Underachieving stores can tarnish both the franchise system’s reputation with potential investors who are examining the retail concept and also affect the perception of its customers. Weak stores affect the quality of the story told in the Uniform Franchise Offering Circular, in which one must declare how many stores have been closed. In the long term, poor locations can adversely affect the brand’s image and have a negative impact on its future success.
Selecting high-quality sites is not easy
Can the future really be predicted?
Does that sound like a franchisor’s dream? It’s not, it’s a reality. In fact, today’s digital technologies, combined with the enormous amount of consumer data available to us, allow companies to know all of these things and many more.
Customer analytics makes it possible
Once franchise companies have this profile of their “best customer” in hand, they can search any trade area in the United States to find people who match the profile. When they find large concentrations of customers with the same characteristics as their best customers, they’ve discovered fertile ground for their franchise. From there, companies can examine specific locations to reveal the site that is near the greatest possible number of likely customers.
How forward-thinking franchises use customer analytics
Should I stay or should I go?
The future of franchising
Rich Hollander is president of Buxton’s CustomerID division and a partner in the company. He can be reached at 817-332-3681 or rich.hollander@buxtonco.com.
Any franchisor knows that the three keys to success are “location, location, location.” However, most new franchisees have little or no experience in selecting high-quality retail sites. Franchisors do provide some support in selecting retail locations, but the quality of that support varies widely from company to company. Some franchisors provide basic demographic information and population densities while stressing the importance of the store’s visibility from the street. Other franchisors provide more detailed information, such as the optimum tenant mix surrounding the store. The smart franchisors will send someone from the operations department to view the site in person to determine its suitability.
One all-important factor is typically missing in the analysis of retail sites: the individual customer. In today’s retail environment, any franchisor or franchisee that opens locations without taking the customer into account is at a distinct competitive disadvantage.
Imagine for a moment that a franchise organization has the ability to predict the future. Imagine that the company could take any address in the United States and forecast, with uncanny accuracy, the future sales results it could achieve there. Imagine also that the franchise system could select any residential address near a store and know, with a great degree of certainty, whether a person living there will become its customer.
A new strategic tool for franchises, customer analytics, allows companies to “predict the future” of its locations by predicting the future behavior of customers. More than likely, franchise companies have a tremendous amount of customer data available right now, but isn’t quite sure what to do with it. Through customer analytics, firms can mine the information that they’ve gathered to open new stores successfully and develop ongoing relationships with existing and potential customers.
It starts by creating a “best customer” profile, which is a highly-detailed picture of your most loyal customers. These profiles go far deeper than basic demographic data like a person’s name, age, race and marital status. To be effective, customer profiles must include vital psychographic data revealing all sorts of things about an individual: the magazines they read, the Web sites they visit, the brands they love, the stores they frequent, how much money they spend, how often they shop, and so on. Of course, analysis at this level takes a staggering amount of data.
Today, site selection for franchisors is not about finding the right real estate characteristics; it’s about finding customers with the right characteristics.
Some franchise associations are taking the lead in helping their franchisees find top-performing locations. For example, a dealer association for a nationwide auto repair franchise uses customer analytics to help franchisees find quality sites and predict sales revenue anywhere in the United States. The predictive sales model examines the surrounding customer base to see which households, and which individuals within those households, are likely to patronize the auto repair stores. Using advanced geospatial technology, the model also estimates how far a customer will drive to a particular location. By drilling down further, franchisees can see exactly what a particular household is likely to be worth, in dollars, to their store. Again, it’s like predicting the future, one customer at a time.
The information is provided to the franchisee in the form of a “Site Score,” which includes useful information about the surrounding customer base, potential sales results and the impact of opening additional locations nearby.
The model can also improve the quality of the franchisees’ marketing. By extracting the most likely respondents from the surrounding customer base, the franchisee can develop a high-quality prospect list. This increases both the efficiency and response of direct marketing efforts undertaken by the franchisee.
The predictive sales model developed for the dealer association can also help franchisees when lease expiration dates are coming up, too. Site scores can show a franchisee whether the current address is still the most profitable site in the area, or if there is another location nearby that could yield greater revenue.
For any franchise, customer analytics can be an extremely valuable competitive tool. Once the initial predictive model is in place, managers can use customer analytics to gain insight into many critical decisions that go far beyond initial site selection. Analytics can reveal which areas of the country are ripest for franchise expansion, how many stores a particular market will support and the sales impact of new competition. Analytics can even be used to select the optimum product mix in a particular store.
As more franchises realize the hidden value in their data, it’s easy to predict the future with customer analytics. Whether a franchise is using this new technology to its advantage, or its competition is using it against the franchise, it’s clear that customer analytics will have a big impact on the world of franchising in the years to come.
