“This is my most used tool, day in and day out. It’s been integral in building customer personas and in creating targeted and informed ads. If you want the best chance to succeed, then Placer is a must.”

~ Amy Elliott, Data scientist at Bob Mills‍

The Challenge

Can better customer insights increase sales at a location different than the others?

Bob Mills Furniture Company is a family-owned and operated furniture chain with locations in Oklahoma, Texas, and Kansas. In business for more than 50 years, they know how to deliver quality furniture to their local customers.

One of these stores is located in a unique market, and management knew that it needed a new approach to hit its high sales forecasts. Amy Elliott, a new data scientist at Bob Mills, was asked to use behavioral and demographic data like household income, media preferences, and more to identify that store’s best customers and determine how to market to them.

In others words, how could she understand the market landscape, get deep customer insights, and use those insights to increase sales?

The Solution

Demographic and trade area Data Show The Target store had a different type of customer

Using Placer, Amy compared the trade area, visitation metrics, and audience profiles of the one location to the other ten stores, analyzing details like visit frequency, average dwell time, demographics, and journey before and after, noting multiple distinctions for the location.

Learn more about Ethnicity

For instance, demographic data revealed that the target store had a more diverse customer base than other locations, with over 50% of their customers being non-white.  Similarly, Amy also learned that the customers for this standout location responded more strongly to ads for “close out sales” and similar keywords compared to other locations, and that they drove no more than 5 miles to their store, a far shorter drive time than their other locations, some of which saw drives of 40 or more miles. Similarly, data on household income showed that the location overindexed for households in poverty compared to other locations, another key difference.

Learn more about Audience Profile

The Outcome

SUCCESS: Store Sales +17% Higher than Forecast

Using the new persona data, Bob Mills moved the location away from the standard marketing that all stores received and tested a new ad strategy specific to that store, targeting their best customers with store-specific ad keywords (e.g. “close out sale”) and serving the ads to the top zip codes within 5 miles, not the larger area used previously.

Learn more about Visitors by Origin

These customer personas and ad changes completely changed the store’s performance, beating seasonally-adjusted sales forecasts by 17%.

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