Savvy retailers are aware of the importance and value of compiling pieces of information that can give them marketing levers for communicating and motivating select customer segments.
It is powerful to invite a customer back whom you haven’t seen over a specific period of time. It is valuable to increase the frequency of a customer’s shopping and buying habits. Combining key variables within your client’s customer data can result in a very powerful tactical model called RFM, analysing the customer’s most recent visit date (recency) along with his average frequency of visits (frequency), as well as his spending levels (monetary) into a working marketing model.
You can help build this very effective tool for your business clients. Help them reveal their best customers, find opportunity segments, and define segments they should not waste marketing dollars on.
And, for additional deeper insights, combine the RFM model with a geographic view of where their customers are coming from. Layering on the distance from or drive time to a location adds additional insight for consideration when building the marketing, media, and communication plan.
For example, the maps below represent a destination retailer, where drive-time data is appended to customer records. On the first map, customers coded as high frequency can be found in two distinct areas — within the 10-minute and between the 20- and 25-minute regions.
Go one step further and identify the high-spend customers among the high-frequency group, and the data illustrates they are also coming from those two distinct regions.
Further investigation into these two groups, such as segmentation by consumer type and media and behavioural preferences, results in a multi-dimensional data model from which to build strategy for growth.
Now, with all of this knowledge, select a group of valuable customers you want to bring back again. Send an e-mail invitation they can’t refuse. Track results to know how many acted on your invite and how much they spent when they did.