Data Drives Direct Mail Sales

Sharon MCatalog, Database

Understanding and interpreting data into actionable insights are important in both e-commerce and catalog success. Getting into the data and asking questions is how you uncover new insights and improve your direct mail success and revenue.

Segment Your Customers

You may have heard the term “segment your customers” but what does it really mean when it comes to your direct mail campaign? Analyzing your customer files and developing like groups or segments can prove to be a goldmine of information:

  1. Where did your customers come from? Were your customers added from sources such as PPC, organic search, catalog prospecting, sweeps contest, conference attendee list, or email sign-up?
  2. What are their key traits or demographics? Where do they live (i.e. zip code)? Are they men and/or women? What are their ages? Do they have children living at home?
  3. Review transactions next. When do your customers buy? How often do they make a purchase, what is their average transaction value ($), and what is their preferred transaction channel?

Enrich or Score the Database

To segment and define your groups, assign flags in the customer database based on the key criteria. For scoring, rank the top variables and assign a weight to each.  Note the acquisition source, customer type and merchandise category spend to help you develop a campaign strategy. More ideas on offer strategies can be found in our earlier blog.

Segmentation in Use – a Wine Retailer Example

A retailer who sells both white and red wines might learn that while sales appear equal on the surface, the customer who primarily buys white wine demonstrates a higher retention rate and a higher lifetime value than the customer who buys red wine.  Therefore, this customer is much more valuable to the company.

  • This knowledge could be used to feature a higher percentage of white wine in its catalogs and email messaging.
  • You could even take this a step further and analyze metrics based on white wine types such as Chardonnay and Sauvignon Blanc.

Understanding the value of how customers behave as it relates to product purchases can help with customer acquisition.

  • In this example, the company focused on white wine keywords and leveraged the insight to justify the higher spend on white wine keywords over red wine keywords.

The same logic applied to the wine example could also be applied to customers whose first purchase is clearance merchandise (or perhaps a promotion offer) versus full price merchandise. This kind of analysis works especially well for catalogs. How does segmentation apply to catalog distribution? We share more on our Catalog Consulting Blog, including how to use data to plan.

Clients often rely on us to serve as their resident data expert. We support the digital marketing and merchant teams with data analysis, allowing your IT department to focus on other priorities. Data analytics consulting services are available on either a project basis or monthly retainer. Contact us today for support getting started!

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