Using Your Relational Database, Part Two

Last week we wrote about relational databases opening up a world of marketing opportunities and ultimately making better use of your database (“Using Your Relational Database). This week, Jim Coogan, president of Sante Fe, NM-based Catalog Marketing Economics, brings you the second installment.

* If your business is seasonal, segment buyers by either purchase date or type of seasonal merchandise purchased, then tailor your mailings to reactivate each segment of buyers during their prime selling season and lower the frequency of mailing outside of their best selling seasons.

* When customers request a print catalog, try to e-mail them—and thus convert them–immediately. The Internet has changed the attention span of buyers, and your best chance to convert a qualified catalog inquiry is by contacting him the day he requests a catalog.

* Separate customers who bought as a result of a promotion or deal from those who bought at regular prices. Then see if you can effectively send the “deal” customers nonpromotional offers as well as promotional ones?

* Look for merchandising opportunities by finding what products are typically purchased together and then group them together in your catalog. You can even try to create kits or “buy X, get Y” deals.

* Offer clearance and overstock merchandise primarily to those who have previously purchased clearance and overstock products, rather than to customers who paid full price. This helps keep your selling costs low and prevents your total house file from expecting (and waiting for) sales.

* Relational databases can drive square-inch analysis to the profit-per-item granular level. Looking at profit by item, profit by merchandise category, and profit per page better enables you to keep focused on your best merchandise categories.

* Continually look to see if your Web customers are significantly different than your traditional customers. Are your Web and traditional customers so different that you are evolving into two separate businesses?

* Consider appending co-op database house file scores into your RFM segmentation. Then try dropping households with poor mail order buying behavior and reactivating “hot” households within dormant RFM segments.

* Examine the lifetime value of customers by customer type–list source, merchandise type, season, and any other characteristic that can allow you to separate high-value customers from low-value customers.

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