Are your Web buyers or your catalog requesters dragging down your response rates? Many catalogers face a problem of the flood of Web buyers, in that the number of buyers is going up but response to house buyer file mailings is going down. Web buyers aren’t as loyal; your competition from search and price comparison engines is just a click away. They’re also not as responsive to catalog mailings. Catalog requesters are similar to Web buyers because it’s easy to request a catalog on the Web, the time window to convert a catalog request is much shorter, and catalog request response rates can quickly fall below breakeven if not closely monitored.
How do you know if your circulation is healthy? Here’s an example:
Say you’re mailing 1 million Web buyers at $2.00/catalog mailed. Your breakeven is $1.00/catalog. This circulation looks healthy.
But when you segment your circulation into Web buyers that purchased as a direct result of receiving a catalog (catalog-driven Web buyers) and Web buyers who didn’t receive a catalog but ordered because of natural or paid search, affiliates, etc. (pure Web buyers), you can see that the circulation is not healthy.
|Catalog Driven Web Buyers||400,000||$3.85/catalog||$1,540,000|
|Pure Web Buyers||600,000||$.77/catalog||$460,000|
In this example, 60% of the circulation is below breakeven!
How much money is lost by mailing the pure Web buyers below breakeven?
Sales/book: $.77/catalog mailed
Total sales: $460,000
Cost per catalog: $.50/cost per catalog mailed
Total catalog cost: $300,000
Merchandise margin: 50%
Total margin: $230,000
Loss (Catalog cost-margin): ($70,000) loss
Catalogers need to rigorously segment their buyer files to make certain that they are suffering from hidden losses from poor performing segments. Which segments should be segmented?
- Pure Web buyers (all the Web driven source codes)
- One-time Web buyers
- Low ticket Web buyers
- Older Web buyers who haven’t bought in 12 months
- Holiday buyers
- Web catalog requests
- Price comparison engine shoppers
If you are a member of a cooperative database, use their powerful optimization tools to find the best Web buyers and suppress the Web buyers who aren’t responsive to catalogs. How do you use the coop database’s optimization modeling?
- Drop the Web buyers who show little or no mail order buying activity.
- Find your breakeven and suppress those buyers below your breakeven.
- Segment your Web buyers and catalog requests before you optimize; you’ll get better results if you optimize one-time Web buyers separately from holiday Web buyers, for example.
- Change your contact strategy and send poor performing Web segments more e-mails and fewer catalogs.
- Consider solos, e-mails, postcards and other lower cost contacts to your marginal LTV buyers.
- Segment your catalog driven Web buyers from your pure Web buyers.
Don’t assume that your buyer file circulation is healthy in the face of softening response rates. Dig deeper than RFM segmentation and segment your buyers and catalog requests by channel to validate the true response rates by segment. You need to know the response rates of your Web buyers to keep your circulation healthy.
Jim Coogan is president of Santa Fe, NM-based consultancy Catalog Marketing Economics.