The past year was extremely difficult for catalog companies. Many firms elected to mail deeper to their house files (instead of prospecting for new buyers).  Prospecting is down -30% to -50% according to industry sources. New list testing is off -43%. This means 12-month buyer counts are down.  Sooner or later (I hope sooner) catalogers need to start prospecting again. File counts cannot continue to decrease or sales will continue to decline. It is time to get back into the catalog prospecting mode. Now is when catalogers should cautiously increase prospecting levels to build for the future. As we emerge from the recession, those companies who continue marketing and mining for new buyers will be in a much better position to take advantage of the rebound.  We are already starting to see improvement within several segments. There is a cost associated with acquiring a new buyer. How much you are willing to pay for a new buyer depends on what you can afford to spend, how fast you want to grow and the life-time-value of the buyers being acquired. You must be willing to invest (key word) in acquiring new buyers; the lifeblood of any business.

Cooperative Database Performance – As you increase your level of prospecting, resist the temptation to pull out of any cooperative databases in favor of another. When a cataloger decides which cooperative database to keep using and which one to drop they use a multitude of factors. One factor is performance. Another is overall contribution. If a cataloger feels they are supplying “X” amount of buyers to a cooperative database but only taking less than “X” amount of prospect names from the database they feel the contribution is not in their favor and that particular cooperative database should be dropped.  But how does this effect models and prospecting names overall within the cooperative databases?

The problem is not every cataloger is pulling out of the same exact cooperative databases.  Even within the same product category, certain cooperative database work well for some catalogers but not others.  However, the names shared by all are still required to build an effective model and supply the best prospecting names. In essence, on top of everyone’s 12-month buyer counts decreasing and straight list rentals getting more difficult to get to perform well, the cooperative databases are also being affected.  In order for catalogers to keep their prospect names at their highest level to get through these tough times, it is imperative that everyone continues to stay within all cooperative databases they have been using.

Outside List Performance – Maximizing outside list performance can be accomplished by either increasing the response rate or the average order size or both. I prefer to focus on improving the response rate because it will yield a great number of new buyers thus growing your 12-month buyer file faster. Select outside lists based on “R” (recency of last purchase). Maximize rollouts before testing new lists. Double the usage each time (assuming there are enough names in the list universe). After maximizing list continuations, fill-in with the lists you want to test.  Looking for buyers who have purchased multiple times recently is also a good way to improve response rates. Use Marginal List Optimization to improve outside list performance. When prospecting in back-to-back mailings four to six weeks apart, should previously used names from an outside list or coop model be eliminated? For example, if an outside list or coop segment is mailed a catalog on August 28, should the same list or database segment be mailed again on September 25 just four weeks later? There will be duplicate names but I do not recommend omitting previous usage. Here’s why.

1. Outside List Rentals – Any omits would mean a zero balance (unless older names are mailed that most likely will not perform as well).  There is the option to replace some of the prospecting quantity with lists that are not already being used.  However, the prospecting universe is substantially reduced if previous names are eliminated from a given list. What’s more, if the results support mailing the same list consecutive times why not mail them.
2. Cooperative Database Prospect Models – I have tested this based on what Coops call “prior” names do well.  The idea is that these records came to the top of the model twice (at least).  The duplication rate between mailings depends on a number of factors – product category, which months the models are run, how different the customers are between the various mailings, number of names being taken.  Also duplication is higher in top segments than it is in lower segments. A model is designed by building a profile of customers and selecting prospects from the database that look like those customers being modeled.  If the customers for one mailing and for the next mailing are pretty much the same the profile will look the same.  If the models are built in August and September, for example, the database does not change much.  Since the profile and databases do not change, the model will pull many of the same names. For the most part, our analysis has indicated names receiving both catalogs tend to perform better than those that receive only one catalog.  There is typically a 60% to 75% duplication of names from one mailing to the next within a given model segment.

The printed catalog drives shoppers to the website.  As the economy begins to improve, consider increasing the amount of outside list prospecting with your print catalog. It just might be time to get back into the prospecting mode.