Expand Your Market Through Analysis
However, it's important to put this phenomenon in perspective.
This may not come as a surprise, but traditional snail-mail marketers have not scrapped their prospect mailings for acquiring new customers and turned their advertising budget dollars over to the Internet and e-mail marketing.
For further perspective, at a symposium in May, Regina Brady, vice president of strategy and partnerships at FloNetwork, Toronto, quoted a recent study from Forrester Research, Cambridge, MA, indicating that the average cost per sale for acquiring a new customer from a rented e-mail file was $286.
Until e-mail catches up to snail mail in terms of list quality and segmentation, mailers will have to turn to more practical approaches to improve their prospecting.
There are several approaches that, requiring only a little more investigative research, should improve response.
Analyze and Research Selections
Analysis and research of selections should be one of the most critical aspects of any mailing analysis. It will not only enable expansion into selections that are working well by identifying new segment opportunities but also will allow careful review of marginal lists with an eye toward improving selections.
The first step is to identify all the segments available on the lists being mailed as production or control files and gain an understanding of how the list owner defines them.
This may seem obvious, but mailers historically use selects that work for them and do not consider a list to be the sum of many different parts.
I've found that there are various degrees to which histories are accurately maintained. I've encountered too many situations in which list results are reported without a clear understanding of the selections used.
Identifying segments available can be done in two ways.
Meetings With List Manager Criticial
The importance of face-to-face meetings with list managers and list owners at various trade shows cannot be stressed enough. As a mailer, it is critical for you to sit down with your broker, identify the major files you use and set up target list meetings.
If this is not always feasible, work with your broker and carefully analyze the segments made available on the data card.
Though I have a great deal of confidence in my own data card system, MIN and SRDS, this analysis should always include the original data card from the list owner or manager.
I have seen client histories involving magazine files where the mailer was selecting direct mail sold names. With publication files, source definitions are not the same on every list. Some may include renewals in this select while others may include only the publisher's own direct mail sold names or agent sources.
You may find that a publisher's definition of direct mail also includes insert source names. Though these sources may be strong, it is important to know exactly what you are receiving and the mix they represent.
If you use magazine subscriber names, try to arrange for your broker to send you fulfillment house definitions of each potential source for some of your key lists and then match these up with how your names are selected. Reviewing these definitions also will generate new test ideas as you gain an understanding of the composition of each file.
The Importance of Self-Reported Data
Many mailers today are making extensive use of self-reported data from some of the larger questionnaire files on the market.
These would include lists such as Donnelley Shareforce, Lifestyle Selector, Targetsource, Behaviorbank and Buyers by Mail.
How many of you have actually reviewed the questionnaire from each of these companies?
I was in a situation recently where I had been using a specific ailment select from one of these files and, after reviewing the questionnaire, realized that the question actually produced several possible answers that are now being tested separately.
These are just a few examples of how gains can be made by carefully researching the files you use.
For example, in the catalog area, you should know what "average unit of sale" represents on the data card. Is it cumulative? The last transaction?
How is a single buyer vs. multibuyer defined? Is a single buyer always new to file?
Can you test cash vs. credit, and how does the list owner define cash? Is a credit buyer an installment sale or derived from pure credit card transactions?
Evaluate List Usage
This is a spreadsheet approach where you assign each list in your history to a specific category or list type. You could use SRDS categories as a guideline, or you might refine these to reflect the nature of the product or service you sell.
Based on your criteria for success - profit per order, return on investment, contribution to overhead - lists within each category would then be ranked in descending order and summarized by category.
For example, if you were establishing a category review for a publication's mailing history, each category would include:
• Number of lists.
• Quantity mailed.
• Gross orders.
• Net orders.
• Gross percent response.
• Net percent response.
Within each category, indexes can be developed to measure and compare performance. This approach is useful for identifying new list opportunities by focusing on those markets that have been responsive. Furthermore, results for a given market could suggest alternative approaches and offer strategies.
Track List Rental Decoys
Assuming your list is on the market, you are most likely renting or exchanging with most of the lists to which you mail.
I can't emphasize how important this is. This is really very basic, but I wonder how many mailers actually track the mailing pieces that come in from their list rental program.
What's to be learned? Plenty.
For example, timing becomes an issue. Not only are the people you rent to or exchange with mailing your file, but chances are very good that they also are mailing to the same files you use on a regular basis. Tracking your decoys will let you know if your own mailing patterns fall in line with your competition. Are you in the mail before, at the same time or after your competition? All this clearly affects your response.
In addition to timing, price points and offer clearly become an issue. How does your pricing compare with your competition? Has the upfront offer changed in any way?
For example, seeing a competitor move to a hard offer while you are promoting with a soft offer will impact performance. You may not want to drop the list from your mailing program, but this knowledge may enable you to limit your exposure by forecasting conservatively and limiting your list order volume.
Looking for a new creative package? What better way to see what's really working for your market? This is a great way to research new packages for you to test.
Take Advantage of Modeling
While list modeling is one of the more advanced tools available for mailers, not all may be candidates for a full mailed regression model.
While the benefits are obvious to those using this tool, some mailers are just not in a position to commit large volumes to regression testing. Most of these require a fixed number of responses/orders to analyze, and this usually requires that you mail fairly large nths.
A number of the larger list owners today will offer mailers the opportunity to build "look-alike" models or good customer match models. We have seen this to be an extremely effective approach, and they're working. What is key is that you generally will not have to commit to large volumes, and you may be able to have these models built at no cost and pay a surcharge based on usage.
The success of Abacus Direct and Z24 in the catalog market has lead to the creation of similar databases in the publishing area by both Abacus and Experian.
While clients are testing and results are still being evaluated, if you are a publisher, participating has a big upside. As a publishing mailer, your list cost per thousand will be lower than the traditional lists you are renting. In addition, there is most likely a menu of model options from which you can choose. For those publishers that mail heavily to expires, there is an opportunity to activate older names.
Jeff Kobil is vice president at MSGi Direct, New York, previously known as Stevens-Knox & Associates.