The right steps for successful matchbacks differ only in their complexity of rules, priorities and match criteria. Not surprisingly, the rules applied get increasingly more complex the more contact pieces you have in the mail at one time. Therefore, well thought-out criteria are critical in maximizing the usefulness of the matchback process.
Do gather relevant data from your matchback vendor. Include in your file appropriate sales data such as name, address and customer number. Also include all order information such as date of purchase; order total with or without shipping (depending on how you typically do your reporting); and product information if you plan to analyze post-matchback product sales.
If you’re using standard order export technology (e.g., Dydacomp’s Mail Order Manager Export Module), do tell your vendor which fields to include in the matchback and which to ignore. And always provide a field record layout. Don’t assume field name and content are obvious. When the wrong fields are used in a matchback program, you risk paying for an extra round of processing if you discovered that your post-matchback sales are less than your pre-matchback sales.
Before starting the matchback process, do have your matchback vendor run both your mail tapes and the order file through standard address correction software. Standardizing addresses in both files will significantly improve your match rate. That is, instead of making the program try to match 1234 Hazel Grove Lane and 1234 Hazel Gr Ln, both your mail tapes and your orders will have the same software-approved layout.
Don’t forget to create instructions. We’ve found that because matchbacks can be extremely complex, it’s best to create written instructions for your matchback vendor. These will provide both parties with clear guidelines and expectations. Start your instructions with basic information from the files discussed above (e.g., mail quantity, total sales). You’ll add to these instructions as you go through the steps detailed on page 46.
Do quick checks prior to matching back. Check that your matchback vendor has the correct mail counts, particularly if you’re using a different vendor from your normal mail processing vendor. The vendor should provide a report of name quantity by mail drop from the mail tapes. Check it against your final merge/purge records for each mail drop to be sure the numbers match.
Do check that the total dollars and number of orders from the sales file that your matchback vendor uses matches your idea of total sales for that time period. If you run a gross sales report and it shows, say, $850,000, be sure the order export file also totals about $850,000. Don’t sweat small differences, which can be caused by exchanges and returns. But your totals should be close enough to help ensure that the correct data are going into the process.
Do decide what kind of output you need. This might seem like it should be the last step, but you’ll find that determining the format of what you expect post-matchback will help you define the criteria for the process, itself (see below). These reports should include sales and orders by mailed group and mail drop, as well as key performance indicators, such as average order value, response rates, percentage of breakeven or contribution, and sales per book mailed.
Don’t forget to define your matchback logic. Typically, mailers will match back unknowns and Internet orders only because they assume all keycodes captured during order entry were captured accurately. But if you suspect you’re having problems with accurate keycode capture in your contact center, consider matching all orders against the mail tapes. Compare the matched-back keycode with the captured keycode to assess the extent of the capture-rate problems.
Do decide how often and when to perform a matchback. How often you choose to do a matchback will depend on your mailing frequency, budget and planning cycle. Many large direct marketers, particularly those with retail channels, do matchbacks as frequently as once a month. But for smaller mailers, I recommend you do a matchback at least once a mailing season, for example, spring/summer, fall/holiday or whatever seasons fit your mail plan.
Don’t forget to define a date range. Once you’ve established your matchback frequency, provide your data processing vendor with a list of contact pieces (e.g., catalog, postcard) sent during the matchback period and the specific date ranges each piece covers. See sample chart (below). The matchback date range for Drop No. 1 is Sept. 1 (the start of Drop No. 1 in-home) through Oct. 2 (the day before the subsequent catalog in-home).
Mail Drop | In-home Date | Matchback Date Range |
Drop No. 1 | Sept. 1-3 | Sept 1-Oct. 2 |
Drop No. 2 | Oct. 3-5 | Oct. 3-Oct. 31 |
Drop No. 3 | Nov. 1-3 | Nov. 1-Dec. 4 |
Drop No. 4 | Dec. 5-7 | Dec. 5-Dec. 31 |
Do determine your match priority. This can be the trickiest part of the matchback process. By match priority I mean the rules you create to allocate orders and in what order you choose to apply those rules. The specifics of your match priority will depend on the kinds of decisions you’ll be making for future campaigns.
For example, let’s say Jane Smith ordered in December. And in December you mailed her both a regular catalog and a special VIP mailing. If you allocate her order to the regular catalog, will your boss cut funding for your VIP mailing? If you allocate her order to the VIP mailing, will the deflated catalog results imply you should cut circulation? This isn’t just an office politics issue; it’s a question of maximizing return on investment. The key to match priority is creating rules that enable you to maximize decision-making. You may need to experiment with your rules to discern what works best for you.
Do carefully review your preliminary output. If it’s your first matchback, have your data processing vendor send output file dumps before running the entire matchback. A dump is a handful of sample records from the output file that enable you to verify that you’re getting back what you expected. It also gives you the opportunity to make changes to your matchback logic if needed.
As you do more matchbacks, you’ll get better at defining criteria and gleaning useful data from the results. But for now, don’t get hung up on details. You’ll be forced to make compromises, but the information you’ll find will be useful.
So until the day that all customers beg to give us their keycode information, happy matching.
Terrell Sellix is vice president of marketing at McIntyre Direct, a Portland, Ore.-based, full-service catalog agency. Sellix combines her love of data analysis with a sensitivity to the human side of marketing that stems from four years of marketing good health concepts in West Africa. For questions, contact her at: (503) 286-1400.
- Companies:
- McIntyre Direct