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Three Big Mistakes Direct Marketers Make When Reading Test Results
 
By Cynthia Baughan Wheaton
Principal, Wheaton Group
 
Original Version of an article that appeared in the May 2003 issue of Target Marketing

I love the way the numbers of our business can "talk" to us - giving us guidance.  We pride ourselves on the precision of our results.  And yet, if we are not careful, the numbers can lie to us - wasting time, resources and misdirecting our businesses.  Often, we must tease out the true answer rather than take the simple answer at face value.

The following are three big mistakes that many marketers are making.  They may seem obvious, yet I see companies overlooking the obvious in the quest to get things done and move to the next opportunity.

Big Mistake #1:  Skipping the Homework
The first step in analysis is to gather the facts.  Otherwise, there may be critical clues that are overlooked in the more traditional phase of the analysis.  Homework should include a thorough check of every phase of the solicitation and fulfillment of the offer. 

Start with a review of the name selection instructions, looking for any bias that may have been inadvertently introduced, particularly during split and key.  (Written instructions should have been kept current throughout the selection process.)  Go on to check name and address output.  If possible, get dumps of names and verify that selection criteria were used properly.  At the least, check the duplicates listing to see if there was a problem.

Create a partnership with your printer.  Get printed samples, preferably by attending the print run rather than relying on hand-selected samples.

Next, verify what actually circulated:  counts, dates, keycodes, and physical samples of the solicitations.  Get samples to check for proper insertion, correctness of the order form, readability of the ink-jet message, and other critical elements. 

Ideally, you have visited the lettershop, and examined machine-inserted samples to verify correctness before the mail has been turned over for delivery.  On occasion, bags of mail are found at the printer after it is too late for insertion into the postal system, or when the delayed timing will generate lower response. 

In addition, if different creative packages have gone out from different vendors, they can be biased if one panel is received on a different date than its counterpart.  For instance, a test between a solo catalog and a catalog in an envelope, initiated by different vendors, would require close coordination. 

Talk to your team of supporters.  Your list broker may have new perspective on any outside lists that were used.  Check with Customer Service, Systems, and Fulfillment to see if there have been any complications that may impact the methodology you use to evaluate results.

The mail can provide important clues.  Monitor arrival dates and the condition of your own "seeds."  Also monitor the arrival dates and offers of your competitors.  Did they coincide with yours?

Big Mistake #2:  Lack of Perspective
If you look at a mailing or test in isolation, you will not understand its overall relevance to your business.  Often, by putting results in proper context, you will see clear direction in unexpected places.  Also, it is important to determine cause and effect as best you can.  Understand the "why?" as well as the "what?" of your results.

If you have changed more than one variable when comparing two tests, be careful with the analysis.  You will not know the individual effect of the changes.  Perhaps one change helped a lot, while the second change response.  You may need to re-test in a different combination. 

Measure test results incrementally against a control, and look for statistically significant differences.  Anything less will be misleading.  Check your actual response rates against your sample sizes.  Test quantities should have been determined statistically, based on the expected response rate or something slightly lower.  If the actual response is quite a bit lower than expected, your reading of the test cells will probably be jeopardized.  If the results are too small to read with confidence, plan a re-test.

In list testing, if you are testing another variable, such as timing, be sure to test both alternatives against the same set of lists.  For instance, it is not fair to compare Cover A (Lists 1 through 5) against Cover B (Lists 1, 2, 3, 7, and 10).  Also, be sure that the included lists are in the same proportion to each other within the test panels.  For instance, if List A is 20% of the circulation for the Cover A test, then List A should be 20% of the Cover B test.  If it is not, arithmetically adjust the proportions so that an unbiased read of results is possible.

Individual test panels do not have to be identical in size to be compared accurately.  For instance, your control may be 250,000, while the two test panels may be 35,000 and 23,000.  Each test panel needs to be big enough to read with confidence, but each test does not have to be identical - or even particularly close in size. 

The caveat to this is when the panels (any combination of test and control) involve extremely different quantities of different physical packages, with one (likely the control) qualifying for a postal discount, while the second panel does not.  The smaller panel will experience a lower rate of deliverability, which in turn will lower corresponding response.

Do not apply averages when calculating results, unless you have no other alternative.  For instance, you cannot assume that web orders are the same percentage of total orders within each keycode.  You also want to use the true cost of each individual rental list segment, rather than an overall average cost per thousand.

Costs included in an analysis should be carefully chosen.  For instance, rollout-quantity-based costs should be used to evaluate a test, rather than the actual cost of producing the test.  Using test costs will put it at a disadvantage, because the overhead of developing the test is spread over much smaller circulation than the control.

Big Mistake #3 - Forgetting the Future
Solicitations are made for two reasons:  1) generating revenue and profit, and 2) learning how to increase your profitability in subsequent contacts.  Always consider the future implications of your findings.

Pay particular attention to unexpected results from ongoing offers or lists.  If a "gold standard" list for your business suddenly has bad results, consider a retest.  This is particularly important if your homework provides no reasonable explanation.  Act cautiously on weak test results.

Identify any operational changes that must be made to have "winning" tests ready to rollout.  Factor incremental cost requirements into your analysis.

Document your findings in a simple but thorough manner.  Communicate findings to the appropriate people and encourage future feedback, so your company can build on the base of knowledge rather than constantly reinventing the wheel.

Perhaps most importantly, identify next steps.  What do these results tell you about the past?  What do they mean for the future?  If results are inconclusive, or suspect due to an error, your best long-term alternative may be to re-test.

Conclusion
These three big mistakes come from one root cause - lack of time.  That could be due to a shortage of resources, or cash-flow considerations.  But, there is no aspect of the business that is more important than understanding your results.  Testing will never be perfect, but if you put in the time required for thorough planning and appropriate analysis, you will ultimately save time and money.

Cynthia Baughan Wheaton is a Principal at Wheaton Group, which specializes in direct marketing consulting and data mining, data quality assessment and assurance, and the delivery of cost-effective data warehouses and marts.  Cynthia can be reached at 919-969-9218, or cynthia.wheaton@wheatongroup.com

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