Have you ever wondered why some great, new products and ideas never go anywhere? There are probably a multitude of reasons. But one may be that management focuses on immediate profitability instead of the opportunity.
When testing new offers, for example, actual results may be good, but insufficient to produce the required profitability.
The following example demonstrates this concept by showing the sales results for a hypothetical 50,000-package direct mail test.
-50,000 direct mail packages cost $600 per thousand including printing, lettershop, postage and list rental
-Test 25,000 packages of offer #1 against a like amount for offer #2 for a total of 50,000
-The program also tests 10,000 rental names for each of five lists testing the offer and the lists simultaneously
-The product sells for $200
-Both offers cost the same to fulfill
-The profit for each product sold is $100 taking into account shipping, refurbishing and all associated product support costs
-The response rate for test offer #1 is .5%
-The response rate for offer #2 is .3%
-Though unlikely in real life, let's assume that all lists responded at the same rate
The test grid was set up as follows.
Here were the test profit results.
Notice that offer #1 lost $2,500 for 25,000 pieces dropped. And test offer #2 came in even more in the red with a $7,500 loss.
Conclusion: this is NOT the way to evaluate direct marketing tests. Why? The rollout of the tested lists comes to well over 1 million names. Based on the greater mail quantity and associated cost savings, the rollout of test #1 becomes profitable.
So here is another chart using the same assumptions and test results given above. But the ROLLOUT costs for a 1 million-piece run drops to $375 rather than $600 per thousand dramatically reducing the overall cost. What was a $2,500 loss for offer #1 becomes a $3,125 net profit when taking the rollout costs into account.
Here is the recommended way to analyze your test results.
The above tables were simplified to demonstrate why you should not require your testing to produce immediate profits. Don’t look at test results based on what you did, but on what would happen if you rolled it out to your target markets.
What you are looking for are not profits from the actual test, but a significant profit-making opportunity.
In what other ways do you look at campaign profitability?