The things to test are those that usually have the greatest impact on response rate: offer, price, premium, creative (including strategy, format and copy), seasonality and list selection. Remember, of course, to test one element at a time, so you will be able to clearly link cause and effect.
First, test more substantial differences in the approach. You can fine-tune your program later on by testing finer points. (Mail is a responsive medium, and you will often achieve profitable results quickly; your next level of testing then becomes a matter of seeing how you can make a "good thing better.") By testing with small but statistically significant mailings, you can keep expenses to a minimum. Modestly priced testing can also encourage you to explore innovative approaches that might turn out to be breakthrough winners. You will find testing to be a fascinating, instructive and highly profitable exercise, full of marketing and advertising lessons you would not have gained otherwise.
- When should I test? There are as many answers to this question as there are companies with mailing programs. But here are some general guidelines:
- When you want to fine-tune a successful mailing to improve results even further.
- When your expense or expense-per-inquiry isn't what you had hoped.
- When you are presented with a new creative concept that you feel might be a significant performer but (wisely) requires more than gut instinct to justify a major rollout.
- When you seek to expand your market via wider-ranging list selection.
- When something in your marketing mix changes: a different price, a new offer, a promising premium.
- When there is a new-product introduction.
It is desirable to have an ongoing testing program. As you know, the marketplace is constantly altering and testing is a powerful tool for keeping up with changes. Also, testing supplies knowledge, and no marketer can have too much of that. Hunches, intuition and artistry will always play an important role in our discipline but so must the realities of response rates and numerical analysis.
What kind of response is necessary for a test to be reliable and predictable? Here again, there is no answer that applies to every company and every program, but there is a good rule of thumb. For a test to be considered predictable, you should receive a minimum of 1% return for the mailing in question. For example, for a 5,000-piece mailing, this would represent 50 responses