The selection of the appropriate test markets (usually small cities) is difficult. The number selected is a function of the reliability desired in the projected results and the number of variables being tested. It is reasonable to assume that, as the number of test markets increases, the reliability of the results also increases, if only by decreasing the chances of extreme errors.
When selecting test markets the following criteria are typically used:
1. The markets should not be over-tested.
2. The markets should be ‘normal’ regarding the historical development of the product class involved.
3. The markets should be typical regarding the competitive advertising situation.
4. No single industry should dominate the markets.
5. The markets selected should be so to represent different geographical regions (where different conditions might affect sales) that results can be projected.
6. Markets that contain groups not normal to the product’s target should be avoided.
7. The markets should have a media pattern to the similar to the proposed national media plan.
8. The markets should not be too small to provide meaningful results or so large that the testing becomes unusually expensive.
9. The markets should be relatively self contained that is, not too much waste circulation going outside the market, and no strong outside media present.
Several commercial research firms (e.g., Nielsen) maintain a number of test markets for their clients. Thus, not only are historical data available about the sales of individual brands, but personnel are available to undertake such tasks as ensuring product distribution, undertaking store audits, and interviewing consumers.
Projecting the Results:
If the company’s market share, total sales, and repeat buying measurement clearly exceed expectations, there is no reason not to proceed with national distribution. But such successful market tests results are not always achieved. Usually it is difficult to project the results in such a way as to provide an accurate estimate of the first year’s sales. To make such a projection for a frequently purchased product, it is necessary to know the rate at which consumers are first attracted to try the new product, the number of first buyers who buy a second time, the number of second buyers who buy a third time, and so on.
The difficulty in forecasting future sales lies in the fact that the demand for a new product typically rises rapidly then peaks and declines to a lower level. The reason for this is that many more consumers try the product than eventually adopt it. The challenge is to look beyond the hump in the sales curve and estimate the level of sales after the effects of the product’s introduction subside. The objective is to predict the sales level as early as possible from the test market results. The present state of the art allows reasonably accurate forecasts to be made between three and six months after introduction.
Electronic Test Markets:
Test market data are obtained using a variety of research instruments, including store audits, continuous consumer panels, and personal interviews via telephone. Increasingly, companies are using electronic mini-markets tests that not only reduce the cost of a traditional test market project by as much as a third but provide the needed data more quickly. Such high-tech research methods generate single source data that is, they track the behavior of individual households with respect to both their media habits and their purchases. The result is a measure of the impact of one or more marketing variables such as advertising copy, price, and a particular type of consumer promotion (e.g. coupons) on the trial and repeat purchases of a new product. Such single source research systems are also used to test the effect of advertising commercials, advertising weight, media scheduling and promotions on the sales of established products.