Not all market potential indexes are developed from a single series; some are combinations of several factors, occasionally as many as 20. Many of these indexes are developed by particular companies or industries to measure market potentials for their products. Others are developed by independent organizations, frequently published as indexes of market potential for consumers in general.
Special multiple indexes are designed to measure the relative potentials of different markets for a particular product. Such indexes have the advantage of taking into account several factors that influence the sales of the given product. When such indexes are constructed for specific products, it seems logical that they should measure potential relatively accurately. They have some pitfalls, however, that make them much less foolproof than they appear. Individuals preparing the index usually use their judgment in selecting the factors to combine. Whether this judgment is sound or not cannot be proven. Furthermore, who is to say how many factors should be used, or once the factors to use have been determined, how to combine them?
At first glance the Lotus super car illustration appears to use a special multiple factor index of potential sales. Potential buyers are identified as:
35 – 45 years old
Incomes higher than $150,000
In fact, this is more of a single factor index because any one person must have all of these characteristics to be considered a potential buyer. An area with 100,000 professional men 35 – 45 would have zero potential for super car if none of them had incomes of more than $ 150,000.
As indicated above, many subjective decisions tend to be made in using the multiple factor procedure. Many such judgments are based on estimates of how close the indexes obtained correspond to actual sales results. If this comparison is used to select an index, one can argue that sales themselves might as well be used as a direct index that is, if sales data are available for purposes of comparison, they are also available for use as a direct index. They would be superior to the other index if the measure of accuracy in the other index is its similarity to actual sales. A multiple factor index, however, may correspond in general with the sales pattern but may still show specific areas that do not correspond.
Multiple regression analysis is frequently used to eliminate some of the subjective aspects of the multiple factor method, such as determining the relative importance of alternative factors and the weights to be assigned each factor. But since the dependent variable (the geographical sales potential) is most known, it is not possible to obtain an estimate of the regression equation. To overcome this problem analysts frequently resort to company sales as a substitute for sales potentials.
General multiple factor indexes have been developed by a number of organizations. They usually are constructed as indexes of consumer purchasing power and are presumed to be indexes of market potential for consumer goods in general.
The best known general index of this type is the Sales and Marketing Management Buying Power Index. This index is constructed from three factors – income, retail sales, and population. Income is weighted 5, sales, and population 2. For each county in the United States income, retail sales, and population are reduced to percentages of the US total. These percentages are weighted as indicated above, then summed, and the total divided by 10 (the sum of weights). This gives an index for each country as a percent of the US total. General indexes of this type differ from special indexes only in the fact that they are designed for use with many products rather than with one specific product. Presumably, this makes these general indexes more a measure of real market potential instead of merely a measure of a particular firm’s past sales distribution.