Abstract
Of the people who buy a brand or product in a given period of time, a certain number—the “loyal” buyers—will buy again in a later one. The proportion of buyers who are loyal in both can be predicted from a mathematical model, using observed data relating to one period only.
In verifying the predictions against the actually observed loyalty proportion for the following period, the goodness of fit has, with one exception, averaged about half a percentage point for loyalty percentages ranging from less than one percent to over 25 percent. Practical applications of developments of this kind are also discussed.
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