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Purchase Probabilities If the only goal of your research is to determine which price point yields the most favorable rating, then any inherent problems with measuring purchase probabilities are minimized. The simple mean scores comparing the stated likelihood of purchase, or interest in the product, can be compared across the different price points. The most favored rating identifies the best price point. Rarely, however, is this level of interest sufficient. Most of our clients want to know not only which price point is best received but also what will generate the most revenue. Furthermore, if there is any question whatsoever about the possibility of introducing the product, they want accurate information so that they can assess what their return on investment will be for this new product, and if that is sufficient to warrant the product development, marketing, and sales effort that will be required. Under these circumstances, an accurate assessment of the likelihood of purchase is required. What this implies, of course, is that survey data as provided by most respondents are not accurate in this regard. This is true. Under most but not all circumstances, respondents will in the aggregate over-state their likelihood of purchase. The aggregate over-statement of purchases masks some interesting sub-trends. If we ask the question about the likelihood of purchase and use a response scale of 0-10, where 0 means absolutely will not purchase and 10 means definitely will purchase, we see that:
What this implies, of course, is that producing an accurate sales forecast from survey data requires
that questions about the likelihood of purchase must be calibrated to more accurately reflect the actual
likelihood of purchase. Most typically, the calibration involves transformation from the linear 0-10 scale
onto an S-curve function with modest purchase probabilities at the low end of the scale, rapid acceleration
of the curve through the intermediate portions of the scale, followed by a plateau effect at the upper
end of the response scale.
At MRA, we use industry sources, existing research, and data from the survey to calibrate purchase probabilities. The end result is a sales forecast with alternative scenarios that allows you to make informed decisions about potential that any new product introductions might have. No other research company can bring you this level of precision and expertise. Please contact us to find out how our state of the art solutions can help your marketing decisions. |