Probability of Switching to the New Brand—This is the proportion of consumers who, when
in a purchase situation with both the new brand and established brands, will purchase the new
brand over the established brands. It is entered as a probability between 0.00 and 1.00.
Probability of Repurchasing the New Brand—Based on satisfaction ratings, this is the
proportion of consumers who have already bought the brand and would repurchase the new
brand over established brands. It is entered as a probability between 0.00 and 1.00.
Industry Sales Projection—The total potential market for the product.
Fixed Costs, Other—The fixed costs allocated to the new product (excluding the
previously-entered marketing mix variables: advertising, distribution, and sales promotion).
OUTPUT
Projected Long-run Market Share—Calculated based on the probabilities of trial, purchase,
and repurchase, this is the ultimately occurring market share that can be expected for the new
product. It is used to compute projected company sales and variable contribution margin from
the industry projection and per-unit contribution. The impact of “what-if” changes in the
marketing mix can be diagnosed against this variable.
Total Profit Contribution—This is the result of translating market share into dollars after
accounting for fixed costs.
ASSESSOR Exercise
Good Times Snack Company is a manufacturer of snack cakes. The company distributes only
over a three-state region in the Northeast but its cakes are extremely popular in that area,
regularly maintaining market shares almost as large as the big nationwide producers. Good
Times is planning to launch a new chocolate and cream snack cake, and is considering an
investment of about $1.8 million on advertising, distribution, and sales promotions (such as free
samples), allocated as follows: advertising, $800,000; distribution, $600,000; sales promotion,
$400,000. Your task is to determine whether an increase in any or all of these budgets would be
advisable in terms of increasing total company profit contribution.
Good Times management has provided you with estimates of certain parameters to be used in
running the ASSESSOR model. They believe the long-run trial probability of this product is
90%, and the probability that a customer who receives a free sample will actually purchase one is
80%. Based on studies of similar, previously-launched products, management believes the
probability a customer will switch to the new brand is 70% and the probability of a repeat
purchase is 60%. Key parameters used in developing the response function are as follow: