Product Line Optimization Using a DecisionSimulator™
Category: Personal Care Manufacturer
Methods: Product Line Optimization, Choice Modeling, DecisionSimulator™
A global manufacturer of specialty personal-care products needed to develop a response to major changes made to the category leader’s product line.
The specialty person-care product category is dominated by one brand. When that brand’s manufacturer decided to make significant changes to it’s product line—including changing product names, graphics, package counts, and pricing—market competitors needed to get an early read on consumer reaction by testing potential strategies for their own brands.
The overall objective was to understand what strategy would maximize overall product line revenue. Specifically, our client wanted to know how to change their package counts, designs, and prices for its products relative to the category leader’s changes. In addition, our client wanted to tailor separate responses for mass merchandisers and drugstores.
Research Design and Methods
A 25-minute Internet survey was conducted among more than 2,000 representative category users who shop at one of four retailers. The sample was balanced to ensure a mix of targeted demographics (age, gender, and income) and current brands used. All of the respondents were recruited from the American Consumer Opinion® panel.
Each respondent was asked to imagine they were shopping for products in the category. A choice task was designed so that the respondents were assigned to view a subset of category products with different prices, package counts, and designs. Each respondent reviewed 10 different shelf sets of product images and information and was asked to select the one product (per set) they would be most likely to purchase. The respondents’ choice data was aggregated and modeled to produce a DecisionSimulator™ that showed market-level results for optimal combinations of the client’s product line.
Based on the results of this research, our client adopted a new revenue-maximizing strategy that included new packaging and new pricing tailored to each of its four major retail sales channels. Results of this research were also utilized as support when negotiating with retail buying managers. The research findings were ultimately used to optimize the shelf set of the manufacturer’s products at each retailer.
Analytical Consulting Services
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