In today's competitive retail landscape, a company sought to refine its pricing strategies to boost revenue, enhance customer engagement, and create offers that better align with customer preferences, driving sustained growth and attracting new customers.
The company currently uses several pricing incentives, but wonders which one delivers the greatest value and cost-effectiveness, and whether other options might work better.
The solution is to use MaxDiff, a data-driven survey technique that ranks consumer preferences through trade-offs, to identify which incentives resonate most with consumers and drive optimal results.
"We match lower prices found at competitors" scored highest overall at 71.2%, showing that price matching is the most universally appealing incentive.
Among the key target segment (middle-class women), "Buy three, get one free!" (76.3%) and "Buy two, get one 50% off" (73.7%) dramatically outperformed the general population scores.
Cette étude de cas a été dérivée d'une étude réelle menée par MaxDiffPro. Elle a été anonymisée pour des raisons de confidentialité : les options testées et les résultats présentés ici ne correspondent pas exactement à la réalité. L'étude réelle avait les caractéristiques suivantes :
The timeline depends on the complexity of the study and the target audience.
MaxDiff ranking of 13 pricing incentives - All respondents vs. Key target segment
Score Ranking:
The scores (in %) shown indicate the percentage of respondents who rated each message as highly appealing.
Bi-dimensional categorization of pricing incentives - proximity indicates similar preferences, circle size represents importance
The Preference Map visualizes preferences through a bi-dimensional categorization, with proximity indicating similar preferences and circle size representing importance.
Consumer preferences and cumulative effectiveness of pricing incentives, highlighting the best combinations
The Product Mix Chart shows consumer preferences and cumulative effectiveness of pricing incentives, highlighting the best combinations. Using a combination of four distinct incentives, spread far apart on the preference map, optimizes the campaign's impact due to their complementary effects.
By optimizing the mix of pricing incentives based on the MaxDiff findings, the company saw a 7% increase in revenue within the first quarter. Additionally, there was a 11% improvement in customer acquisition, and repeat purchase rates grew by 15%, demonstrating the effectiveness of the data-driven strategy.
Choosing the right pricing incentives may seem intuitive, but when multiple options compete for budget and attention, MaxDiff identifies objectively which ones deliver the greatest impact.
By combining data-driven ranking with segment-specific analysis and the Product Mix optimization, the company was able to design a pricing strategy that resonated with its most valuable customers.
MaxDiff helps teams identify which messages, features, or ideas truly resonate with customers.
Typical study: 15–25 items tested · 150–300 respondents · Results in 3–5 days
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