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Drivers’ Education: Using JMP(R) Pro 14 to Find Latent Drivers of Customer Preference ( 2019-EU-45MP-066 )

Level: Intermediate
Job Function: Analyst / Scientist / Engineer
Robert Reul, Managing Director, Isometric Solutions

This work sheds light on the importance of latent drivers addressing both how consumer choices can inform business choices and how latent drivers can inform marketing strategy. In our study, a smart home security provider is competing in a crowded marketplace against both highly established competitors and deeply funded disrupters (Google, Amazon). Our task was to find the best value proposition to make a distinct marketing claim and thereby increase brand awareness and drive customer acquisition. The study tested a large set of alternatives. Here, typically the ranking or rating methods would be cognitively burdensome, resulting in inconsistent late-survey responses. Using the MaxDiff Design approach, we generated a balanced incomplete block design that efficiently tested 21 different value propositions in convenient subsets of five. The choice experiment was fielded to 1,524 respondents via sophisticated web interview. This yielded 30,480 comparisons analyzed with MaxDiff Choice to establish the relative marginal utilities, identifying value propositions with greatest appeal. To assure the ultimate marketing claim was as distinct as it was strong, Fit Model was used to analyze the relationship between marginal utilities and the sought outcome variable, likelihood to purchase. This revealed the unique and compelling “latent drivers” used as new advertising claims.