The Seven Basic RDE Steps
Step 1. Identify groups or classes of features that constitute the target product (offering, etc.) For example, in the case of a credit card offer, the variables could be APRs (annual percentage rates), Rewards Options, and so on. Every such variable (also called a ‘silo’ or a ‘bucket’ of ideas) comprises several APRs, Rewards Options, etc.
Step 2. Mix and match the elements according to an experimental design to create a set of prototypes. The second step is usually done automatically by a tool that creates a unique individual design plan for each respondent, allowing for individual models of utilities for each respondent.
Step 3. Show the prototypes to consumers and collect their responses on a rating question (e.g., “How likely would you be to buy this product?”).
Step 4. Analyze results using a regression module. One of the key differentiating points of RDE is individual models of utilities for each respondent. This allows patterns discovered in the data, across elements and respondents (Step 6) to generate rules for more targeted optimization as well as uncover all meaningful two-way synergisms and suppressions between the elements, . RDE uses dummy variable regression to estimate the absolute values of the utilities, which in turn allows for databasing the results. The database makes for meaningful comparison of the element utilities in one study, and across studies, which then track the consumers’ minds across studies and time.
Step 5. Optimize. Uncover the optimal product, find the best combination that has the highest sum of utilities.
Step 6. Identify naturally occurring attitudinal segments of the population that show similar patterns of the utilities.
Step 7. Apply the generated rules to create new products, services, offerings, and so on.
Read more about this topic: Rule-developing Experimentation
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