| "Systematic, intelligently inquisitive and precise, RDE’s objective is to eliminate guesswork in the process of reading the minds of consumers." KIRKUS REPORTS |
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© 2007. Moskowitz and Gofman. All rights reserved.
What are the common steps in any RDE?
Selling Blue Elephants
By Howard Moskowitz and Alex Gofman
By Howard Moskowitz and Alex Gofman
| Moskowitz Jacobs Inc. |
Step 1. Think about the problem and identify groups of features that comprise the target
product (offering, etc.) For example, in the case of a credit card offer, the variables could be
Amount APRs, Rewards Options, and so on. Every such variable (or a “bucket” of ideas) comprises
several alternatives. When you work with a beverage, sugar content may be 6, 8, or 10 units; when
you work with a credit card, APR may be 0%, 4.00%, 9.99%, 15%, and 21.99%. So the first step
is to do your homework and structure the problem. This is the most difficult part of your job. Here
is where your expertise comes in. Be aware of the GIGO (Garbage In, Garbage Out) principle to
appreciate the importance of the first step. The good news is that you can throw many ideas into the
buckets for customers to test. The rest of the process is highly automated, virtually painless.
Step 2. Mix and match the elements according to a special experimental design (a schema of
putting together elements) 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, resulting in
individual models of utilities for each respondent.
Step 3. Show the prototypes to consumers (or let the respondents taste them, in the case of
products) and obtain their reaction (usually, purchase intent, liking, or interest in the idea). The third
step is typically an automated Web survey or a taste exercise in a facility.
Step 4.* Analyze results (build individual models) using a regression module. The magic of
experimental design estimates the contribution of each individual element to the liking scores that a
consumer would assign, whether the contribution is positive (so the liking is higher) or negative (so
the liking is lower). Colloquially, analysis shows what everything brings to the party. This analysis is
automated. Shortly after completing the survey, RDE tools provide a table of utilities (individual
scores of elements), the building blocks of your new products.
Step 5. Optimize. To uncover your optimal product, you just need to find (usually an automatic
process as well) the best, or optimal, combination that has the highest sum of utilities. It is that
simple!
Step 6. Identify naturally occurring attitudinal segments of the population that show similar
patterns of the utilities. The segments span demographically and socially among different groups
of people. By creating rules for the new products or services using the attitudinal segments, it’s
possible to increase the acceptance by 10-50% or even more. You don’t have to worry about
creating modestly better products averaged for everyone when you can create superb products for
selected people. The good part of the process is that it is (as you can guess by now) also an
automated procedure.
Step 7. Apply the generated rules to create new products, offerings, and so on. Want to have a
credit card optimized for value-oriented middle-aged customers? Just “dial in” the parameters in the
tool, and voila! Here is the best possible offering! Want to offer a credit card for young
professionals? You have the data already - just “dial in” what you want, and the rules are
immediately generated. This step is the most fun to use.
* In many cases (especially, more simple ones), Steps 4-6 are treated as one step.
product (offering, etc.) For example, in the case of a credit card offer, the variables could be
Amount APRs, Rewards Options, and so on. Every such variable (or a “bucket” of ideas) comprises
several alternatives. When you work with a beverage, sugar content may be 6, 8, or 10 units; when
you work with a credit card, APR may be 0%, 4.00%, 9.99%, 15%, and 21.99%. So the first step
is to do your homework and structure the problem. This is the most difficult part of your job. Here
is where your expertise comes in. Be aware of the GIGO (Garbage In, Garbage Out) principle to
appreciate the importance of the first step. The good news is that you can throw many ideas into the
buckets for customers to test. The rest of the process is highly automated, virtually painless.
Step 2. Mix and match the elements according to a special experimental design (a schema of
putting together elements) 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, resulting in
individual models of utilities for each respondent.
Step 3. Show the prototypes to consumers (or let the respondents taste them, in the case of
products) and obtain their reaction (usually, purchase intent, liking, or interest in the idea). The third
step is typically an automated Web survey or a taste exercise in a facility.
Step 4.* Analyze results (build individual models) using a regression module. The magic of
experimental design estimates the contribution of each individual element to the liking scores that a
consumer would assign, whether the contribution is positive (so the liking is higher) or negative (so
the liking is lower). Colloquially, analysis shows what everything brings to the party. This analysis is
automated. Shortly after completing the survey, RDE tools provide a table of utilities (individual
scores of elements), the building blocks of your new products.
Step 5. Optimize. To uncover your optimal product, you just need to find (usually an automatic
process as well) the best, or optimal, combination that has the highest sum of utilities. It is that
simple!
Step 6. Identify naturally occurring attitudinal segments of the population that show similar
patterns of the utilities. The segments span demographically and socially among different groups
of people. By creating rules for the new products or services using the attitudinal segments, it’s
possible to increase the acceptance by 10-50% or even more. You don’t have to worry about
creating modestly better products averaged for everyone when you can create superb products for
selected people. The good part of the process is that it is (as you can guess by now) also an
automated procedure.
Step 7. Apply the generated rules to create new products, offerings, and so on. Want to have a
credit card optimized for value-oriented middle-aged customers? Just “dial in” the parameters in the
tool, and voila! Here is the best possible offering! Want to offer a credit card for young
professionals? You have the data already - just “dial in” what you want, and the rules are
immediately generated. This step is the most fun to use.
* In many cases (especially, more simple ones), Steps 4-6 are treated as one step.
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