**5. Finding these mind-sets in the population using the PVI**

Researchers are accustomed to working with mind-sets. The notion that people radically differ from each other in how they react to simple stimuli is an old one, embodied in aphorisms and folk wisdom. What is novel, however, is the rather unpleasant realization that there is generally no simple set of rules, which one can use to put a new person into a mind-set. There is the ever-present wish that people who are 'alike' in who they ARE (e.g., age, education, gender, residence, shopping behaviors, and so forth) will share similar mind-sets. Thus, the standard method of cross-tabulating individuals to search for clues to the potential membership in one or several mind-sets is to use the easy-to-collect information about the person. As we will see below, in a study of 41 students, similar in age, education, and so on, this is not the case. Birds of a feather may flock together, but they think disparately.

Many marketers and scientists have 'complained' that the mind-sets provide valuable information, but they need the mind-sets to be generalized. For reason of cost and simply the marginal knowledge imparted by each new respondent, most Mind Genomics studies comprise at most 300 respondents. A great lesson can be learned about mind-sets with as few as 40**–**50 respondents. The base size of 50–100 suffices to reveal the nature of the mind-set, and often to define it, but does not let the researcher or businessperson make full use of the mind-sets for other purposes. A method is needed to assign new people to mind-sets that have already been discovered.

One original method was to work with large samples of 300+ respondents, discover their mind-sets, and then, during the research, purchase a great deal of additional information about these same 300 respondents. A data analysis would be then hired to create ad hoc models attempting to relate mind-set members to some combination of purchased information. Occasionally the predictive methods worked, but most often the collection of the ancillary data was expensive; the number of variables to collect was unknown as subject to many vagaries occurring when the data were collected and required significant analytical effort.

### *Sequencing the 'Dairy Mind' Using Mind Genomics to Create an "MRI of Consumer Decisions" DOI: http://dx.doi.org/10.5772/intechopen.101422*

During the past 5 years, author HRM and colleagues, especially author Gere, have collaborated to create an easier system based upon a Monte-Carlo method. The original summary for data, showing the coefficients for the three mindsets, for example, is perturbed to create 'noisy' data. A decision tree is created to determine the assignment of a new respondent to one of the three mind-sets, based upon the perturbed data. At the end, a synthesized decision tree is created, comprising six of the 16 elements. The respondent uses a 2-point scale rate for each of these six elements. The pattern of the ratings assigns a respondent to one mind-set or of the two or three mind-sets emerging from the study.

**Figure 1** shows an example of the first part of the PVI. The left-most rectangle shows the introductory information about the respondent. The respondent identity (name) is never collected, but there is an option to collect the respondent phone number and email address. This option must be accepted by the respondent who participates in the study, viz. so-called opt-in. Should the respondent refuse to provide the information when requested, PVI is instructed to close, going no further, and thus respecting the respondent's desire for privacy.

Each of the 10 studies generates six questions, based upon the elements in the study, but with the option to edit the elements, as well as edit the two-point rating scale. Not shown is the option to ask four simple questions for each product PVI, each question having up to four answers, one of which must be selected.

Each of the 10 studies is set up separately, and then added into the PVI tool. Thus, for this project with 10 different dairy products, the PVI comprised the information rectangle (left), and 10 columns, one column corresponding to each product in the set of studies.


#### **Figure 1.**

*Example of the PVI, showing the introductory panel, and two panels for products, a smoothie and a healthful, nutritional shake.*

The researcher setting up the study can instruct the PVI to randomize the order of the studies when desired, to randomize the order of the questions within the study, when desired, and even to randomize the full set of 60 questions. The latter, full randomization, makes the task difficult for the respondent to 'game.'

The time to complete the introductory panel is approximately 45 s. The evaluation for each panel takes approximately 15 s. Thus, for the introductory panel and for the 10 product panels, the total time is approximately 195 s or 3.5 min. The time suffices to 'sequence' the mind of the respondent on the 10 dairy products, that is, to discover what is important. The PVI typically takes about 3–4 min for 10 different products (as well as the information page.)

The researcher can set up the PVI to drive three additional steps, each of which is optional. **Figure 2** immediately provides the feedback to the respondent regarding the assignment of the respondent to the proper mind-set for each product.


**Figure 2.**

*PVI output with partial feedback for one respondent (four of 10 products).*

*Sequencing the 'Dairy Mind' Using Mind Genomics to Create an "MRI of Consumer Decisions" DOI: http://dx.doi.org/10.5772/intechopen.101422*

