**6. Creating an integrated database from the set of PVIs**

We conclude the empirical section of this chapter with the creation of an integrated database, comprising the information about each respondent who participates. The database comprises the information about the respondent herself or himself, such as age, gender, country, and other material collected at the start of the PVI. **Figure 3** shows part of the database.

Each row of the database comprises the information about the respondent, the name of the individual study on which the respondent is being 'typed,' the mindset name, as well as other information not shown. The other information comprises the mind-sets, the feedback, the six questions and their answers, and the (up to) four questions and answers that could be asked for each product at the start of the PVI for that product.

The first objective of the database is to advance science. **Tables 4** and **5** show the results from one small study conducted with 41 students at Ryerson University, who participated in a larger study, from which these data were abstracted. Had the study been limited to 10 products, each respondent would have seen the products in random order, the questions within the products in random order, and the entire sequence might have lasted less than 4–5 min. The actual study comprised the 'typing' by all 41 students on the full set of 67 products.

It is clear from **Tables 4** and **5** that groups and individuals show a preponderance of the group of mind-sets encompassed by the term 'flavor seeker'. Yet there are other mind-sets, and a few respondents who fall into these other mind-sets. **Table 5** shows the mind-set memberships for 10 of the 41 respondents. Most of the respondents fall into the group called 'flavor seeker'. In general, for these dairy products, about 60% of the time a respondent will fall into one of the groups that can be defined as 'flavor seekers.' The rest of the time, the respondent will fall into different groups, whether these be traditionalists, value seekers, health seekers, and


**Figure 3.** *Part of the database created for the study, for one respondent.*


#### **Table 4.**

*Distribution of groups into different mind-sets. Groups with one respondent are not shown.*


#### **Table 5.**

*How 10 different panelists fall distribute into the mind-sets.*

so on. From this small sample, the hierarchy of memberships in the different mindsets is not clear. That is, when the respondent does not fall into the 'flavor seeker' group, it is not clear the next likely group to which the respondent might file.

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

## **7. Discussion**

The 'emerging'science of Mind Genomics traditionally has focused on how people think about one product. The notion of creating a set of Mind Genomics studies appears to be first attempted with the It! studies beginning in 2001. In those studies, the effort was made to identify fundamental mind-sets of respondents across 20–30 different foods and beverages [13].

These early studies opened the way to thinking both about a 'wiki' of the mind for a set of different foods, and the potential of typing a person on these different foods. The early thinking, however, was simply to discover a limited set of overarching categories. Thus, in the first study, the efforts revealed three groups of mind-sets for foods, based on one's desire for the food. The set of 30 foods was encompassed in the so-called Crave It! Study [14]. The three mind-sets were called Elaborates (focusing on the description of the food), Imaginers (focusing on the description of the ambience, and other ancillary factors), and Classics (focusing only on the food itself). These three mind-sets appeared in consecutive studies, albeit in different proportions.

Around 2008, when marketers began to think about using Mind Genomics to sell foods, the notion of typing the same person on a set of related foods began to emerge. The standard question was the same: Across different foods, is there a single mind-set segment which best describes a single individual? And thus, was born the idea for this paper, namely, create a typing tool, the PVI, personal viewpoint identifier, which could 'sequence' a person's mind, assigning the respondent to different and appropriate mind-sets for each of a set of identifiable products.

As noted in the introduction to this chapter, the evolution of Mind Genomics studies quickly revealed just how easy it was to dig deeply into the granularity of a person's mind on a specific topic. The simplicity, rapidity, and sheer efficiency of a Mind Genomics study soon make it less rewarding to investigate one product with excruciating thoroughness. One might consider that response to Mind Genomics to be more of an indication of personality than a description of the scientific project, but the reality is that it appeared possible to create powerful, granular data at an 'industrial level.' It was easy to investigate 10, 20, 30, or more products or situations (e.g., insurance, anxiety, health issues) as it did to investigate one product or situation. One needed simply to create more studies, launch them in parallel with as many respondents as one wanted, and as many of the types of respondents as were thought to be need. The only constraint was money.

The question arose, however, about interconnecting these results, not at the general level, but at the level of the individual. If one could mind-type a person on 10, 20, or even 100 or more products or situations, was there any way to integrate the data? It was not feasible to run a person on 100 studies, each lasting 3–4 min, simply because of fatigue, boredom, and resistance. Working with 100 products, each study requiring 3–4 min, means that to do the original study at an industrial scale, we would require 300–500 min, or 5+ h. One could, however, create the simply typing tool, the PVI, with each part of the PVI lasting 15–30 s. The typing tool could be run in one long, relaxed, stretched session, lasting about 30–55 min.

The data for this study comes from the typing of 41 students from Ryerson University, done by author SD as part of her senior capstone project. This chapter demonstrates the relative simplicity and power emerging from the research ability to corral data from different studies, reshape the results, and use the resulting data to create a new data set, and in turn to create a new PVI. The PVI, whether for all the products or simply for the 10 dairy products, allows us to type new people in a reasonably short session, to identify relations between who the person is and how the person thinks.

Looking backward at the effort as it applies to the knowledge of thinking, it seems possible now to erect large-scale databases of the mind literally from the 'bottom-up', in short spans of time, with efficiencies never-before realized. One can imagine the power of science, whether food science, medicine, social science, legal science, and so on, when it is possible for practitioners to create these large-scale structures, with the PVI attached, literally one can type millions of people, to understand the covariation of the mind with behavior, with health, and so on, almost ad infinitum.

## **8. Conclusion**

To get a sense of an investor looking at the value of mind-typing a person on a set of different products, consider this scenario, doable now, and most likely the case in the not-too-distant future. Imagine a store with 'beacons', receivers and senders of information. Imagine these beacons linked with computer screens, with the computer screens placed near different parts of the dairy case(s). A shopper who has gone through the PVI exercise, and had her or his mind 'typed,' whether for dairy alone or for many foods, would have a card in her or his bag or wallet. The information in the card would identify the mind-set of the person for the different types of items in the dairy case, or even for the different types of items in the entire store.

One might then imagine the beacon 'reading the card', to discover the mind-sets of the individual with that card. The person herself or himself would not be the relevant information, and thus would remain private. All that would be required would be 'knowing' the mind-set of the person for the particular product. Privacy would be an issue and certainly the massive computations to generate a cogent recommendation for this individual would not be necessary. All the relevant information is stored on the card, that is, the relevant information about what to say to the shopper for the product to be sold. An offer about the product might be made, or the salient messages about the product would appear on the respondent's smart phone, or on electronic signage above the product. The scenario just painted means true individualization of the shopping experience, with the right words, cogent messages, and even electronic, storable coupons.

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