FOUNDING A NEW SCIENCE: MIND GENOMICS

FOUNDING A NEW SCIENCE: MIND GENOMICS

HOWARD R. MOSKOWITZ1,3, ALEX GOFMAN1, JACQUELINE BECKLEY2

and HOLLIS ASHMAN2

1Moskowitz Jacobs, Inc.1025 Westchester Ave.

White Plains, New York, NY 10604

2The Insight & Understanding GroupDenville, NJ

Accepted for Publication February 20, 2006

ABSTRACT

We present in this article our vision for a new science, modeled on theemerging science of genomics and the technology of informatics. Our goal inthis new science is to better understand how people react to ideas in a formaland structured way, using the principles of stimulus–response (from experi-mental psychology), conjoint analysis (from consumer research and statistics),Internet-based testing (from marketing research) and multiple tests to identifypatterns of mind-sets (patterned after genomics). We show how this formalapproach can then be used to construct new, innovative ideas in business. Wedemonstrate the approach using the development of new ideas for an elec-tronic color palette for cosmetic products to be used by consumers.

INTRODUCTION

During the past several decades, the emergence of computation as amajor driver of scientific prowess has accelerated. When first developed in the1940s, much of the statistical computation was done either manually by so-called “computers” (i.e., individuals who did the computation) or by sortingmachines such as the Hollerith card-sorting machine. At that time, use ofstatistics was relatively minor, confined to those types of statistical tests thatcould be executed easily in the field or in the laboratory. The notion oflarger-scaled analyses using statistical methods was acceptable, but more oftenin the realm of fantasy than fact. The senior author has fond (and occasionallynot-so-fond) memories of manually analyzing data from studies with a pro-

3 Corresponding author: TEL: (914) 421-7400; FAX: (914) 428-8364; EMAIL: [email protected]

Journal of Sensory Studies 21 (2006) 266–307. All Rights Reserved.© 2006, The Author(s)Journal compilation © 2006, Blackwell Publishing

266

mailto:[email protected]

fessor at Queens College in New York. The data, collected by Professor LouisM. Herman in the late 1950s at the Wright Patterson Air Force Base, wereanalyzed during a 4-month internship in 1962 by the author and Jerry Weiss,both undergraduate students in psychology. The manual analysis of what todaywould be considered a simple three-way analysis of variance took approxi-mately 3 months, using the MonroeMatic and Friden calculators, and anassortment of scratch paper to record intermediate results.

During those years, the notion of genomics was becoming more interest-ing, but the thought that someday such thinking could generate easy-to-execute studies for the Genome project was far away (Collins et al. 2003). Thenotion was even further away in the future that recombining ideas rather thangenes using statistical design could be a reality, and indeed as will be shown avery simple reality at that. It would be the confluence of statistics and genom-ics, especially the simplicity of executing work in both, that would be theinspiration for the science described here (e.g., Systat 1997; Van Ommen andStierum 2002; Watkins and German 2002).

With increasing computational power readily available, and with theexpanding interest in statistical design for quality control at first and sub-sequently for product design, the opportunity became increasingly real tounderstand consumer responses to products through so-called “designedexperiments.” Whereas at first, statistical thinking was limited to inferentialstatistics, tests of differences between agricultural treatments or product pro-cessing, statistical design of test combinations quickly revealed that a system-atic approach to product development would work quite well.

It was quite another thing to use statistical design to understand theconsumer mind, and to move such understanding to the creation of ideas forproduct business in the commercial world. However, such applications ofexperimental design were soon in coming, driven by a scientific renaissanceafter Sputnik. The psychological sciences benefited as much as the physicaland biological sciences did. In the early 1960s, a frenzy of newly fundedresearch efforts concentrated on better understanding underpinnings of psy-chological measurement (e.g., Suppes and Zinnes 1963). One of the mostimportant developments of this period was conjoint measurement, at first aproduct of mathematical psychologists seeking to better understand the under-pinnings of measurement (Luce and Tukey 1964), but destined to grow intoa major intellectual development stream that would spark radical develop-ments in consumer research and business (Green and Rao 1971; Green andSrinivasan 1990; Wittink et al. 1994; Moskowitz et al. 2005c).

Conjoint measurement, the basic quantitative structure underlying thescience proposed in this article, can be reduced to a simple descriptive state-ment, namely the use of experimental design to understand reactions to ideasby measuring reactions to mixtures of ideas. Conjoint measurement uses

267MIND GENOMICS

experimental design, mixing together small components (or “idealets,” if sucha word was to be used), generating combinations, acquiring subjectiveresponses to those combinations, and then deducing what components drivethe reactions (Box et al. 1978).

Conjoint measurement differs from the more conventional one-at-a-timemeasurement strategies so commonly taught in university level sciencecourses. The point of view of conjoint measurement in particular andstatistical experimental design in general is that the combination of inde-pendent variables allows each of them to affect the other in a way thatcould not be seen in the traditional one-at-a-time approach (Anderson1970).

HOW BUSINESS NEEDS DRIVE NEW THINKING

Conjoint measurement might have remained a well-respected, frequentlyhigh-level research method in the world of marketing research, with a slowmigration into other fields such as public policy, had it not been for theprofound demands of business. At one level, conjoint analysis was happilysatisfying the need for marketing and product development professionals tounderstand how specific features of a concept, whether product, emotion,brand, reassurance, etc., drive responses.

A more profound contribution to business comes from looking at thepotential of conjoint analysis to understand “broad sweeps of categories andideas,” not just the limited ideas from one product alone. Furthermore, addi-tional information comes when the conjoint approach can constitute a user-friendly database that a developer or marketer can interrogate in order todevelop new ideas. Thus, business problems, specifically the need for under-standing, drive conjoint measurement into broader applications, primarilybecause conjoint measurement is able to provide such deep, fundamental andprofound information about how people make decisions in a fashion that isboth direct and easy to understand.

The final business need is to create product ideas in a systematic wayusing the insights developed from conjoint analysis. A great deal of today’sso-called “innovation thinking” revolves around two poles, neither of which issystematic creation. One pole is the activity of coming up with new ideas. Thisis the so-called “ideation phase.” Professionals talk about ideation, have allsorts of suggestions about what to do to create ideas, but really do not talkabout precise processes to create ideas. The second pole is metrics. Businessloves metrics, which is about processes and output. There are countless articlesabout the numbers of ideas that are generated in meetings, about the Stage

268 H.R. MOSKOWITZ ET AL.

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Gate process and its ability to funnel ideas (Cooper 1993). What is missing,however, is a formalized system that actually creates the ideas. Conjointanalysis provides that system. Because conjoint analysis mixes and matchesideas in the test phase, why not do this mixing and matching of disparate ideasfrom different product categories in order to create an invention machine in theservice of innovation? The notion of such formalized mixing and matching ofdisparate ideas from different realms to create novel combinations was pre-sented by Moskowitz (1995) for oral care, but at that time, the development ofconjoint analysis was not sufficient to make the process a very simple one.That time has now arrived for a formal, easy-to-implement system.

BY WAY OF HISTORICAL INTRODUCTION

The science of Mind Genomics began in the last part of the 1990s, as thenotion of archiving utility values went from dream to reality. Prior to thedevelopment of conjoint analysis using dummy variable modeling, whichallowed for meaningful values of element utilities, most conjoint analysis usedso-called “complete concepts.” Each concept comprised exactly one elementfrom each of the available silos. Thus, because of statistical multicolinearity,analysis of the data could not generate absolute values for the utilities. That is,the desire of users of conjoint measurement to work with complete conceptsmeant that statistical regression analyses of the data developed relative utili-ties. Differences between the utility values were meaningful within a silo, butnot within the utility values themselves. Nor, in fact, could utility values becompared across silos, and indeed, they could not be compared across studies.The adoption of dummy variable modeling, with incomplete concepts, gener-ated absolute values of utilities, first making the research easier, but moreimportantly creating the foundations of a valid science. As long as conjointanalysis used (and continues to use) complete concepts with the inevitablemulticolinearity that ensues, it will be impossible for the utilities to have realmeaning. There may be conference after conference, article after articledealing with these issues of making otherwise nonmeaningful utilities mean-ingful, but they will only be statistical exercises, not the foundations of ascience.

CREATING THE NEW SCIENCE – SETS OF LINKED STUDIES(IT!, INNOVAIDONLINE) GENERATING A SEARCHABLE

DATABASE

Conjoint analysis, first the output of efforts in mathematical psychology,then a key tool to understand and prioritize features in marketing, now

269MIND GENOMICS

becomes the basis of this new science. The new science itself, Mind Genomics,creates a corpus of knowledge about how people respond to the components ofa complex stimulus. The objective of this science is to create databases aboutwhat features in product descriptions or situational “vignettes” are important.At surface level, the science quantifies what is important. At a deeper level, thescience creates a body of knowledge that reveals how people think aboutdifferent topics, working from responses to complex vignettes downward tomore fine-grained granularity as to how specific components contribute.

First, attempts at creating this corpus of knowledge can be seen by twoinitiatives to create databases of concept ideas, using conjoint analysis andattempting to formalize the knowledge structure. These are the It! databasesand the InnovAidOnline initiative.

It! Databases

When the first steps toward this science were taken in early 2000, theobjective was simply to understand what features of products or what specificcommunications and brand names make products craveable. The strategy wasto work on a number of different products, not just one product alone. Whattransformed the approach from a research project to a science was the creationof linked databases, the structured approach and the enormous potential tounderstand new, hitherto unexpected aspects of consumer responses, eitherfrom patterns of the individual utilities alone within a product study, acrossdifferent products or integrating the conjoint portion of a study with theself-profiling or classification portion of the same study.

The early efforts created the science by developing a so-called “megadatabase” of 30 related studies. Those early efforts were followed by updatedmega databases for craving (called the “Crave It!” series), as well as otherlarge-scale databases for beverages (Drink It!) and a number of other differentdatabases. As shown in the following list, the databases span a range fromfoods to lifestyles.

It! Databases created and venues where the results have been presented orpublished:

(1) Foods (Crave It!)a. Crave It! USA (Moskowitz et al. 2002a);b. Eurocrave (Aarts et al. 2002);c. Eurocrave (Luckow et al. 2003);d. Teen Crave It! (Ashman et al. 2002);e. Beckley et al. (2002);f. Beckley et al. (2004a,b);g. Moskowitz et al. (2002b);h. Moskowitz et al. (2005d);


i. Beckley et al. (2004c);j. Krieger et al. (2002);k. Moskowitz and Beckley (2005).

(2) Beverages (Drink It!)a. Hughson et al. (2004);b. Poskanzer and Ashman (2003).

(3) Fast food experience (Its! Convenient)a. Ashman and Beckley (2004).

(4) Healthful products (Healthy You!)a. Hirsch and Zawel (2002);b. Zawel (2002);c. Luckow et al. (2005).

(5) Anxiety (Deal With It!)a. Ashman et al. (2004);b. Beckley and Ashman (2004);c. Moskowitz et al. (2004).

(6) The customer shopping experience (Buy It!)a. Himmelstein et al. (2004);b. Beckley et al. (2004d);c. Moskowitz and Ashman (2003);d. Minkus-McKenna et al. (2004);e. Ashman et al. 2003.

In addition to the published databases, there are other databases in theeffort, including those dealing with insurance (Protect It!) and with not-for-profit topics (Give It!).

The reason that the It! databases may be construed to be the first contri-butions to this new science is the combination of systematics (attempts tocatalog mind-sets using conjoint analysis), rules (attempts to understandgeneral trends), applications (attempts to use the results to create new ideas)and testable predictions (attempts to predict success of products or new trendsfrom the conjoint results, which quantify level of consumer interest in the ideaor set of ideas).

InnovaidOnline.Net Initiative

A second effort, run after the successful It! studies, focused on creatingnew product ideas using a systematized process based on the organizingprinciple first explicated by the English philosopher John Locke. That is, thethinking was that new ideas are simply combinations of old ideas, albeit in newmixtures. Idea innovation, therefore, would be best done by having a collectionof these ideas already available to the developer, and a tool for combining these

271MIND GENOMICS

ideas. Such an organizing principle, although propounded almost 400 yearsago by Locke, also lies at today’s science of genomics.

This set of large-scale databases was called “InnovaidOnline.” The goalwas to create a set of related studies for foods, beverages and lifestyles, suchthat the elements of the studies were “actionable” to the product developer.Whereas It! dealt with product features, emotions, brands and reassurance,InnovaidOnline dealt strictly with the features of the product, package andmerchandising. It! studies were meant to act as a foundation for knowledge.InnovaidOnline studies were designed to aid the product developer to synthe-size new ideas following the inspiration of genomics.

In 2004, the elements set for InnovAidOnline were prepared, and werelaunched in 2005. A screen shot of the different studies appears in Fig. 1,which shows only a partial list. The full set of elements was made available ona Web site (www.innovaidonline.net). Demonstrations of the approach weremade at different conferences, using data from cookies, consumer electronicsand cosmetics. In all the presentations, the key message that resonated amongthe audience was the need to develop a system that could help create newproduct ideas by cutting and pasting little “idealets” or components, such as

FIG. 1. SCREEN SHOT OF INNOVAIDONLINE DATABASES AVAILABLE IN 2005


http://www.innovaidonline.net

the elements in the InnovAidOnline database. To the degree that the conceptelements came from the same or very similar product categories, the genomic“splicing” of these concept elements in InnovAidOnline would resemble con-ventional conjoint analysis, which searched for a better product. The degreethat the concept elements in the same experiment or test study came from“different product categories,” the genomic splicing of these elements wouldresemble true genetic changes, akin to splicing of DNA strands from differentspecies. It is worth mentioning that 2005 did not represent the first time thesethoughts about genomics and conjoint had been presented. As noted earlier, thesenior author presented such ideas over a decade in a number of conferences(e.g., Moskowitz 1999; Moskowitz et al. 2002c; Moskowitz et al. 2005b), withthe ideas appearing in different books (Moskowitz 1995) and publishedarticles (Moskowitz 2001).

EXEMPLIFYING ASPECTS OF THE NEW GENOMICS ORCOMBINATORIAL SCIENCE USING COSMETICS

Case histories are often a good way to illustrate new ideas because thecase history takes the approach from early stage thinking to a worked examplewith testable results. We will illustrate the Mind Genomics approach usingdata from a small demonstration with cosmetics. Cosmetics constitute a main-stay of consumer-packaged goods. With the fierce competitive environmentworldwide, unpredictability of styles and fads and expense of marketing andmerchandising products in this ever-changing environment, anything that canhelp better create new ideas will be welcome to the enterprising businessperson.

The objective of the case history was to synthesize a new product, theelectronic color palette, which could help a user identify the optimal colors fordifferent cosmetic products. The ingoing hypothesis was that a synthesis ofcosmetics and electronics represents a new thrust for companies looking todifferentiate in a competitive market.

The first three studies dealt with lip cream, eye shadow and skin colorsensor, respectively. The main objective of the first three studies was todevelop a small database of features that interested consumers. The fourthstudy, dealt with here later, synthesized a new-to-the-world combination offeatures by splicing together ideas from different products into a new “whole.”The two-phase exercise would demonstrate both the approach to developingthe database, and the synthesis using genomics-inspired recombination ofelements. The knowledge development tool was a research method for iden-tifying the response to concept elements presenting entire concepts to theparticipants, and using statistical analyses (design, regression) to estimate thecontribution (Moskowitz et al. 2001).

273MIND GENOMICS

Step 1: Silos and Elements

The elements are at the heart of the study. For the three studies, eachelement could be classified as belonging to one of six silos, as shown inTable 1. The same set of six silos applied to each of the three studies.

Step 2: Experimental Design

Each of the studies generated a unique set of 400 experimental designs,all of which were permutations of the same basic design (Moskowitz andGofman 2005). The basic design comprised 48 combinations of the 36 ele-ments, such that each element appeared independently of every other element,an equal number of times, against randomized combinations. This strategyensures that no particular combination of two elements can unduly influencethe results. Thus, if a pair of elements synergize so that the combination doesmuch better or worse than expected, such an interacting pair appears for onlysome of the time across the many combinations and thus, its impact on the datais minimal. With the approximate 100–130 panelists participating, the permu-tation strategy ensured that each person would be presented with a unique setof combinations, although the person would always test all of the individualelements.

Step 3: Field Execution

A total of 6,000 invitations were sent to individuals who had previouslyindicated that they would like to participate in these types of studies. Theinvitation presented all three studies, from which the participant could chooseone that was most interesting. The individuals were given a relatively narrowtime slot to participate (4 days), which decreased the standard rate of 9% inthese types of studies to a slightly lower response rate of 6%. The color sensorstudy generated 117 completes of 175 log-ins, the lip gloss study generated

TABLE 1.THE SIX SILOS FOR EACH PRODUCT

Silo Topic of silo

A What it is? (product definition)B Who will use it, for whom is it designed?C Mode and ease of useE Features and benefitsE Additional features (add-ons, special characteristics)F Where is it sold, how it is merchandised, where do you

find it?


127 completes of 171 log-ins and the eye shadow study generated 125 of 193log-ins. The actual invitation appears in Fig. 2. Note that the invitation iscouched in a way that invites participation, rather than presenting the invitationto research as a clinical exercise. Such warm, colloquial-phrased invitationsgenerate higher response rates among consumers because they invite partici-pation and collegiality in a nonjudgmental, nonthreatening language.

When participants clicked on the embedded link, they were led to theinterview, which began with an introduction to the study. The introduction tothe participants appears in Fig. 3, for the color sensory study. A similar orien-tation page was constructed for the lip cream and eye shadow studies, albeitparticularized to the topic. The orientation page focuses the participant’s mindon the task, introduces the rating scale and offers an incentive (sweepstakes).Such incentives increase the rate of participation.

The test stimuli comprise short, easy-to-read concepts, similar to the textconcepts shown in Fig. 4. With 60 combinations to evaluate, each elementappears thrice and is absent 57 times. The participants in the study mayrecognize that they have seen some of the elements before in other conceptsbut generally are not aware that they are seeing systematically varied concepts,

FIG. 2. THE INVITATION TO PARTICIPATE IN THE EVALUATION

275MIND GENOMICS

or even if they are, it is virtually impossible for any participant to understandthe underlying structure. Thus, the participants are reduced to answering on thebasis of their intuitive response, rather than trying to “game the system.”

Step 4: Basic Results

Each participant evaluated 48 different combinations, for eye shadow, lipcream or color sensor, respectively, using an anchored 1–9 rating scale (seeFig. 4 for an example of the scale). The ratings for each participant areconverted into a binary response, with original ratings of 1–6 converted to thevalue “0,” and ratings 7–9 converted to the value “100.” The conversionchanges the focus from the intensity of the participant’s feeling about theproduct to membership in the class of “concept acceptors” (7–9 or 100), ormembership in the class of “concept rejecters” (1–6 or 0). Such focus onmembership diminishes some of the metric information in the data, but con-forms to the conventions of consumer research, which is interested in groupmembership. It is important to keep in mind that with 48 concepts presented to

FIG. 3. THE ORIENTATION PAGE PARTICULARIZED FOR A “NEW COLOR SENSOR” (ONEOF THE THREE PROJECTS IN THE FIRST PHASE)


each person, every individual may for one concept be considered an “acceptor”because of the rating of 7–9, and yet for another concept be considered a“rejecter” because of the rating of 1–6. That is, acceptance/rejection is con-tingent in response to an individual concept, not to the entire product.

The data for each participant are subject to regression modeling, which isperfectly valid for these types of results as each participant evaluated 48concepts set up specifically to be analyzed by regression modeling. The experi-mental design ensures that all 36 elements are statistically independent of eachother.

The results of the study are shown in Table 2, from the entire set ofparticipants. The results can be interpreted quite simply as follows.

Modeling. The model is a simple, intuitively obvious and understand-able additive equation of the form:

Rating = k k k k 0 + + 1 2 36 (1)

where k0 is the additive constant (the expected value of the rating when ele-ments 1 to 36 are all 0), and k1, k2 and k36 are elements 1, 2 and 36, respectively.

Individual-Level Analysis. Each person generates her own additivemodel for the study in which she participated.

FIG. 4. EXAMPLE OF A CONCEPT COMPRISING FOUR ELEMENTS

277MIND GENOMICS

TABLE 2.PERFORMANCE (UTILITY VALUE) OF THE 36 ELEMENTS AND THE ADDITIVE

CONSTANT FOR THE THREE PRODUCTS

Eye shadow Lip cream Color sensor

Base size (number of participants in the study who completed the interview)125 127 117

Additive constant (basic interest in idea without elements)43 61 48

Silo A – what is it? (product definition)A dazzling collection of

six perfectlyharmonized eyeshadows . . . bring outthe best in your eyes

8 Long-lasting color andshine in a compactportable palette

4 A color detector designedto mix and matchcolors

0

A racy palette with sixdramatic shades in oneslim compact

6 Moisturizing, long-lastinglip color . . . perfect forany skin tone

2 Find the perfect matchwith a personal colordetector . . . superiorcolor capabilities rightat your fingertips

-1

Six perfectly coordinatedshades at your disposal. . . to create an endlessnumber of stunninglooks

5 A sassy array of lipcream color . . . thequickest way tobrighten up your face

1 A high-resolution colordetector withshade-matchingcapabilities

-1

A splendid array of eightshimmering shades. . . to brighten andenliven your eyes

5 A colorful array ofexquisite and versatilelip colors . . . wear oneshade alone or innumerouscombinations

0 Color-matchingtechnology driven by ahigh-power colordetector

-2

A range of brilliantcolors in one handycompact . . . thepossibilities areendless

3 A lip cream that blendscaptivating color anddelicious flavor . . . amust-have for anyspecial occasion

-3 A pocket-size colordetector . . . to helpidentify the rightcolors

-2

Six-color combina-tion . . . designed toenhance and bring outyour natural eye color

3 Ravishing lip cream thatis easy to layer andblend . . . make acolorful impression

-4 A pocket-size device thatdetects colors that arebest matched together

-3

Silo B – who will use it, for whom is it designed?Perfect to wear day and

night . . . perfect forany occasion

2 For the woman who isalways on therun . . . easy to usewherever you are

0 Ultrareliable . . .state-of-the-arttechnology forscientists, productionmanagers and otherprofessionals

1

When you do not have alot of time . . . theperfect way toaccentuate your eyes

1 Perfectly poutedlips . . . lets the classicwoman release thedramatic side

0 A sophisticated devicethat lets the intellectenrich his or her life

0


TABLE 2.CONTINUED


For the professionalwoman . . . a surge ofcolor to brighten upyour eyes

0 For those who like anatural look withbeautiful color . . .enhance your look injust a few seconds

0 For anyone who wants toadd more color to theirlife . . . the possibilitiesare endless

0

Lets the classic womanrelease the dramaticside . . . all in the blinkof an eye

-4 For the woman wantingto make a personalizedstatement reflective ofher identity

-1 Lets the professionalbring more color intothe office

-2

For the girl who cannotcommit to one eyeshadow

-5 Potent color andluxurious feel . . . forthe daring andseductive woman

-2 A pleasing gift for theartist and technologyfanatic alike

-2

Perfect for the refinedwoman wanting tomake an elegantstatement at the socialevent of the year

-6 Ideal for the refinedwoman wanting tomake an elegantstatement at the socialevent of the year

-8 For the technology-savvyindividual looking fora new toy

-4

Silo C – mode and ease of useIt is easy to blend colors

to achieve the desiredlook

6 Would not smudge, runor transfer . . . so youcan eat, drink and kisswithout having toreapply

7 Easy to use . . . great forany color needs

1

Easy to apply, easy toremove . . . beauty in amatter of seconds

6 Mix, layer, lighten orintensify . . . achievethe perfect shade forevery occasion

4 Small and lightweight. . . fits perfectly into

your back pocket

0

Wear each shade alone,or combine shades toturn everyday eyesinto irresistible eyes

2 Find a color that is rightfor you by mixing twoor three shadestogether . . . bring outyour inner artist

-2 Complex technologywith simplisticapplication . . . getprecise results with thepush of a button

0

Wear each shade alone,or mix and match afew for a unique look

1 Versatile shades to wearfor a day at work or anight on the town

-2 Just 4 oz and batterypowered . . . take itwith you wherever youroam

-1

Try mixing a couple ofshades together tocreate a new favorite

1 Juicy lips with brilliantcolor . . . create arunway look in onestroke

-2 Small enough to fit in thepalm of your hand. . . good things docome in small pack-ages

-2

Each shimmering colorcan be worn alone orlayered to achieve amultitude of excitingshades

0 A fuss-free formula forlips with an easy andprecise brush applica-tion

-2 Easy input and fastresponse . . . no morewasting time wonder-ing if your color coor-dination is right

-3

279MIND GENOMICS

TABLE 2.CONTINUED


Silo D – features and benefitsThe 18-h long-wear eye

shadow that would notsmudge, run or fade

11 Satin feel and finish . . .for creamy,moist-looking lips

6 Small light beams cansense the differencebetween matte andglossy, and detect thefinest nuances in color

5

Shimmery color kisseslids . . . adds a bit ofglamor to your look

9 Hydrating gel drencheslips . . . lips feelmoisturized even afteryou take it off

4 Accurate colordifferentiation . . .match colors asprecisely as possible

2

Made withhypoallergenicingredients for contactwearers and sensitiveeyes . . . dermatologist-andophthalmologist-approved

8 Sheer color with theperfect hint ofshimmer and shine

3 Connects to yourcomputer, personaldigital assistant and avariety of otherdevices . . . the perfectcolor companion

1

Rich, long-wearing andcrease-free . . . youreyes deserve the best

8 Silky soft lip cream . . .set the stage forintrigue

0 High resolution andaccuracy . . . easily andprecisely distinguishbetween shades ofcolors

0

The perfect way tocontour, highlight anddefine eyes . . . addsthe final touch to yourappearance

6 High gloss finish . . . fora fresh and flirty lookfor your lips

-2 Utilizes over a billionhues of color . . .discover the perfectshade with ease

0

Ensures long-lastingluminous color todefine your eyes in anylighting situation

6 Semimatte finish . . . forvelvety, full-bodiedlips

-4 The latest technology todetect and matchcolors beyond therange of human vision

-1

Silo E – additional features (add-ons, special characteristics)Enhanced with alpha

hydroxy and fruit acids. . . improve skin’stexture

4 Formulated with retinolto visibly reduce liplines . . . and collagenfor visibly fuller lips

1 Additional removablememory chip storesshades and hues . . .so you can keep all thecolors you create

2

With a unique blend ofoil-free moisturizers. . . so your eye lids

feel silky smooth

4 Enhanced with sunprotection factor 15. . . gives your lips theutmost protection

-1 So reliable, it comes withan extended 10-yearwarranty

0

With a bonus brush forerror-proof application

3 Enriched with vitamin Eand aloe . . . increasewearability and keepthe color true

-2 With an additional carcharger . . . so you cancharge and go, alwaysthere when you need it

-1


Summary Data. The results can be summarized for the total panelsimply by averaging the individual components of the model (additive con-stant, 36 utilities) across all the participants. Thus, for eye shadow with 125participants, the average comes from all 125 participants. Each part of theadditive model is the average of the corresponding, individual set of 125equations, one equation per participant. Thus, the additive constant is the

TABLE 2.CONTINUED


Enhanced withmicrocrystal sparkles. . . to give your eyes asugar-coated sheen

0 Made from shea butterand aloe . . . conditionlips while envelopingthem inhigh-pigmented color

-2 Comes with arechargeable battery. . . for a seeminglyendless life

-1

A bonus leather casekeeps it clean andprotects it from heat

0 Infused with lightreflectors for aluscious, full-colorshine

-3 Sits safely in a cushionedcase . . . keeps it out ofharm’s way

-1

Pearl extract addsbrilliance andluminosity to lids

-3 Nondrying formula isenriched withemollients . . . soften,soothe and pamperyour lips

-4 Energy-savingtechnology . . . get thejob done withoutharming theenvironment

-2

Silo F – where is it sold, how it is merchandised, where do you find it?Available at your neigh-

borhood drug store11 Available at your local

drug store-3 Find it in the electronics

section of departmentstores nationwide

0

Find it in the beautysection of departmentstores nationwide

-1 Find it in the beautysection of departmentstores nationwide

-8 Available at electronicretail stores like BestBuy

-3

Buy it directly from themanufacturer’s onlineWeb site

-13 Available at beauty retailstores like Sephora

-23 Available at your neigh-borhood technologyand electronics dealer

-5

Available at beauty retailstores like Sephora

-14 Buy it directly from themanufacturer’s onlineWeb site

-25 Buy it directly from themanufacturer’s onlineWeb site

-10

Purchase through a mail-order catalog and haveit delivered right toyour door

-14 Purchase through a mail-order catalog and haveit delivered right toyour door

-25 Purchase through a mail-order catalog and haveit delivered right toyour door

-14

Purchase with the aid of apersonal sales repre-sentative in the comfortof your home

-27 Purchase with the aid of apersonal sales repre-sentative in the comfortof your home

-35 Purchase with the aid of apersonal sales repre-sentative in thecomfort of your home

-17

All data come from the total panel of participants for each study. Elements are sorted within a silo frombest performing to worst performing.

281MIND GENOMICS

average of all 125 additive constants, etc. Such summarization generates astable estimate that can be compared across elements within a silo, across siloswithin a study and across studies comprising different elements.

Explicating the Additive Constant. The additive constant for eyeshadow, as an example, is 43. This means that without any elements beingpresent for eye shadow, approximately 43% of the participants would beinterested in the product, i.e., would rate the concept 7–9 on the scale. Theadditive constant is, of course, a calculated parameter as every concept com-prised 3–4 elements. Despite its origin as a calculated value, the additiveconstant still has intuitive meaning as a baseline.

The Additive Constant in Light of the Nature of the StudyParticipants. Keep in mind that these participants are self-selecting, becausethey know from the invitation (Fig. 2) that the study would deal with women’shealth and beauty aid (HBA) products. We can compare this additive constant ofeye shadow to the additive constant for lip cream (61) and to the color sensor(48). Lip cream is more interesting. Part of the ingoing “vision” of MindGenomics is simply to obtain normative databases for such product areas.

Explicating the Element Utilities. The 36 individual elements, fallinginto the six silos, give us another sense of the product ideas. Let us first look ateye shadow. There are some very strong-performing elements, but not many.Recall the definition of the element as the conditional probability of a partici-pant being interested in the product (i.e., switching from a rating of 1–6 denotingnot interested, to a rating of 7–9 denoting interested). A strong element is: “The18-hour long-wear eye shadow that won’t smudge, run or fade.” Another strongelement is: “Available at your neighborhood drug store.” Both elementshave utility values of +11, which from previous studies would suggest a verystrong-performing idea. Indeed, with so many elements mixed and matchedagainst different backgrounds, it is virtually impossible for a weak-performingelement to do well by “accident.” There are too many variations.

Not Every Idea Does Well. Silo B, which deals with “ease of use” and“who will use it,” clearly shows some poor-performing ideas with negativeutilities, such as “Perfect for the refined woman wanting to make an elegantstatement at the social event of the year.” This element has a utility of -6,meaning that when it is added to the concept, the interest goes down.

Using Normative Data or Benchmark Results. The normative datafrom these types of studies suggest that the really strong elements perform 15or higher, strong elements perform 10 or higher and good but not great


elements perform 6 or higher. For the most part, the elements only performmodestly (around 0–5). Such modest performance for the total panel is to beexpected if the elements attract some groups of individuals but repel othergroups. We will see this type of segmentation into some groups that like andother groups that dislike the elements in the next section.

Step 5: Looking for Key Segments or “Mind-Sets” in a World Awashwith Choice

In the past 40 years, marketers have become increasingly aware thatpeople have different ways of looking at products and communications. Whatone person likes, another person may dislike. The differences in what peoplelike cannot easily be traced to geodemographic differences.

Let us first look at the traditional marketing methods for segmentation.Marketing approaches believe that the researcher should ask the participantmany questions about goals, lifestyles and the like. From the patterns of answersit should become possible, at least in traditional thinking, to identify differentgroups of people with radically different ways of looking at the world. Presum-ably, differences in the grand scheme of the way a person approaches the worldshould translate into more specific differences for almost any product. Thus, inthe mind of the marketer, the segmentation is identical with people. People aredifferent, and the goal is to divide up people into these homogeneous clusters.Only afterward does the marketer deal with these clusters, one cluster of peopleat a time, whether this is with a new product or a new positioning.

Attempts to classify the population into like-minded groups, separatefrom conventional geodemographics, go back at least 30 years (Wells 1975),with popular interest in such segmentation generating a best-selling businessbook (Mitchell 1983), and moving into commercial applications (e.g., theVALS or Value & Lifestyle Survey from SRI Consulting, Inc.). Such attemptsrepresent some ways in which marketers and other students of social behaviorconceive of differences among individuals.

The approach of Mind Genomics to segmentation comes from a world-view different from the more conventional marketing approaches. The ingoingassumption of Mind Genomics is that there exist segments in the population,much as the traditional marketer might believe. However, these segments maynot be general. They do not cross over different categories. These segmentsmanifest themselves simply as patterns of responses to concepts. Those threeassertions about segments radically differ from the overarching approachesimplicitly (and often explicitly) promoted by marketers.

Mind Genomics holds that the segmentation is momentary, opportunistic,limited to a particular product category and emerges from differences inresponses to the stimuli being tested. It may be, however, that we find segments

283MIND GENOMICS

that apply from one product category to another, such as the individuals wholike elaborate descriptions of foods (so-called “Elaborates”) versus those wholike traditional descriptions of food without being fancy (so-called “Classics”),and finally those individuals who like foods described in nonfood language(so-called “Imaginers”; Beckley and Moskowitz 2002; Moskowitz et al.2005a). A similar three-segment division of participants occurred for bever-ages as well in the Drink It! databases (Moskowitz et al. 2005c). It is just anaccident, however, that these three segments apply to many foods. Further-more, even if the same segment appears from one food to another does notmean that an individual once a member of a segment such as Elaborate,remains a member of this self-same segment (i.e., Elaborate) his whole life,and across all foods. “Thus, segmentation is a convenient way to divide thefoods, and responses to them.” It is a segmentation limited to a single product,which may or may not represent a general way people divide.

The second point is that these segments are emergent groups, comingfrom the response to a set of concepts. “Segments in Mind Genomics representdifferent types of ideas held by people, revealed by the pattern of response ofthese people to concepts. The segments may or may not represent actualpeople.” The difference between segments as defining people and segments asdefining ideas held by people is subtle but important. Marketers and in actu-ality most people believe in the existential validity of the segment as a groupof people who can be pointed at. Mind Genomics holds that the segments aredifferent sets of ideas, emerging from responses to concepts, with peoplepossibly falling into one set or one segment with greater probability thanpeople falling into the other set of ideas or segment. Thus, in some ways, MindGenomics holds that that the segments are a probabilistic entity, similar inmany ways to the paths of electrons around an atomic nucleus in the waytoday’s particle physics thinks of the paths. The paths are only probabilities,states, rather than fixed locations. Mind Genomics segments are only collec-tions of related ideas that can be occupied by a person.

Segments emerge from standard statistical analysis of the patterns ofutilities at the individual participant level. The utilities used for segmentationare the so-called “persuasion utilities,” which are the regression coefficientsfor the different elements (but not the additive constant) estimated at anindividual-by-individual basis before any binary transformation. The segmen-tation is accomplished by simple, well-accepted methods, such as first definingthe distance between pairs of participants by a distance measure (e.g., the value[1 – Pearson’s correlation]), and then using that distance measure to put peopleinto different groups such that people in the same group or segment are “closeto each other,” and people in different segments are “far away from each other.”

The reality of these segments is in the fact that they make sense, emergein similar ways time after time in different studies almost like archetypes, and


can be used to create product ideas and more powerful communications. Thesegments have to be understood by the pattern of the ideas that they comprise.We have to stand back to see the nature of the segment itself. Most of the time,we will see the segments emerge simply as a set of related elements, scoredwell by a subset of individuals in a study.

Armed with this way of thinking about segments as common, related setsof ideas that emerge from the pattern of utilities for different participants, letus investigate our three different HBA products (lip cream, eye shadow andskin color sensor). We segmented the participants in each study into threegroups. The segmentation or clustering is a formal statistical operation. Withthese data, let us see what elements do well.

The data for each of the studies were separately analyzed, with theparticipants put into segments based on the pattern of their individual utilities.We looked at the three segment solutions for each product to see whether wecould create three general segments, transcending a specific product type. Thisattempt at creating super segments somewhat stretches the meaning a bit foreach segment, but the approach allows us to treat the data in a more directfashion. The super segmentation is not necessary, simply convenient. The threeemerging general segments appearing in Table 3 are the following:

(1) Segment 1 – interested in short messaging, basic benefits, best-performingelements only have modest utility;

(2) Segment 2 – interested in extra features, “techie”;(3) Segment 3 – what can be accomplished with the technology.

It is important to keep in mind that the real goal of segmentation here is to finddifferent segments of people’s mind-sets, rather than identifying any indi-vidual as belonging to one of these three segments. That is, we are using thesegment to identify these mental archetypes in the cosmetic area. Thus, thesegmentation approach proposed in Mind Genomics represents a crossoverbetween conventional segmentation done by marketers and archetype-basedthinking done by psychoanalysts (Wertime 2003). The segmentation is anoperationally straightforward, defined method for uncovering these archetypesor locations of mind-sets. The segmentation involves the way the mind orga-nizes the information, rather than the way people divide into groups. Such anapproach using conjoint analysis and segmentation as a method for identifyinglocations of ideas in a mind space rather than people appears to have been firstpromoted in the automobile sales business by Moore and Moskowitz (2002).

Step 6: Selecting “Idealets” to Recombine into New Products, andRunning the Fourth (Recombinant) Study

The objective of recombining is to create newer and better concepts, notnecessarily for a single product, but even perhaps for a new-to-the-world

285MIND GENOMICS

TABLE 3.WINNING ELEMENTS FOR THREE SUPER SEGMENTS DEVELOPED FROM THE

COSMETIC DATA

Study Super segment and element Utility

Segment 1 – interested in short messaging, basic benefits, best-performing elements only havemodest utility

Eye Available at your neighborhood drug store 8Lip Long-lasting color and shine in a compact portable palette 8Eye The 18-h long-wear eye shadow that would not smudge, run or fade 7Lip Would not smudge, run or transfer . . . so you can eat, drink and kiss without

having to reapply7

Color Small light beams can sense the difference between matte and glossy, and detectthe finest nuances in color

6

Segment 2 – interested in extra features, “techie”Eye Available at your neighborhood drug store 29Color With an additional car charger . . . so you can charge and go, always there when

you need it20

Eye A bonus leather case keeps it clean and protects it from heat 20Eye Find it in the beauty section of department stores nationwide 20Eye With a bonus brush for error-proof application 19Color Comes with a rechargeable battery . . . for a seemingly endless life 18Color Sits safely in a cushioned case . . . keeps it out of harm’s way 18Color Find it in the electronics section of department stores nationwide 18Eye Buy it directly from the manufacturer’s online Web site 18Eye Enhanced with alpha hydroxy and fruit acids . . . improve skin’s texture 18Color Additional removable memory chip stores shades and hues . . . so you can keep all

the colors you create16

Color So reliable, it comes with an extended 10-year warranty 16Eye Pearl extract adds brilliance and luminosity to lids 15Eye With a unique blend of oil-free moisturizers . . . so your eye lids feel silky smooth 15Lip Satin feel and finish . . . for creamy, moist-looking lips 15Lip Buy it directly from the manufacturer’s online Web site 11Lip Moisturizing, long-lasting lip color . . . perfect for any skin tone 11Segment 3 – what can be accomplished with the technologyColor Small light beams can sense the difference between matte and glossy, and detect

the finest nuances in color31

Lip For the woman wanting to make a personalized statement reflective of her identity 31Color Utilizes over a billion hues of color . . . discover the perfect shade with ease 30Lip Perfectly pouted lips . . . lets the classic woman release the dramatic side 30Color The latest technology to detect and match colors beyond the range of human

vision26

Lip Would not smudge, run or transfer . . . so you can eat, drink and kiss withouthaving to reapply

25

Color Connects to your computer, personal digital assistant and a variety of otherdevices . . . the perfect color companion

24

Eyes Shimmery color kisses lids . . . adds a bit of glamour to your look 23Color Available in your neighborhood technology and electronics dealer 22Color For the technology-savvy individual looking for a new toy 22


product. Our three studies on skin color sense, eye shadow and lip gloss allowthe developer to create such a recombinant idea. We begin with a basicpositioning statement – namely a product that allows the user to understandtheir skin tone, the appropriate eye shadow, and appropriate lip cream. We donot necessarily know what this product will be – as there are no rules for anew-to-the-world product. However, we can present winning “idealets” fromthe three studies, as shown in Table 3. These “idealets” win among differentsegments.

The second stage of the project comprises a new study, this time with 36elements, selected from winning ideas in the first phase, but selected from thethree initial (i.e., basic) studies. Let us now put these “idealets” into anunderlying structure or architecture as we did for the basic study, and testcombinations of these “idealets” as we did before. We simply introduce thenew product idea by the basic positioning statement, not forcing the participantinto any predefined mental framework. We then present different, systemati-cally varied combinations of these elements. The combinations are mixed and

TABLE 3.CONTINUED

Study Super segment and element Utility

Eyes A dazzling collection of six perfectly harmonized eye shadows . . . bring out thebest in your eyes

21

Eyes A racy palette with six dramatic shades in one slim compact 21Lip Juicy lips with brilliant color . . . create a runway look in one stroke 20Color Accurate color differentiation . . . match colors as precisely as possible 18Lip For those who like a natural look with beautiful color . . . enhance your look in

just a few seconds18

Eyes The perfect way to contour, highlight, and define eyes . . . adds the final touch toyour appearance

17

Lip Potent color and luxurious feel . . . for the daring and seductive woman 17Eyes Rich, long wearing and crease-free . . . your eyes deserve the best 16Color High resolution and accuracy . . . easily and precisely distinguish between shades

of colors15

Color Find it in the electronics section of department stores nationwide 15Eyes Perfect to wear day and night . . . perfect for any occasion 15Lip Purchase with the aid of a personal sales representative in the comfort of your

home15

Lip For the woman who’s always on the run . . . easy to use wherever you are 15Color Purchase with the aid of a personal sales representative in the comfort of your

home14

Color A pocket-size color detector . . . to help identify the right colors 14Eyes Made with hypoallergenic ingredients for contact-wearers and sensitive eyes . . .

dermatologist- and ophthalmologist-approved14

Eyes The 18-h long-wear eye shadow that would not smudge, run or fade 14

Elements are sorted in descending order by utility value.

287MIND GENOMICS

matched. The positioning statement ensures that the participant knows that theproduct idea deals with a personal electronic makeup palette, which is intro-duced by the text shown in Fig. 5.

In the actual study, a total of 6,000 “new” participants were invited byemail, with 260 individuals participating. Time frames dictated completing thestudy within 72 h, which decreased the response rate to 4.3% of the invitees.Each new participant evaluated a unique set of 48 combinations, much in theway that the previous participants had evaluated a unique set. The 36 elementscame from the three different studies so that the orientation and rating questionhad to be couched in general terms. Keep in mind that the participants had noidea that the elements were really abstracted from previous studies; all theyknew was that they were evaluating a presumably “reasonable” idea based onthe introductory positioning. The participants were again segmented into threegroups to identify different mind-set positions.

The partial results for the study appear in Table 4, which shows theperformance of the winning elements for the three segments developed fromthe new data. We tried to use the same names that were used for the first partof the study, although there were some differences, especially in Segment 1. Inthe first set of studies, Segment 1 comprised individuals interested in shortmessaging and basic benefits, whereas in the fourth (spliced elements) study,this segment comprised individuals interested in bottom-line performance.Such a study to examine variation in segmentation should not surprise, giventhe differences in positioning and elements.

FIG. 5. THE ORIENTATION PAGE FOR THE ELECTRONIC MAKEUP PALETTE (PHASE 2)


TABLE 4.RESULTS FROM THE SECOND PHASE (FOURTH STUDY), WITH ELEMENTS SELECTEDFROM THREE DIFFERENT PRODUCTS, BUT WITH THE CONCEPT POSITIONED SIMPLY

AS AN “ELECTRONIC PALETTE”

Total Concept response segment

Perform Techie Usage

100% 42% 26% 32%260 109 68 83

Additive Constant 36 39 12 51Segment 1 – bottom-line-oriented – super performanceUtilizes over a billion hues of color . . . discovers the perfect

shade with ease2 12 0 -9

The 18-h long-wear eye and lip colors that would not smudge,run or fade

7 11 11 -2

The latest technology . . . detects and matches colors beyondthe range of human vision

5 9 12 -5

Segment 2 – interested in extra features, “techie”Additional removable memory chip stores shades and hues

. . . so you can keep all the colors you create5 7 24 -13

Buy it directly from the manufacturer’s online Web site -1 -11 17 -4A bonus leather case keeps it clean and protects it from heat 5 7 16 -7Sits safely in a cushioned case . . . keeps it out of harm’s way 0 -1 15 -13Find it in the beauty section of department stores nationwide 3 2 15 -6Available at your neighborhood drug store 5 2 14 1With an additional car charger . . . so you can charge and go,

always there when you need it1 -1 14 -8

Available in your neighborhood technology and electronicsdealer

-8 -15 14 -17

So reliable, it comes with an extended 10-year warranty 7 8 12 2The latest technology . . . detects and matches colors beyond

the range of human vision5 9 12 -5

Comes with a rechargeable battery . . . for a seemingly endlesslife

2 4 11 -9

The 18-h long-wear eye and lip colors that would not smudge,run or fade

7 11 11 -2

Find it in the electronics section of department storesnationwide

-7 -11 11 -16

Accurate color differentiation . . . match colors as precisely aspossible

0 0 11 -8

Small light beams sense the difference between matte andglossy, and detect the finest nuances in color

3 4 10 -5

Moisturizing, long-lasting eye and lip color . . . helps you findthe perfect shades for any skin tone

7 7 10 4

Perfectly pouted lips and bright, striking eyes . . . lets theclassic woman in you release your dramatic side

5 7 9 1

Long-lasting color and shine in a compact portable palette 6 5 8 5A dazzling collection of eye shadow and lip cream colors . . .

brings out the best in your lips and eyes3 2 8 -2

289MIND GENOMICS

Step 7: Identifying Interactions among Pairs of Ideas to Prevent PoorCombinations

Before creating a new combination of ideas by splicing together compo-nents, it is important to determine whether the combinations “work” togetheror not. Some combinations make intuitive sense while some do not. Thesecombinations may be identified ahead of time and specified as pairwise restric-tions. However, there are many combinations that just do not seem to “work”together, even though there is no reason, a priori, to assume that they wouldfail to work. It may be that to participants in the study, the combinations arecounterintuitive, or clash with each other, even though one would never haveguessed.

Fortunately, the permuted, main-effects experimental designs used inthese studies allow the discovery of significant interactions, both of positiveand negative natures. The approach is quite simple, uses the principles ofstatistics and follows these steps to quickly reveal which combinations dobetter than expected and which combinations do worse:

Data Preparation. Line up all of the raw data, comprising rows of 36columns (one per concept element) and a 37th column corresponding to therating on the 9-point scale. With 48 concepts per participant and with 260participants, there are 12,480 rows.

“Interest” Measure. Create the 38th column corresponding to interest,where interest takes on the value 100 if the rating is 7–9 to denote interest, ortakes on the value 0 if the rating is 1–6 to denote lack of interest.

Create All Pairs of Elements from Each of the Two Silos. There are sixsilos, A–F, so there are 15 pairs of silos ([6 ¥ 5]/2 = 15). For each pair of silos,

TABLE 4.CONTINUED

Total Concept response segment

Perform Techie Usage

Segment 3 – what can be accomplished with the technologyEasy to apply, easy to remove . . . beauty in a matter of seconds 8 7 4 11Mix, layer, lighten or intensify . . . achieve the perfect shade 5 7 -6 10Brilliant color . . . create a runway look in one stroke 4 4 -2 9A pocket-size makeup palette with a built-in color detector

. . . helps you identify the right colors6 4 5 8

Makeup you can wear all day without having to reapply 6 8 1 8

Only “winning” elements are shown for each segment.


there are 36 pairs of elements (e.g.,A1 . . . A6 crossed with B1 . . . B6 generates36 combinations). Therefore there are 15 ¥ 36 or 480 pairs of elements.

Identify What Pairwise Interactions Covary with Interest. Computethe Pearson’s correlation (or other measure of association) between eachelement pair and the interest value. There are 480 of these correlations, one perelement pair.

Rank Order These 480 Interactions, and Consider Only Thosewith Strongly Significant Positive Correlations (�0.025) and NegativeCorrelations (�-0.025). These are the combinations that synergize so thatthe combination of elements does far better than chance, or combinations thatsuppress so that the combination does far worse than chance. These seeminglow correlations are, in fact, quite significant when one realizes they arecomputed using 12,000+ observations.

Use the Negative Correlations as Constraints. When it is time toidentify winning combinations, make sure that no poor scoring combinationsenter. These would prevent combinations of elements that might perform wellalone, but do not do well together.

Table 5 shows these synergistic and suppressive combinations for thetotal panel. Only the most significant pairs are shown.

Step 8: Synthesis of New Ideas Using a Recombinant Optimizer

A key benefit of genomics-based thinking is that ideas can be recombinedinto newer and possibly better combinations. The splicing of ideas alreadyexists in the basic design of the research, where the elements are treated asindividual pieces, and recombined by the computer program during the courseof the interview. Once the utility values of these individual ideas are identified,it becomes possible to further recombine the winning ideas into yet newerconcepts by mixing together winning ideas. The analysis of interactions dis-cussed earlier (Table 5) will warn whether or not the combinations that lookpromising on the basis of individual elements have a negative utility whencombined. Judgment works as well, indeed in parallel with statistics, whendeciding what combinations of optimal elements make business sense.

We can get a sense of optimization by looking at concepts created on thebasis of high-performing elements. The instructions to optimize appear inFig. 6A, which shows the objective – maximize the total acceptance of athree-element concept, for total panel. The first combination appears inFig. 6B (concept itself) and Fig. 6C (so-called “diagnostics” of the concept,showing how the elements contribute to the rating). Let us dissect the resultsfrom the concept optimizer as follows.

291MIND GENOMICS

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FIG. 6. (A) INSTRUCTIONS TO OPTIMIZE A THREE-ELEMENT CONCEPT, FOR TOTALPANEL. THE OPTIMIZER WAS CONFINED TO CONSIDERING THREE SILOS (C, D AND E)

TO CREATE A PRODUCT/MERCHANDISING CONCEPT. (B) SCREEN SHOT OF THEOPTIMAL CONCEPT CREATED FROM INSTRUCTIONS SHOWN IN (A). (C) DIAGNOSTICS

FOR THE OPTIMAL CONCEPT SHOWN IN (B). RESULTS SHOW THE EXPECTEDPERFORMANCE OF THE CONCEPT FOR TOTAL PANEL, AND TWO OF THE THREE

SEGMENTS. THE OPTIMIZER PROVIDES THIS TYPE OF PROFILE FOR ALLKEY SUBGROUPS (AGE, SEGMENT, ETC.). (D) OPTIMAL CONCEPT FOR

SEGMENT 2 (ADD-ONS)

295MIND GENOMICS

Structure of the Concept. The concept comprises only three elements,not six. The reason for this constraint comes from the fact that in the actualevaluations, the participants evaluated concepts comprising a minimum of threeelements and a maximum of four. Even though there were six categories, we

C

D

FIG. 6. CONTINUED


look only at the best set of elements with three categories, with only one elementfrom each category. The other three categories are missing. For this optimiza-tion, the three silos selected for the optimization were C (mode and ease of use),D (features and benefits) and E (additional features, merchandising).

How to Create the Combination. The combination is created withoutpaying attention to constraints that might be imposed from knowledge of howthe combinations of elements performed. However, we can check from Table5 whether the optimal combination comprises elements that do not worktogether. There are no combinations that would correlate negatively withinterest, suggesting that the three pairs of elements in the optimized conceptare compatible with each other. The pairs are C6–D2, C6–E5 and D2–E5,which we construct by knowing that the optimal combination comprises C6,D2 and E5 (see Fig. 6C).

Estimating the Total Interest in the Optimized Three-Element Con-cept. The individual utilities can be added to the constant. The sum is the totalutility or expected proportion of consumers who would be interested in thisnew combination, based on the universe of individuals who responded to thesurvey. The actual proportion in the total population would, of course, be lowerbecause the participants in the survey were already interested in participating,and may not reflect the rest of the nonresponding population.

How Well Does the Concept Score? The sum of the utilities is 57(Fig. 6C), coming from an additive constant of 36 and three utilities each ofvalue 7. The modest value for total panel should not surprise as the segmen-tation suggests that the population is not homogeneous. Rather, there aregroups with diverging interests, so what appears to one group of participantsmay be very unappealing to another. For this particular combination of C6, D2and E5, the concept scores are as follows:

(1) Total panel 57(2) Segment 1 (Techies) 65(3) Segment 2 (Performance) 39(4) Segment 3 (Usage) 62

Analyzing Subgroups. The same type of analysis may be done for anysubgroup or set of subgroups, forcing in any triple of silos, or even allowingthe computer to pick the silos based on the attempt simply to optimize interest.For example, if we concentrate on Segment 2 (Add-ons), we can generateanother combination, C6, D6 and E4. Its acceptance goes up from 39 to 52, atthe expense of acceptance by the other segments (see Fig. 6D):

297MIND GENOMICS

(1) Total panel 52 (down from 57)(2) Segment 1 (Techies) 62 (down from 65)(3) Segment 2 (Performance) 52 (up from 39)(4) Segment 3 (Usage) 44 (down from 62)

DISCUSSION

DOES THIS NEW APPROACH QUALIFY AS A SCIENCE IN THEWAY A DICTIONARY DEFINES SCIENCE?

The title of this article states clearly that the approaches presented hereconstitute a new science. Rather than belaboring the point, one way to dealwith the scope of the approach and to show how it is a science is to consult adictionary to see whether the approach fits into what might be conventionallycalled a science. Figure 7 shows a structured definition of the term “science”from WordNet 2.0 (Princeton University 2003). The term “science” is “theability to produce solutions in some public domain.” The examples includespecific disciplines, such as psychological science, metallurgy, etc.

Each of the sciences listed in Fig. 7 comprises both approaches and asubstantive body of knowledge. The science of Mind Genomics comprisesapproaches, some taken from statistics, some from the applied fields of con-sumer research and some from experimental psychology. However, MindGenomics does not stop there. Mind Genomics generates “archival results,”databases of ideas and their utility values, not just hypothesis tests. MindGenomics strives for databases that can be used again and again, whosecomponents can be compared, contrasted, combined into new things. That is,the data from these studies can become facts that one can combine to get apicture about the way the consumer works. Hypothesis tests, in contrast,simply evaluate whether an explanation about why something works (e.g., ahypothesis about the mechanism) is true or untrue.

TO WHAT EXTENT IS THE METHOD OF CONJOINT ANALYSISINTEGRAL TO THE SCIENCE OF MIND GENOMICS?

In the foregoing explication of this proposed new science, a great deal ofemphasis has been placed on the methods experimental design, specificallyconjoint analysis. More specifically, the form of conjoint analysis is theso-called “full profile conjoint analysis” where the participant evaluates com-binations of “idealets,” in which combinations are then deconstructed to thecomponent contributes. To what extent does this science simply equivalent to


the methods, in which case we are not dealing with a science at all, but ratherwith the use of the method to understand how people react to ideas?

The answer to the foregoing question is that the science comprises theunderstanding and systematization of components of ideas, and the rules oftheir recombination. The actual science itself combines both the method forgetting the information (experimental design) and the information itself (indi-vidual utilities).

Some research results lead to the choice of experimental design as apreferred method. Yet, the science does not depend on experimental design.One might instruct the participants to rate each of the elements rather thanrating complete more compound concepts (vignettes), but in such a case theindividual utilities might be flawed. It is well known that self-assessments ofimportance are often tremendously flawed, as shown in a comprehensive

ScienceA Noun

1 skill, scienceability to produce solutions in some problem domain; "the skill of a well-trained boxer"; "the sweet science of pugilism"

Category Tree: psychological_feature

cognition; knowledge; noesisability; powerskill, sciencevirtuositynose

2 science, scientific_disciplinea particular branch of scientific knowledge; "the science of genetics"

Category Tree: psychological_feature

cognition; knowledge; noesiscontent; cognitive_content; mental_objectknowledge_domain; knowledge_basediscipline; subject; subject_area; subject_field; field; field_of_study; study;

bailiwick; branch_of_knowledgescience, scientific_disciplinepsychology; psychological_sciencenutritionmetrologymetallurgyarchitectonics; tectonicsagrologyagrobiologyagronomy; scientific_agriculturemathematics; math; mathsnatural_science

FIG. 7. DEFINITION OF THE TERM “SCIENCE”Adapted from WordNet 2.0 Copyright 2003 by Princeton University.

299MIND GENOMICS

monograph presenting the results of more than 200 published articles onself-assessment (Dunning et al. 2004). A glaring example of these flaws, whichcould reduce the validity of utility values for individual ideas, comes from theobservation that the utility values of well-known brands are much lower inconcepts than the utility values of statements about product features (Mosk-owitz et al. 2005c). Even though brands are assumed to be very important,brand names, i.e., surrogates from brands, show relatively low utility valuesranging from -10 to +5, for literally dozens of well-known brands in studiesperformed both in the U.S.A. and Europe (Germany, France, UK), and amongboth teens and adults. The disconnect between brand names as they perform inconcepts (i.e., vignettes or mini advertisements) and the commonly held con-ceptions of brand names when assessed alone in the absence of anything elsemakes one wonder about how valid are stand-alone assessments of ideas. Inany event, conjoint analysis is not the science, but only the best method“today” for getting the data for the science of Mind Genomics.

EIGHT FOUNDATIONAL STEPS OR POINTS OF VIEWUNDERLYING THE SCIENCE OF MIND GENOMICS

We can summarize the foundations of this newly proposed science of MindGenomics in the following steps, which provide not only the specifics of themethod but also some perspective from the sciences that lie at its foundation.

The Organizing Principle of Stimulus–Response, from ExperimentalPsychology, Allows the Researcher to Understand the “Mind” by thePattern of Reactions to Stimuli

People do not know necessarily what is important to them, but can reactintuitively to ideas. If these ideas comprise systematically varied vignettes(combinations of elements or “idealets”), then through statistical analysisusing regression, we can determine which specific concept element or“idealet” “drives” the consumer responses.

Deep Understanding Comes from Understanding Responses at anIntuitive, Rather than at a Considered Level

A strong understanding of what is important to consumers comes frompresenting them with a large set of such systematically varied combinationsand getting them to respond at an intuitive or “gut” level, not at a consideredintellectualized level. This strategy of research more naturally approximateswhat happens in the external world.


Series of Studies of Different Aspects of a Product, Service or LifeSituation Teach Far More than Any Single Study

Any domain (e.g., food preferences, states of anxiety, financial services)can be better dealt with through a series of such experimentally designedcombinations, rather than one single study alone. Thus, when it comes to theMind Genomics of food, we might wish to have a dozen to five dozen suchstudies, each of which deals with a different food or eating condition. Thisview that one can gain a broader view of the consumer mind-set comes directlyout of the science of genomics, where the researcher obtains a sense of how agene expresses itself through multiple tests, not just one test.

Common Structure across Many Studies (So-Called “Mega StudyDesign”) Generates More Knowledge because the Structure Allows forComparability

The different tests (i.e., for different foods) are best laid out in a singlecommon structure, with the specific “idealets” in each test individualized tothe product being studied. However, the nature of each test element is specifiedby a template, so that the researcher can immediately discover how the sameexact element or similar type of element performs across studies.

Individuals Should Be Allowed to Participate in Studies about Topicsthat They Find Interesting and Relevant

The studies should be set up so that an individual is invited to participatein the general project (e.g., food cravings, healthy food products, insurance,anxiety states). Only when the individual expresses interest in a particulartopic does it make sense to guide the individual into the specific study. In thisway, the researcher ensures that the respondents who participate have selectedthemselves as being interested. Only later do they actually go into a specificstudy, through a second selection process.

Analysis of the Response to the Systematically Varied ConceptsGenerates a Profile of Utilities for Each Respondent, One Utility Valueper Element per Respondent

These utility values show the “mind-set” of the respondent to the categoryand constitute a “footprint” of the respondent’s mind. By changing the ratingattribute, we learn about how “instructions to the mind” change the respon-dent’s point of view and judgment criteria. By changing the test stimuli (e.g.,type of food), we learn about how the same mind responds to a variety ofsimilar types of stimuli (i.e., similar messages across foods). By working withmany individuals in the population with the same rating scales and test stimuli,

301MIND GENOMICS

we identify the nature of different mind-sets in the population (mental geno-types), which may be specific to a single product or may transcend a set ofrelated products so that the mind-sets become an organizing principle for thelarger product category.

Analytic Procedures to Deal with the Data Are Fairly Straightforward,Coming from Standard, Off-the-Shelf Software Available in AnyStatistical Program

The basic procedure is experimental design of the test stimuli to create aset of combinations of “idealets” or elements that can be deconstructed byregression analysis. The statistical analyses are done at the individual respon-dent level so that the mind-set of any individual can be studied in depth, or themind-sets of many individuals can be combined into a single holistic view.

New Ideas Can Be Generated by Combining “Idealets” into NewCombinations

This Lockean approach to concepts holds that the science of MindGenomics is both normative, revealing what exists, and prescriptive, suggest-ing by recombination what could be. Such prescriptive approaches are veryimportant for advancing the science of consumer research, especially in thecommercial world, where development can be done using knowledge about theconsumer mind-set.

THE SCIENCE OF MIND GENOMICS AS AN ARCHIVALDATABASE OF ELEMENT UTILITIES

A key aspect of science is the accretion of knowledge in archival data-bases. Without data archiving and a way to meaningful sort through thearchives to understand principles, the methods presented here constitutemerely a toolbox to solve problems. With archived data, we can look to thedata to synthesize insights about consumers, beyond simply discussing thenumerical results in verbal terms. For example, we might ask whether there arethree major segments in cosmetics, in general, as was suggested here bysegmentation for the three studies. Other questions that penetrate deeper intothe data might deal with issues such as the nature of the segments, types ofproducts that appeal to the segments, general reactivity of the segments to newideas, etc. Note the difference in emphasis between solving the problem(“What elements win in the study?”) and creating a set of organizing principlesleading to ideas and new issues (“What is common about the segments?” “Dothese segments have reality beyond this study?” etc.).


APPLICATIONS OF MIND GENOMICS

Our goal in founding this new science is to better understand the valuestructure of the individual’s mind using high-level consumer research tools.The mega studies comprising related studies in a product category provide anoverview to the way consumers make trade-offs among options in the category.Looking across different studies provides insight into the distribution of mind-sets or mental genotypes worldwide.

Mind Genomics has another objective – practical application of knowl-edge and insights to create better products and services. Our suggested newscience stands, therefore, on two platforms – knowledge about people’s judg-ment criteria when it comes to “ecologically meaningful” stimuli such asproducts, as well as direct applicability of the results in a business frameworksuch as communication and product development.

We have applied the approach of Mind Genomics to areas as diverse asfood craveability, beverages, insurance, anxiety-provoking social issues andshopping. Our next goals are to take the approach and apply to areas as diverseas the morals/ethics, political policy and financial issues. The goal of this earlystage research was to show proof of the concept, develop a database, show howthe results can be used and build this newly developing science from the“ground up.”

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FOUNDING A NEW SCIENCE: MIND GENOMICS