Product Innovation Toolbox

Kannapon Lopetcharat is the Executive Director at Nouveau Centric Co. Ltd. in Bangkok, Thailand. He holds a PhD in sensory science and psychophysics, with a minor in statistics from Oregon State University. He has worked for Unilever and Avon as a consumer science manager, and has extensive experience in applying consumer product and sensory research in product development and innovation. Dulce Paredes is an experienced ‘consumer navigator’ who works with organizations using consumer insights to develop products and innovation programs. She is the global leader of consumer insights and market research flavor division for Takasago International Corporation (USA). She previously led R&D consumer sciences groups at Avon Products and Kraft Foods. She was a product developer for PepsiCo Inc. after completing her PhD in food science from Cornell University. Jacqueline H. Beckley is the founder of The Understanding & Insight Group, LLC, in Denville, New Jersey, USA. She is considered one of the early adaptors of face-to-face qualitative understanding. Prior to this, Beckley held positions within industry and consulting, including director of consumer perception at Nabisco, Inc., Vice President at Peryam & Kroll Marketing and Sensory Research, group manager of sensory research and R&D for the Quaker Oats Company, and research scientist for Amoco Chemical Company.

• Contributors xivAcknowledgements xviIntroduction: The View from Pixel to Picture xviiKannapon Lopetcharat, Dulce Paredes, and Jacqueline H. BeckleyPart I Prepare For Your Journey 11 Setting the Direction: First, Know Where You Are 4Howard Moskowitz and Jacqueline H. Beckley1.1 Roles in the corporation – the dance of the knowledge worker 41.2 Insights leader – learning on the job vs. learning in school 61.3 Being the authentic you 81.4 What should you read? 91.5 What else do you need to do to prepare to be an insight leader? 91.6 Dealing with management and your clients/customers 101.7 Guidelines to success 111.8 Reporting results 121.9 Do not “winstonize” 131.10 Making it public – helpful hints to grow from student to professional 151.11 The two types of professionals in the world of evaluating products (and studying consumers/people) 161.12 Knowing your limits and inviting others in 171.13 The bottom line – what’s it all about? 18Discussion questions 19References 192 The Consumer Explorer: Key to Delivering the Innovation Strategy 22Dulce Paredes and Kannapon Lopetcharat2.1 The rise of the Consumer Explorer 222.2 The roles of the Consumer Explorer 232.3 Taking the lead 272.4 Practical advice from seasoned explorers 32Discussion questions 33References 333 Invention and Innovation 36Daniel M. Ennis3.1 Dual aptitudes needed for innovation 363.2 Benefits 383.3 The invention–innovation paradigm in science 393.4 The time scale of innovations 413.5 Final remarks 41Discussion questions 42References 42Note 424 Designing the Research Model 44Kannapon Lopetcharat, Dulce Paredes, and Jacqueline H. Beckley4.1 Factors influencing product innovation 444.2 Setting up a successful product innovation program 464.3 Current approach to NPD 474.4 Experimentation in practice 484.5 Iterative Experimentation Qualitative–Quantitative Research model 54Discussion questions 57References 575 What You Must Look For – Signs of High Potential Insights 60Kannapon Lopetcharat, Dulce Paredes, and Jacqueline H. Beckley5.1 What is insight? 605.2 Good insights have the following characteristics: 615.3 What is an “ownable” insight? 625.4 How to develop high potential insights 635.5 Making insights ownable 655.6 Summary 72Discussion questions 73References 73Part II Gear Up For Your Journey 756 Tools for Upfront Research on Consumer Triggers and Barriers: Qualitative Tools 786.1 Understanding Consumer Language 78Kannapon Lopetcharat and Jacqueline H. Beckley6.1.1 Consumers do not understand technical product language, so what should we say about our new products? 786.1.2 How to select a method? 796.1.3 Free Elicitation and Zaltman metaphor elicitation technique (ZMET) 816.1.4 Laddering interview 836.1.5 Kelly’s Repertory Grid and Flash Profiling 926.1.6 Summary and future 100Discussion questions 101Note 101References 1016.2 Qualitative Multivariate Analysis 103Kannapon Lopetcharat and Jacqueline H. Beckley6.2.1 Consumers do not know what they want, really. Really? 1036.2.2 Introduction 1046.2.3 Qualitative multivariate analysis in practice 1056.2.4 Qualitative Multivariate Analysis in practice: deeper understanding of cottage cheese consumption 1186.2.5 Consumer perceived values 1216.2.6 Summary and future of Qualitative Multivariate Analysis 123Discussion questions 123References 1236.3 The Gameboard “Model Building” 125Jennifer Vahalik, Melissa Jeltema, Jacqueline H. Beckley, and Jeff Garza6.3.1 The problem – how to talk to consumers about new products that do not exist? 1256.3.2 A new method: Gameboard strategy “Model Building” 1266.3.3 Construction: creative process model 1266.3.4 Interview guide for model construction methodology 1306.3.5 Ensuring reliability of the outcomes 1326.3.6 Analysis of the outcomes from Gameboard “Model Building” 1326.3.7 Analysis overview 1336.3.8 Consumer-centered products and Gameboard “Model Building” 1346.3.9 Limitations 1356.3.10 Quantitative Gameboard 1366.3.11 Theoretical background of model construction methodology 1376.3.12 Summary and future 138Discussion questions 139References 1397 Tools for Upfront Research on Consumer Triggers and Barriers: Qualitative-Quantitative Tools 1427.1 Creative Blogging 142Kannapon Lopetcharat and Dulce Paredes7.1.1 Introduction 1437.1.2 The rise of blogging platforms enables new mode of data collection 1457.1.3 Creative Blogging 1487.1.4 Creative Blogging in practice: a case example in Thailand 1577.1.5 Choosing the platform: Close-or Open-platform 1587.1.6 Read between the lines: dialogue with consumers 1587.1.7 Future of Creative Blogging 162Discussion questions 1627.2 CATA as a Decision-Making Tool 163Kannapon Lopetcharat and Dulce Paredes7.2.1 Introduction 1637.2.2 Check All That Apply (CATA) task in practice 1657.2.3 Selecting benefit propositions for a new product: a case study of a cleansing product using CATA 1697.2.4 Summary and future of CATA in product research 176Discussion questions 176Notes 176References 1768 Tools for Up-Front Research on Understanding Consumer Values 1808.1 KANO Consumer Product Satisfaction Model 180Alina Stelick, Kannapon Lopetcharat, and Dulce Paredes8.1.1 What consumer satisfaction can do to your business 1808.1.2 Philosophy behind KANO’s consumer satisfaction model 1828.1.3 KANO survey step by step 1848.1.4 Case Study: Lipstick KANO survey 1918.1.5 Comparison with degree of importance surveys 1928.1.6 Future of KANO satisfaction survey 195Discussion Questions 196References 1968.2 Systematics of Communication: Conjoint Measurement, Emotions, Cognitive Economics, and Consumer Mind-sets 198Howard Moskowitz and David Moskowitz8.2.1 The issue 1988.2.2 Consumer research: experimentation vs. testing 1998.2.3 Conjoint analysis (aka conjoint measurement) 2008.2.4 Doing the basic conjoint analysis experiment 2018.2.5 The raw material of CA 2078.2.6 Experimental design 2098.2.7 Building models 2098.2.8 Presenting the result – numbers, text, data, talk, move to steps 2118.2.9 Using the results – what do the numbers tell us? 2148.2.10 Beyond individual groups to segments – finding mind-sets using conjoint analysis 2158.2.11 Scenario analysis – discovering synergisms and suppressions (interactions) among elements in a conjoint analysis study 2178.2.12 Dealing with prices 2198.2.13 Linking elements to emotions 2278.2.14 Measuring response time 2278.2.15 Discovering the “new” through conjoint analysis – creating an innovation machine 2288.2.16 Mind Genomics™: a new “science of the mind” based upon conjoint analysis 2298.2.17 The personal viewpoint identifier (PVI) 2378.2.18 Four considerations dictating the future use of conjoint analysis 2418.2.19 Conclusion 243Discussion Questions 243References 2439 New Tools Beyond Conventional Qualitative and Quantitative Meanings 2469.1 Emotions, Moods, and Emotives 246Kannapon Lopetcharat and Dulce Paredes9.1.1 Introduction 2469.1.2 Understanding differences between affect, attitude, mood, emotion and emotive 2489.1.3 Review of emotion theories 2489.1.4 Popular methodologies for the measurement of emotions 2599.1.5 Impact of social media on emotion research 2619.1.6 Conclusion and recommendations 266Discussion Questions 267References 2679.2 Applied Consumer Neuroscience and Behavioral Approaches for Innovation, Product Development, and Communications 271Michelle Niedziela and Kathryn Ambroze9.2.1 A behavioral approach: behavioral and consumer neuroscience science 2729.2.2 Applying novel methods to innovation: choosing the right tool 2859.2.3 Case studies using behavioral science and applied consumer neuroscience 2869.2.4 Conclusions: conceptual framework for behavior-led Innovation 2999.2.5 Future of neuroscience 301Discussion Questions 301References 3029.3 Review of Applications of VR Tools, New Opportunities, and Limitations 305Alina Stelick9.3.1. Importance of context in consumer product research 3059.3.2. Means of creating context 3079.3.3. How to create a study using VR/AR tools 3139.3.4. Looking ahead: what are the current technology limitations and what might be coming up next 3179.3.5. Summary 320Discussion Questions 321References 321Post Scriptum 32610 Tools to Refine and Screen Product Ideas in New Product Development 32810.1 Contemporary Product Research Tools 328Michele Foley10.1.1 Introduction 32810.1.2 What is a concept? 32910.1.3 Elements of a concept 32910.1.4 What is a concept test? 33010.1.5 Common measures 33310.1.6 Sampling: who do you test with? 33310.1.7 Biometrics applications 33410.1.8 New developments in concept testing 33410.1.9 Conclusion: from winning idea to successful product 334Discussion questions 335References 33510.2 Insight Teams: An Adaptive, Self-directed Group to Discovery 336Kannapon Lopetcharat, Dulce Paredes, and Jacqueline H. Beckley10.2.1 Insight Teams for discovery 33610.2.2 Definition of an Insight Team 33710.2.3 When to apply the skills of an Insight Team 33810.2.4 Implementing Insight Teams for development 33910.2.5 How to use the Insight Team 35010.2.6 Case study of using the Insight Team 35010.2.7 The future of Insight Teams 351Discussion questions 351References 35210.3 Rapid Approaches in Defining the Product Space and Product Optimization 353Jennifer Vahalik, Ratapol Teratanavat, Jennifer Lewis, Mary Sonnen, Melissa Jeltema, and Jacqueline H. Beckley10.3.1 Doing more with less 35310.3.2 Listening to understand 35410.3.3 Defining rapid product navigation (RPN) and rapid product optimization (RPO) 35510.3.4 Recommended tools and “how to” implement RPO 35510.3.5 Three Case Studies that illustrate the uses of RPN/RPO 36310.3.6 Theoretical background of the tools 37810.3.7 Summary and future of the tools 379Discussion questions 379Note 380References 38010.4 Free-Choice in Context Preference Ranking: A New Approach for Portfolio Assessment 381Ratapol Teratanavat, James Mwai, Melissa Jeltema, and Jennifer Vahalik10.4.1 Want to offer more. . .but how many is too many? 38110.4.2 Current approaches on product line extension 38210.4.3 Free-choice in context preference ranking 38510.4.4 Practical considerations 39110.4.5 Theoretical backgrounds of free-choice in context preference ranking 39410.4.6 Summary and future 394Discussion questions 39510.4.A Appendix 395References 39610.5 Extended Use Product Research for Predicting Market Success 397Ratapol Teratanavat, Melissa Jeltema, Stephanie Plunkett, and Jennifer Vahalik10.5.1 Challenges in validating and predicting the success of new product launch 39710.5.2 Limitations of traditional approaches 39910.5.3 An alternative: extended use product research 40010.5.4 Steps in conducting extended use product research (EUPR) 40110.5.5 Understanding consumer segments 40210.5.6 Assessment of sensory performance 40210.5.7 Understanding how consumers make choice decisions 40410.5.8 Using behavioral measures to help assess product viability 40510.5.9 Among users, there were also segments of situational users and regular users 40610.5.10 Additional insights on consumer choice selection – learning from extended use product research 40810.5.11 Philosophy behind extended use product research 41010.5.12 Summary and future 411Discussion questions 411References 411Part III Word of the Wise: Wisdom From Experienced Explorers 41311 Putting It All Together: Driving Consumer-Centric Innovation in an Organization 416Stacey Cox and Anthony Jackel11.1 For successful innovation, the consumer story must be front and center 41611.2 What does the path to successful innovation look like? 420Harnessing the power of the past and using tools to set up for success 42211.3 Learning from the past before jumping to collect new information 42211.4 Creating the critical internal contract of the research plan 42311.5 Gathering the data to help influence the direction of innovation and conversation 424Synthesize and simplify: designing and utilizing analytical structures and constructs 42611.6 Connecting the dots of multiple pieces of data and research 42611.7 Creative listening frameworks to help navigate the consumer conversation 42811.8 Operationalizing your learnings with visual product models 43011.9 Crafting the influential strategic conversation to make sense of it all for action 433Evolving from a research runner to an insights influencer 43611.10 Moving from a transactional relationship to an integral strategic partner 43611.11 What does the future hold for the world of insights? 438Discussion questions 439Note 440References 44012 Above Averages: Use of Statistics and Design of Experiments in Product Innovation Applications 442Kannapon Lopetcharat, Dulce Paredes, and Jacqueline H. Beckley12.1 Experimentation vs. testing 44312.2 Statistical experimental design 44412.3 Brief history of experimental design 44812.4 The age of big data and data science 44912.5 Managing experimentation 45112.6 Summary and future 453Discussion questions 454References 45413 How to Work with Industry Experts and Influencers for Innovation 456Veronica Symon13.1 Introduction 45613.2 Meet the influencers 45713.3 Could we go a step further, leverage social media influencers for innovation? 46013.4 Practical tips 46213.5 Conclusion 463Note 463References 46314 Words of the Wise – Virtual Staff 466Carter Green, Ratapol Teratanavat, and Dulce Paredes14.1 Why a virtual staff? 46614.2 What is virtual staff and what is required to be one? 46714.3 How do you go about building and utilizing a virtual staff? 46814.4 How would you rate the performance of a virtual staff? 47014.5 How does virtual staff work based on success case studies? 47214.6 Conclusion 473Discussion questions 474Note 475References 47515 Found in Translation: The Adventure of Conducting Multicultural Consumer Research 478Vanessa Zuccoli and Paulina Morquecho-Campos15.1 Setting the scene: plan ahead 47815.2 Infrastructure, logistics and company: everything you take for granted, DON’T! 48115.3 Multicultural background in just one site 48415.4 Conclusions: found in translation 485Discussion questions 486References 48616 Sturdy Bridges to Future Trends 490Katherine C. S. Rhodes, Dulce Paredes, and Jacqueline H. Beckley16.1 Introduction 49016.2 Redefining data 49116.3 Legacy tools 50016.4 Emerging topic: democratization of data 50116.5 Comparison to 2010–2019 consumer and sensory dive analysis 50416.6 Conclusion 506Discussion questions 507Note 507References 50717 Future Trends and Direction 509Kannapon Lopetcharat, Dulce Paredes, and Jacqueline H. Beckley17.1 Pandemic influenced acceleration of technology 51017.2 The hybrid model of consumer understanding evolves 51117.3 The rise of the individual, the human. Moving from consumption as an end goal to understanding the whole person 51417.4 Nature influenced adoption 51617.5 Social forces for change 51717.6 Conclusion 517References 518Index 521