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Product Innovation Toolbox
A Field Guide to Consumer Understanding and Research
Kannapon Lopetcharat (Edited by), K Lopetcharat (Author), Dulce Paredes (Edited by), Jacqueline H. Beckley (Edited by)
9781119712848, Wiley
Hardback, published 27 October 2022
560 pages
24.4 x 17 x 3.3 cm, 1.219 kg
PRODUCT INNOVATION TOOLBOX Discover how to implement consumer-centric innovation to help create new product development in this latest edition In recent years, behavioral approaches, social media listening, and other new techniques and technologies—digital techniques, augmented intelligence, machine learning, and advanced biometrics, among others—have been foregrounded in innovation research. A focus on the evolving fields of data science and neuroscience is a driving force for both researchers and the people they study. These digital and mobile technologies have enabled researchers to augment listening, observing and categorizing methods, and to adapt new techniques in attempting to better understand consumers. On the other hand, digitized mobile societies, spurred by faster and cheaper internet access, emphasize an interconnectedness that drastically alters human behaviors and creates borderless influences. Even so, the tenets and approaches to insightful deep learning for consumers and other actors, from discovery through to the launch of successful products, remains an intrinsic part of assessing the market. Product Innovation Toolbox brings together key thought leaders and seasoned consumer researchers from corporate R&D, academia, and marketing research companies to share their experiences, advanced consumer research tools and practical tips for successful and sustainable product innovation. By offering these leading-edge tools and insights, the book ensures consumer-centric innovation by linking strategy and a designed approach. The new edition focuses on the integration and connection of all data—both structured and unstructured???for deep learning and activation, rather than a differentiated qualitative—quantitative approach, reflecting the shifting relationships involved in the latest developments in the field. The second edition of Product Innovation Toolbox also includes: Product Innovation Toolbox is an essential resource for product developers, marketers, and technologists.
Contributors xiv Acknowledgements xvi Introduction: The View from Pixel to Picture xvii Part I Prepare For Your Journey 1 1 Setting the Direction: First, Know Where You Are 4 1.1 Roles in the corporation – the dance of the knowledge worker 4 1.2 Insights leader – learning on the job vs. learning in school 6 1.3 Being the authentic you 8 1.4 What should you read? 9 1.5 What else do you need to do to prepare to be an insight leader? 9 1.6 Dealing with management and your clients/customers 10 1.7 Guidelines to success 11 1.8 Reporting results 12 1.9 Do not “winstonize” 13 1.10 Making it public – helpful hints to grow from student to professional 15 1.11 The two types of professionals in the world of evaluating products (and studying consumers/people) 16 1.12 Knowing your limits and inviting others in 17 1.13 The bottom line – what’s it all about? 18 Discussion questions 19 References 19 2 The Consumer Explorer: Key to Delivering the Innovation Strategy 22 2.1 The rise of the Consumer Explorer 22 2.2 The roles of the Consumer Explorer 23 2.3 Taking the lead 27 2.4 Practical advice from seasoned explorers 32 Discussion questions 33 References 33 3 Invention and Innovation 36 3.1 Dual aptitudes needed for innovation 36 3.2 Benefits 38 3.3 The invention–innovation paradigm in science 39 3.4 The time scale of innovations 41 3.5 Final remarks 41 Discussion questions 42 References 42 Note 42 4 Designing the Research Model 44 4.1 Factors influencing product innovation 44 4.2 Setting up a successful product innovation program 46 4.3 Current approach to NPD 47 4.4 Experimentation in practice 48 4.5 Iterative Experimentation Qualitative–Quantitative Research model 54 Discussion questions 57 References 57 5 What You Must Look For – Signs of High Potential Insights 60 5.1 What is insight? 60 5.2 Good insights have the following characteristics: 61 5.3 What is an “ownable” insight? 62 5.4 How to develop high potential insights 63 5.5 Making insights ownable 65 5.6 Summary 72 Discussion questions 73 References 73 Part II Gear Up For Your Journey 75 6 Tools for Upfront Research on Consumer Triggers and Barriers: Qualitative Tools 78 6.1 Understanding Consumer Language 78 6.1.1 Consumers do not understand technical product language, so what should we say about our new products? 78 6.1.2 How to select a method? 79 6.1.3 Free Elicitation and Zaltman metaphor elicitation technique (ZMET) 81 6.1.4 Laddering interview 83 6.1.5 Kelly’s Repertory Grid and Flash Profiling 92 6.1.6 Summary and future 100 Discussion questions 101 Note 101 References 101 6.2 Qualitative Multivariate Analysis 103 6.2.1 Consumers do not know what they want, really. Really? 103 6.2.2 Introduction 104 6.2.3 Qualitative multivariate analysis in practice 105 6.2.4 Qualitative Multivariate Analysis in practice: deeper understanding of cottage cheese consumption 118 6.2.5 Consumer perceived values 121 6.2.6 Summary and future of Qualitative Multivariate Analysis 123 Discussion questions 123 References 123 6.3 The Gameboard “Model Building” 125 6.3.1 The problem – how to talk to consumers about new products that do not exist? 125 6.3.2 A new method: Gameboard strategy “Model Building” 126 6.3.3 Construction: creative process model 126 6.3.4 Interview guide for model construction methodology 130 6.3.5 Ensuring reliability of the outcomes 132 6.3.6 Analysis of the outcomes from Gameboard “Model Building” 132 6.3.7 Analysis overview 133 6.3.8 Consumer-centered products and Gameboard “Model Building” 134 6.3.9 Limitations 135 6.3.10 Quantitative Gameboard 136 6.3.11 Theoretical background of model construction methodology 137 6.3.12 Summary and future 138 Discussion questions 139 References 139 7 Tools for Upfront Research on Consumer Triggers and Barriers: Qualitative-Quantitative Tools 142 7.1 Creative Blogging 142 7.1.1 Introduction 143 7.1.2 The rise of blogging platforms enables new mode of data collection 145 7.1.3 Creative Blogging 148 7.1.4 Creative Blogging in practice: a case example in Thailand 157 7.1.5 Choosing the platform: Close-or Open-platform 158 7.1.6 Read between the lines: dialogue with consumers 158 7.1.7 Future of Creative Blogging 162 Discussion questions 162 7.2 CATA as a Decision-Making Tool 163 7.2.1 Introduction 163 7.2.2 Check All That Apply (CATA) task in practice 165 7.2.3 Selecting benefit propositions for a new product: a case study of a cleansing product using CATA 169 7.2.4 Summary and future of CATA in product research 176 Discussion questions 176 Notes 176 References 176 8 Tools for Up-Front Research on Understanding Consumer Values 180 8.1 KANO Consumer Product Satisfaction Model 180 8.1.1 What consumer satisfaction can do to your business 180 8.1.2 Philosophy behind KANO’s consumer satisfaction model 182 8.1.3 KANO survey step by step 184 8.1.4 Case Study: Lipstick KANO survey 191 8.1.5 Comparison with degree of importance surveys 192 8.1.6 Future of KANO satisfaction survey 195 Discussion Questions 196 References 196 8.2 Systematics of Communication: Conjoint Measurement, Emotions, Cognitive Economics, and Consumer Mind-sets 198 8.2.1 The issue 198 8.2.2 Consumer research: experimentation vs. testing 199 8.2.3 Conjoint analysis (aka conjoint measurement) 200 8.2.4 Doing the basic conjoint analysis experiment 201 8.2.5 The raw material of CA 207 8.2.6 Experimental design 209 8.2.7 Building models 209 8.2.8 Presenting the result – numbers, text, data, talk, move to steps 211 8.2.9 Using the results – what do the numbers tell us? 214 8.2.10 Beyond individual groups to segments – finding mind-sets using conjoint analysis 215 8.2.11 Scenario analysis – discovering synergisms and suppressions (interactions) among elements in a conjoint analysis study 217 8.2.12 Dealing with prices 219 8.2.13 Linking elements to emotions 227 8.2.14 Measuring response time 227 8.2.15 Discovering the “new” through conjoint analysis – creating an innovation machine 228 8.2.16 Mind Genomics™: a new “science of the mind” based upon conjoint analysis 229 8.2.17 The personal viewpoint identifier (PVI) 237 8.2.18 Four considerations dictating the future use of conjoint analysis 241 8.2.19 Conclusion 243 Discussion Questions 243 References 243 9 New Tools Beyond Conventional Qualitative and Quantitative Meanings 246 9.1 Emotions, Moods, and Emotives 246 9.1.1 Introduction 246 9.1.2 Understanding differences between affect, attitude, mood, emotion and emotive 248 9.1.3 Review of emotion theories 248 9.1.4 Popular methodologies for the measurement of emotions 259 9.1.5 Impact of social media on emotion research 261 9.1.6 Conclusion and recommendations 266 Discussion Questions 267 References 267 9.2 Applied Consumer Neuroscience and Behavioral Approaches for Innovation, Product Development, and Communications 271 9.2.1 A behavioral approach: behavioral and consumer neuroscience science 272 9.2.2 Applying novel methods to innovation: choosing the right tool 285 9.2.3 Case studies using behavioral science and applied consumer neuroscience 286 9.2.4 Conclusions: conceptual framework for behavior-led Innovation 299 9.2.5 Future of neuroscience 301 Discussion Questions 301 References 302 9.3 Review of Applications of VR Tools, New Opportunities, and Limitations 305 9.3.1. Importance of context in consumer product research 305 9.3.2. Means of creating context 307 9.3.3. How to create a study using VR/AR tools 313 9.3.4. Looking ahead: what are the current technology limitations and what might be coming up next 317 9.3.5. Summary 320 Discussion Questions 321 References 321 Post Scriptum 326 10 Tools to Refine and Screen Product Ideas in New Product Development 328 10.1 Contemporary Product Research Tools 328 10.1.1 Introduction 328 10.1.2 What is a concept? 329 10.1.3 Elements of a concept 329 10.1.4 What is a concept test? 330 10.1.5 Common measures 333 10.1.6 Sampling: who do you test with? 333 10.1.7 Biometrics applications 334 10.1.8 New developments in concept testing 334 10.1.9 Conclusion: from winning idea to successful product 334 Discussion questions 335 References 335 10.2 Insight Teams: An Adaptive, Self-directed Group to Discovery 336 10.2.1 Insight Teams for discovery 336 10.2.2 Definition of an Insight Team 337 10.2.3 When to apply the skills of an Insight Team 338 10.2.4 Implementing Insight Teams for development 339 10.2.5 How to use the Insight Team 350 10.2.6 Case study of using the Insight Team 350 10.2.7 The future of Insight Teams 351 Discussion questions 351 References 352 10.3 Rapid Approaches in Defining the Product Space and Product Optimization 353 10.3.1 Doing more with less 353 10.3.2 Listening to understand 354 10.3.3 Defining rapid product navigation (RPN) and rapid product optimization (RPO) 355 10.3.4 Recommended tools and “how to” implement RPO 355 10.3.5 Three Case Studies that illustrate the uses of RPN/RPO 363 10.3.6 Theoretical background of the tools 378 10.3.7 Summary and future of the tools 379 Discussion questions 379 Note 380 References 380 10.4 Free-Choice in Context Preference Ranking: A New Approach for Portfolio Assessment 381 10.4.1 Want to offer more. . .but how many is too many? 381 10.4.2 Current approaches on product line extension 382 10.4.3 Free-choice in context preference ranking 385 10.4.4 Practical considerations 391 10.4.5 Theoretical backgrounds of free-choice in context preference ranking 394 10.4.6 Summary and future 394 Discussion questions 395 10.4.A Appendix 395 References 396 10.5 Extended Use Product Research for Predicting Market Success 397 10.5.1 Challenges in validating and predicting the success of new product launch 397 10.5.2 Limitations of traditional approaches 399 10.5.3 An alternative: extended use product research 400 10.5.4 Steps in conducting extended use product research (EUPR) 401 10.5.5 Understanding consumer segments 402 10.5.6 Assessment of sensory performance 402 10.5.7 Understanding how consumers make choice decisions 404 10.5.8 Using behavioral measures to help assess product viability 405 10.5.9 Among users, there were also segments of situational users and regular users 406 10.5.10 Additional insights on consumer choice selection – learning from extended use product research 408 10.5.11 Philosophy behind extended use product research 410 10.5.12 Summary and future 411 Discussion questions 411 References 411 Part III Word of the Wise: Wisdom From Experienced Explorers 413 11 Putting It All Together: Driving Consumer-Centric Innovation in an Organization 416 11.1 For successful innovation, the consumer story must be front and center 416 11.2 What does the path to successful innovation look like? 420 Harnessing the power of the past and using tools to set up for success 422 11.3 Learning from the past before jumping to collect new information 422 11.4 Creating the critical internal contract of the research plan 423 11.5 Gathering the data to help influence the direction of innovation and conversation 424 Synthesize and simplify: designing and utilizing analytical structures and constructs 426 11.6 Connecting the dots of multiple pieces of data and research 426 11.7 Creative listening frameworks to help navigate the consumer conversation 428 11.8 Operationalizing your learnings with visual product models 430 11.9 Crafting the influential strategic conversation to make sense of it all for action 433 Evolving from a research runner to an insights influencer 436 11.10 Moving from a transactional relationship to an integral strategic partner 436 11.11 What does the future hold for the world of insights? 438 Discussion questions 439 Note 440 References 440 12 Above Averages: Use of Statistics and Design of Experiments in Product Innovation Applications 442 12.1 Experimentation vs. testing 443 12.2 Statistical experimental design 444 12.3 Brief history of experimental design 448 12.4 The age of big data and data science 449 12.5 Managing experimentation 451 12.6 Summary and future 453 Discussion questions 454 References 454 13 How to Work with Industry Experts and Influencers for Innovation 456 13.1 Introduction 456 13.2 Meet the influencers 457 13.3 Could we go a step further, leverage social media influencers for innovation? 460 13.4 Practical tips 462 13.5 Conclusion 463 Note 463 References 463 14 Words of the Wise – Virtual Staff 466 14.1 Why a virtual staff? 466 14.2 What is virtual staff and what is required to be one? 467 14.3 How do you go about building and utilizing a virtual staff? 468 14.4 How would you rate the performance of a virtual staff? 470 14.5 How does virtual staff work based on success case studies? 472 14.6 Conclusion 473 Discussion questions 474 Note 475 References 475 15 Found in Translation: The Adventure of Conducting Multicultural Consumer Research 478 15.1 Setting the scene: plan ahead 478 15.2 Infrastructure, logistics and company: everything you take for granted, DON’T! 481 15.3 Multicultural background in just one site 484 15.4 Conclusions: found in translation 485 Discussion questions 486 References 486 16 Sturdy Bridges to Future Trends 490 16.1 Introduction 490 16.2 Redefining data 491 16.3 Legacy tools 500 16.4 Emerging topic: democratization of data 501 16.5 Comparison to 2010–2019 consumer and sensory dive analysis 504 16.6 Conclusion 506 Discussion questions 507 Note 507 References 507 17 Future Trends and Direction 509 17.1 Pandemic influenced acceleration of technology 510 17.2 The hybrid model of consumer understanding evolves 511 17.3 The rise of the individual, the human. Moving from consumption as an end goal to understanding the whole person 514 17.4 Nature influenced adoption 516 17.5 Social forces for change 517 17.6 Conclusion 517 References 518 Index 521
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Subject Areas: Business & management [KJ]
