1. Analyzing the right problem
2. Understanding the big information picture
3. Compensating for imperfect data
4. Developing an effective analysis strategy
5. Establishing the interpretation boundary
6. Applying the ′knowledge filters′
7. ′Re–framing′ the data
8. Presenting the research evidence as a narrative
9. Facilitating informed decision–making
10. Learning from successful practice
This book is supported by a ten–module training course consisting of a series of PowerPoint presentation charts. This also includes case studies that will be helpful to University lecturers and those responsibl e for training new graduates entering the mark et research industry, on either the client or agency side.
"This is modern commercial research, where the mind of the researcher is finally acknowledged as admissible data. Prior knowledge, pragmatism, experience are all robust grist to the ′holistic′ research mill. A must–read textbook for anyone getting to grips with 21st century market research."
—Virginia Valentine, Semiotic Solutions
"This book enables both the research client and practitioner to think more clearly about how different strands of ‘research’ can work together through a unifying analytical approach. Although designed as a teaching and development resource, the underlying thinking makes refreshing reading for all those supplying or using market research."
—Leslie Sopp, Head of Research, Institute of Chartered Accountants, Chairman, Association of Users of Research Agencies
"This book is aimed at newcomers to market research; however, Smith and Fletcher′s approach to their subject can teach us all some new lessons. I was particularly impressed by the weight of theoretical and practical evidence they assemble to underpin their arguments at every turn and, as two of the most respected researchers in the industry, see it as their responsibility to share that knowledge with others in as highly accessible a form as possible."
—Nigel Culkin FMRS, Associate, Dean (Business Partnerships, University of Hertfordshire)
1. ‘New’ market research.
2. Not a science, but a scientific approach.
3. Data–rich intuitive analysis.
4. Analysing the right problem.
5. Understanding the big information picture.
6. Compensating for imperfect data.
7. Developing the analysis strategy.
8. Organizing the qualitative data.
9. Organizing the quantitative data.
10. Establishing the interpretation boundary.
11. Applying the knowledge filters.
12. Reframing the data.
13. Integrating the evidence and presenting research as a narrative.
14. Facilitating informed decision–making.
15. Developing holistic data analysis.
16. Guide to the supporting training module.
Glossary of holistic analysis terms.