The Art & Scienceof Interpreting MarketResearch Evidence

D.V.L. Smith and J.H. Fletcher

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The Art & Scienceof Interpreting MarketResearch Evidence

The Art & Scienceof Interpreting MarketResearch Evidence

D.V.L. Smith and J.H. Fletcher

Copyright 2004 John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester,West Sussex PO19 8SQ, England

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Library of Congress Cataloging-in-Publication Data

Smith, D. V. L. (David Van Lloyd)The art & science of interpreting market research evidence / DVL Smith and JH Fletcher.

p. cm.Includes bibliographical references and index.ISBN 0-470-84424-8 (alk. paper)1. Marketing research. 2. Qualitative research. 3. Statistics. I. Title: Art and science of

interpreting market research evidence. II. Fletcher, J. H. III. Title.

HF5415.2.S558 2004658.8′3--dc22

2003067249

British Library Cataloguing in Publication Data

A catalogue record for this book is available from the British Library

ISBN 0-470-84424-8

Typeset in 10/12pt Garamond by Laserwords Private Limited, Chennai, IndiaPrinted and bound in Great Britain by Antony Rowe Ltd, Chippenham, WiltshireThis book is printed on acid-free paper responsibly manufactured from sustainable forestryin which at least two trees are planted for each one used for paper production.

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Contents

Foreword vii

Preface ix

Acknowledgements xi

1 ‘New’ market research 1

2 Not a science, but a scientific approach 15

3 Data-rich intuitive analysis 27

4 Analysing the right problem 37

5 Understanding the big information picture 49

6 Compensating for imperfect data 61

7 Developing the analysis strategy 83

8 Organizing the qualitative data 91

9 Organizing the quantitative data 105

10 Establishing the interpretation boundary 129

11 Applying the knowledge filters 149

12 Reframing the data 169

13 Integrating the evidence and presenting research as a narrative 179

14 Facilitating informed decision-making 195

vi Contents

15 Developing holistic data analysis 211

16 Guide to the supporting training module 217

Notes 219

References 225

Glossary of holistic analysis terms 229

Index 231

Foreword

It is a great pleasure to write a foreword to this book. I believe that thecontents have the potential to lead a major step forward in the way in whichmanagers in organizations use and apply evidence and fact-based knowledge tomake decisions.

It is stunning that across wholly diverse industrial sectors – for example, look atmarket leader characteristics all the way from high technology at Dell Computersto marketing grocery and household products at Tesco stores – we are finallyrealizing that those who know more outperform the rest. Superiority in learningand sustaining that advantage through the constant search for new insights andbetter understanding of the drivers of customer value in the marketplace hasproved to be one of the most critical corporate competencies. Yet, it is a sourceof competitive advantage we have underestimated so much that we have noteven found a name for it.

We do know, however, that enhancing capabilities in learning faster and betterthan the competition to build sustained competitive advantage through superiorknowledge requires far more than acquiring techniques and technology for datacollection and analysis. The volume of data that the technology can produce,and the precise measurement that data collection and analysis tools can provideare important resources. However, at best they are part of the total array of cluesand insights that build superior understanding of the marketplace. To believethat they are the only ways to generate and test new ways of doing things is asfatuous as pursuing the tired debate about the relative merits of quantitative andqualitative research designs. Such introspective obsessions lead us to miss thereal point.

That point is the prime goal of: building understanding and insight; sensing andanticipating change; and value innovation for superior performance. Importantprogress towards meeting this elusive goal can be made by emphasizing theinterpretation of the whole array of evidence available, regardless of type, notsimply reporting data, and working with decision-makers to develop effectiveand sustained learning processes. The approach in this book provides a valuableframework for implementing these priorities.

There can never have been a time when the need for evidence-based knowl-edge as the basis for management decision-making was greater. It is timely for

viii Foreword

market research professionals to consider their future in this new scenario andthe ways in which they can best add value to decision-making processes.

Professor Nigel F. Piercy

Warwick Business SchoolThe University of Warwick

Preface

The last few years have seen the arrival of ‘new’ market research. Gone are thedays when market research posed as a quasi-academic activity that only flirtedwith the business decision-making process. Today, market researchers are muchmore focused on improving the quality of business decision-making.

This arrival of new market research has presented the industry with an excitingchallenge. This is, how best to communicate to its client base (and also to newgraduates entering the industry) exactly how new market research operates. Thisbook addresses this issue.

• It provides a comprehensive review of the frameworks that today’s newmarket researchers use to draw together different types of, often imperfect,qualitative and quantitative data, and explains how they apply this evidenceto successful information-based decision-making.

This introduction to how new market researchers now interpret data will beof interest to those fascinated as to why so many of the existing textbooks onmarket research bear little resemblance to how market research really operatesin practice. Specifically, our account will be of particular benefit to:

• University graduates who have recently taken up posts as market researchpractitioners, either on the client or agency side.

• Users of market research data who need an overview of how modern marketresearch now operates.

• Lecturers on, and students of, market research, who may wish to incorporateour practical insights into their courses.

• Individuals working in central and local government involved in evidence-based decision-making.

In sum, the book is aimed at individuals who want a simple synthesis of theway in which market research analysts are now going beyond their traditionalmethodological approaches, and are today operating with a more powerful setof data analysis techniques in making sense of customer evidence.

x Preface

Supporting training module

To help educationalists and trainers who wish to run a module on the dataanalysis principles raised in this book, we have prepared a ten-unit lecturecourse that mirrors the content of this book. This is available in the form of aseries of Microsoft PowerPoint charts. For details on how to obtain these chartsvisit Wiley’s website: www.wileyeurope.com/go/smith. This supporting trainingmodule will:

• Help trainers in market research agencies convert the ideas in this book intoa training course that could be used to introduce their new graduate traineesto the principles of ‘new’ market research.

• Assist lecturers on market research courses in colleges and universities tosupplement their ‘orthodox’ teaching on market research with an up-to-dateaccount of how many market research practitioners now operate.

In addition – working in conjunction with the supplementary points we makein the ‘Notes’ section – the training module will help bring alive, with concreteworked examples, many of the general principles outlined in this book.

Acknowledgements

Deciding on the final shape of a book that provides a fresh look at the dataanalysis craft necessitated a considerable amount of drafting. We continuallyhad to check whether our synthesis of existing theory and commercial practicewas pitched at an appropriate level for our audience: newcomers to marketresearch. This placed considerable pressure on Christine Rooke, who typed thisbook, and we would like to start this acknowledgement by thanking her for herprofessionalism and patience in bringing this book together.

We would also like to thank Anne Smith for editing the various drafts, andfor helping to make the book, what we believe, is now an accessible and user-friendly introduction to data analysis for those coming from either an arts orscience background. Thanks also to Paul Costantoura for his insights on howbest to engage the reader.

In preparing the book, it was helpful for the authors to be Directors atCitigate DVL Smith, part of Incepta Marketing Intelligence, the strategic marketintelligence group. This meant that in writing this book we were able to drawon the expertise of various colleagues experienced in innovative data analysis.In particular, thanks are due to Andy Dexter for his ideas, and for supplying anumber of specific quantitative examples.

Thanks are also due to Gavin Mulholland, who contributed some extremelyuseful illustrative practical examples, and to Ian Horritt for his helpful observationson various aspects of Internet surveys, and to John Connaughton for his variouseditorial contributions, designed to help make sure that we struck the appropriatebalance between the art and science, and the theory and practice of commercialdata analysis. Finally, a big thanks to Jo Smith, for helping us, throughout thewhole process, to make difficult decisions about which of our data analysis ideasshould go forward into print, and which should, for the time being, remain onthe developmental drawing board. So in many ways, this book is a Citigate DVLSmith team initiative. Thanks to you all.

1 ‘New’ market research

Summary• Market research is moving away from its roots as a discipline that was

detached from the business decision-making process, and is now moreactively engaged with decision-facilitation.

• This shift has required new methodological thinking: an ‘holistic’ analysisapproach that provides clients with a rounded view of what all their(qualitative and quantitative) marketing evidence is saying.

• The new approach also requires analytical frameworks that com-bine hard market research data with prior management knowledgeand intuition.

• These new frameworks must be disciplined: intuitive thought can bepowerful, but it can also be wrong. The new holistic approach to dataanalysis therefore needs to be based on the rigorous evaluation ofprior management knowledge, as well as drawing on conventional dataanalysis methods.

• We introduce a ten stage guide to analysing market research data inan ‘holistic’ way. The ten steps are: analysing the right problem; under-standing the big information picture; compensating for imperfect data;developing the analysis strategy and organizing the data; establishingthe interpretation boundary; applying the knowledge filters (what weknow about the survey process); reframing the data (to give us freshinsights); integrating the research evidence and telling the researchstory; decision-facilitation; and completing the feedback loop (evalu-ating the effectiveness of the research data in achieving a successfuldecision outcome).

• In sum, in this opening chapter we explain how the evidence availableto market researchers is changing, as a prelude to outlining the criticalthinking skills – the interpretation power – needed to master the newworld of information.

2 ‘New’ market research

Reducing uncertaintyThe underlying principle behind market research is powerful, yet simple. Marketresearch is about helping individuals make informed, evidence-based judgementsand decisions. It is about asking intelligent questions of users, and potentialusers, of products and services about their opinions and experiences, listeningcarefully to what they say, and then interpreting the implications of this feedback.This interpretation is then used to help organizations reduce the uncertaintysurrounding various decisions that need to be made.

The idea has been around for nearly a century. Thus, today, it is commonplacefor businesses, and public sector organizations, to use customer feedback as oneof the inputs into their marketing strategies and public policies. There is little signof there being any downturn in the demand for market research. Who, after all,would speak against taking all the relevant soundings on any issue, interpretingthese viewpoints, and taking this into account when making a decision? Theissue is not about whether or not market research is useful, but a question ofhow research evidence should be interpreted.

Interpretation powerInformation was once power. But, today, the power lies in interpreting whatinformation really means. In the hands of a skilled analyst, survey data mayunearth invaluable insights into what makes people ‘tick’. But the same data,in the hands of a journeyman analyst, may lead to a creative idea being stifledat birth. The need, therefore, is to cultivate the talent, skill, and techniquesrequired to make sense of customer data. It is this issue – the intelligent, holisticinterpretation of market research data – that is at the heart of this book.

The drivers of new holistic market researchIt is possible to identify several distinct developments that have shaped the grow-ing demand for a more holistic approach to the analysis of market research data.

Clarifying contradictory market signals

The sheer amount of market and customer information available has increasedphenomenally. There has also been a change in the type of information used toinform decisions. Increasingly, use is being made of data that are more imperfect,messy, grey, and less robust than many of the sources used in the past.

The challenge for market researchers is to develop the skills and techniquesneeded to weave a story from a combination of different, less than perfect,often confusing and contradictory, information sources. Researchers can nolonger restrict themselves to working with single, reasonably robust, sources ofcustomer opinion.

From detachment to engagement 3

Providing grounded business acumen

There is also the expectation that market researchers will operate with a soundcontextual awareness of the wider, strategic business picture. Market researchersare required to have a mature understanding of what the client’s business is tryingto achieve. This has been a driving force in encouraging market researchers toput their heads above their hitherto methodologically defined parapets.

Understanding the complete customer

Market researchers are now expected to better appreciate the ‘complete’ customerexperience. As companies strive to build a complete picture of a customer’sinteractions with the organization, so too are researchers required to stretch theirthinking to find ways of capturing and understanding a wider range of customerdata. For example, to understand how a customer relates to a bank, it becomesimportant to capture that individual’s experience across the various personal,business, current and savings accounts they may hold at the bank, and also atother financial institutions.

The quest for understanding and ‘insight’

The word ‘insight’ has many different connotations. Yet whatever the exactinterpretation placed on the now rather overworked ‘insight’ word, there is aclear message here from clients: they want more originality, innovation, clarity,and depth of thinking from their market research analysts.

Bridging the data-decision gap

Users of research data want the market research industry to be more committedand involved, than in the past, with the decision-making process, and with theinitial implementation of decisions. Decision-makers, assailed with often bafflingsignals from massive amounts of information, need researchers to cut through thiscomplexity. They want researchers to say what the data really means, rather thanto sit back and adopt a more detached, data-centric position. The informationprofessionals who can add this value will be at a massive premium in the future.

From detachment to engagement

In response to the above demands, we have seen the arrival of a new approachto data analysis that represents a significant change from the original conceptionof market research. Market research began as a discipline based on the model

4 ‘New’ market research

of psychology, sociology, anthropology, and other social sciences. Its start pointwas the classic notion of ‘research’: detached, objective, and keeping as close aspossible to the agreed principles of social science-based inquiry. It was a modelthat worked hard to differentiate professional survey research, from canvassingand selling (under the guise of research). This tradition gave us an industry witha sound set of research practices and a well-established code of ethics.

Factoring intuition into the analysis process

This approach was right for its time and the ‘detachment’ model has much tocommend it. However, users of market research are now looking for an approachthat is better equipped to handle the ‘messiness’ of today’s data, and one that‘engages’ more with the end decision-maker. Classic, objective analysis of single-survey findings is only the start point. Today’s researcher has to both make useof the best of traditional survey methods and also embrace more intuitive inputsinto decision-making.

The arrival of ‘new’ market research

In describing how ‘new’ market research is different from the ‘old’ modusoperandi, it is helpful to think of market research as operating on the followingfour fronts. First, how the quality of each piece of evidence will be assessed(robustness). Secondly, the extent to which the new incoming information willbe assessed relative to relevant and related past evidence (context). Thirdly, thetechniques used to evaluate the meaning and significance of each item of data(evaluation). And fourthly, the way in which the research findings are presentedto the client (application).

It is possible to characterize old market research as being represented by theinner shaded area of Figure 1.1. This illustrates how old market research typicallyfunctioned on each of the above four fronts:

• Robustness: the emphasis, in the past, was on working with orthodox concepts,such as ‘validity’ (is the evidence measuring what we think we are measuring,and free from any systematic bias?), and ‘reliability’ (how likely is it thatthe data will hold good over time, and that we will be able to reproduceour results?).

• Context: in the past, most market researchers would get no further than check-ing their new incoming study against, maybe, one past related research report.

• Evaluation: this would inevitably focus on examining one data set and involvethe application of (classic) statistical tests.

• Application: the study would conclude with a presentation of the researchfindings, possibly with some recommendations for action (but would not beclosely related to the subsequent decision-making process).

The methodological challenges for new market research 5

Decision facilitation: assessingthe safety of putative decisions

Compensating for error inimperfect evidence

DATA

Validity &Reliability

Research evidenceand recommendations

Com

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olis

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Sta

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Com

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a previous study

Com

pared to a synthesis of allevidence in m

arketing information system

Application

RobustnessE

valu

atio

n Context

Figure 1.1 – The scope of ‘new’ market research.

New market research takes us into new territory. This is summarized by theactivities shown in outer white panel in Figure 1.1:

• Robustness: the emphasis today is on ‘compensating’ for the imperfection inthe varied data sources that market researchers now draw upon.

• Context: the availability of marketing information systems usually means thatnew market research evidence will be set in a much richer context thanever before.

• Evaluation: orthodox statistical analytical methods will be employed alongsideframeworks aimed at factoring prior management knowledge (intuition) intothe data analysis process, with this involving the analysis of multiple, not justsingle, data sets.

• Application: new market research goes beyond simply presenting researchfindings and making recommendations, with market researchers now muchmore closely involved with decision-facilitation.

The methodological challenges for new market researchThere are three distinct methodological challenges in building the new holisticmarket research approach outlined above:

6 ‘New’ market research

• The first focuses on finding actionable frameworks to help combine qualitativeand quantitative evidence when tackling business problems.

• The second centres on how to develop frameworks to incorporate manage-ment intuition into the formal data analysis process.

• And the third involves synthesizing what we know about the overall mar-ket research ‘craft’ – what we know from experience does and does notwork – into a form that can be made accessible to data analysts, so that thiscan enrich their interpretation of the data.

We briefly examine these three issues below, but we also return to these majorthemes throughout this book.

Integrating qualitative and quantitative data

Holistic researchers tend not to think of qualitative and quantitative researchas separate disciplines. The emphasis is on finding ways to integrate the twoforms of evidence. Holistic researchers recognize the power of the rigorousstatistical analysis of quantitative data, but they also see merit, on occasion, inanalysing quantitative data in a qualitative way. Similarly, the holistic researcherunderstands the benefits, where appropriate, of not only examining qualitativedata in a thematic way, but also subjecting the evidence to a more quantitatively-orientated analysis.

Distinguishing the qualitative ‘method’ from the qualitative ‘mode’In interpreting the increasingly blurred methodological boundaries betweenqualitative and quantitative evidence, it is helpful to draw a distinction betweenthe qualitative ‘mode’ and the qualitative ‘method’: that is, to explicitly delineatethe idea of the qualitative mode of analysis from the qualitative method ofdata collection.

Most are quite comfortable with the – albeit blurred – distinction betweenqualitative and quantitative data collection. But what happens to that data is adifferent matter. We argue that the qualitative mode – an open and flexible wayof thinking about data – should not be restricted only to the qualitative method.It should be extended to apply also to the quantitative method.

Certainly, the idea of defining ‘qualitative’ as a way of thinking that can beapplied to all forms of data is consistent with dictionary definitions of the terms‘qualitative’ and ‘quantitative’:

• Qualitative: involving, or relating to, distinctions based on qualities, con-stituents, or characteristics.

• Quantitative: involving, or relating to, considerations of quantities – amountor size.

In sum, the qualitative mode is a powerful concept, one that should not berestricted to the qualitative method. It can add insight to almost any piece of

The methodological challenges for new market research 7

information. In fact, there is no reason why the qualitative mode of analysiscannot be expanded to encompass all forms of marketing evidence. In the matrixin Figure 1.2, we illustrate the way the qualitative mode of thinking can apply toeither qualitative or quantitative data.

QUALITATIVEMETHOD

QUALITATIVEMODE

QUANTITATIVEMETHOD

QUANTITATIVEMODE

Structured samplesContent analysis

TabulationsSignificance testing

Identifying commonthemes

Directional trends

Impressionisticand powerful

accounts

Classicaltechniques

Holisticapproaches

Less people, moredata per person

More people,less data per person

Figure 1.2 – Distinguishing the qualitative ‘method’ from the qualitative ‘mode’.

Many will argue that, working across the qualitative/quantitative ‘divide’ iswhat they already do, and in some cases, this may be true. But the point is thatthe qualitative mode has only been sporadically articulated as a skill set in itsown right, separate from the business of collecting data – the qualitative method.We believe that in promoting the holistic school of data analysis, the articulationof our concept of there being a qualitative mode, not just method, concentratesthe mind and helps us to define what holistic data analysis is all about.

This observation challenges quantitative researchers to bring the same level ofattacking interpretation to the numbers as qualitative specialists routinely deliverbased on fewer, but deeper, observations. The challenge to qualitative researchis to take what we define as the ‘qualitative mode of thinking’ out of its ratherintrospective methodological box.

Developing analytical frameworks to embrace prior managementknowledge and intuition

In the past, it seemed that business problems were tackled via two, almostmutually exclusive, channels of thought. There would be the ‘traditional’ market

8 ‘New’ market research

researchers, with their scientific data, in one corner, and in the other, we wouldfind entrepreneurial business leaders, such as Richard Branson and Anita Roddick,talking up the virtues of looking at business problems from an ‘intuitive’, ratherthan just data-led, approach. Now, it is increasingly recognized that ignoringmanagement intuition on the grounds that it does not meet the formal criteria of‘scientific enquiry’ is ill-advised.

Intuition as an ‘organized’ processA key point to acknowledge is that, if we arrive at a solution using our intuition,it does not mean that we did not adhere to an organized process. If we arriveat a solution by intuition, it simply means we got there without consciouslyknowing how we did it. It does not mean we have not been following a soundset of principles. After all, Alan Turing broke the Enigma code by combininghis brilliant, deductive mathematical logic, with his intuitive insights about howa young German soldier, asked to follow the operation manual for the Enigmamachine, might actually behave in a hostile wartime environment. Anotherpowerful analogy is the idea of modern day holistic data analysis being a kindof musical ‘jamming’ session. When musicians jam a jazz piece, invariably theydo not just invent something completely new. They tend to start working aroundreasonably traditional structures, and only then begin to improvise out from thismore conventional starting point.

The power of archetypal evidenceThe fact that market researchers may, in the past, have been dismissive of so-called ‘anecdotal’ or ‘intuitive-based evidence’, even when it was being advancedby seasoned marketing professionals, has been largely unhelpful. A more con-structive approach is to think of the powerful intuitive insights provided by seniormarketing management as being potentially rich, ‘archetypal’ evidence. (That is,evidence that is not simply an isolated snapshot of one individual’s ‘personal’perspective on the world, but the sum of a rich body of reinforcing experiencesbuilt up over many years across various markets, and corroborated by whatothers also think.) This archetypal evidence, albeit informal, is indeed worthy tosit alongside formal survey evidence.

Market researchers have made progress in accepting that intuition – knowing,without knowing why – is not a mystical phenomenon that sits outside the formaldecision-making process. However, the pendulum must not swing too far. It willbe unhelpful if intuitive reasoning becomes exclusively associated with flair andcreativity, and the evaluation of the hard customer data is relegated to beinga dull and lacklustre irrelevance. This would be dangerous because, as we allknow, hunch and intuition can often be plain wrong. The key to success is, ofcourse, combining ‘informed’ intuition with the rigorous scrutiny of data.

The methodological challenges for new market research 9

Data is dumb but beliefs are blindArriving at what we might describe as ‘informed intuition’ represents a majorchallenge. On the one hand, we are all attracted to the power of ‘intuitivethinking’: we are all aware that many successful business people claim that they‘just know’ what the different signals and messages are telling them to do. Butbeliefs, unsubstantiated and unchecked, can be ‘blind’. Not all of intuitive thoughtwill be correct. It can enrich the analysis process, but it can also point us in thewrong direction.

However, if we totally resist intuition, this can stifle our understanding. Totallyliteral, uninspired reportage of customer data will often be plain ‘dumb’. Withoutthat extra flair, insight, and indefinable hunch, the true power of what the data istrying to tell us may be lost.

In sum, truly informed business decision-making requires a combination ofintuitive thinking skills, and a rigorous interrogation of all of our evidence.We need to embrace intuition, but only in the context of controlled analysisframeworks and with appropriate checks and balances. Responding to thischallenge is one of the central preoccupations of this book.

Developing an account of how new market research ‘works’

There is a gap in the methodological literature between the ‘classic’ (and oftenstatistical-based accounts of how market research ‘works’) and the more pragmaticand flexible (yet still rather vague and abstract) approaches being advocated bythe emerging holistic school of data analysis.

We do, of course, have a general appreciation of the way holistic researcherswork. But this falls short of providing a practical step-by-step guide to holisticdata analysis. The absence of a comprehensive organizing framework, explainingthe holistic approach to data analysis, makes getting to grips with the art andscience of the market research ‘craft’ – a mixture of classic social scientific enquiryand practitioner know-how – a particular problem for newcomers.

There are numerous excellent books, from leading academics in the field, onthe theoretical grounding behind market research. There are also numerous firstclass contributions from practitioners on various specialist aspects of the marketresearch process. But there is a limited number of books that – based on anoverview of market research theory and practice – provide a transparent accountof how market researchers now interpret their data in a more holistic way.

Developing an organizing framework to help us learn about holistic analysisis now vitally important. If we do not spell out exactly how market researchers,in ‘real life’, actually analyse data, there is the danger of an ‘anything goes’approach emerging to the way research evidence is used for decision-making bythe commercial and public sectors.

10 ‘New’ market research

The challenge of developing a ‘universal’ frameworkWe strongly believe that there is tremendous value in developing a universalframework that explains how new (holistic-based) market research really works.Here, we fully accept that developing any unified account of how such a broadchurch as the ‘market research industry’ operates will be open to challenge. Itis an industry with many varied niches, ranging from focus group specialiststhrough to those who are experts in undertaking Internet surveys.

Fitness-to-purposeIn mapping out a universal framework, we must also be mindful of the dangersof implying that there is a set standard that operates across different businessproblem-solving scenarios. This is clearly not the case. Market research is aboutfinding solutions to business problems that are ‘fit-to-purpose’. It is a way ofreducing uncertainty in business, rather than an attempt to always model itselfon the ‘classic’ tenets of what constitutes pure scientific enquiry. So, in certainsituations, the appropriate approach may be a ‘classic’ research study, possiblyrequiring an experimental design, that delivers high levels of methodologicalrigour. Yet, in other scenarios, the appropriate research design solution may beone that only provides broad insights and directional guidelines, with a much lessrigorous methodology. Thus, in outlining our approach, the reader needs to relatewhat we are saying to the nature of the marketing problem under investigation.

A synthesis of key theory and best practiceThere have been few attempts to synthesize what the market research industryknows about the interpretation of data into a single book that would serve as abasic introduction to the holistic interpretation of market research data for new-comers. One reason for this is that providing a synthesis of best market researchtheory and practice – the art and the science – requires making difficult decisionsabout which points, from the vast body of literature available, to draw upon.It is literature that incorporates statistics, psychology, sociology, anthropology,marketing, economics, geography, communications theory, and much more.

In addition, much of this literature is difficult to access for the busy marketresearch practitioner, locked as it is in many important, but sometimes obscure,tomes. A further difficulty is that any account of everyday market research analysisalso relies on a body of knowledge that exists mainly in the form of proprietarytechniques and knowledge that is housed within individual market research agen-cies. Clearly there is a limit to the extent to which different agencies – keen to seeka commercial advantage – will put this body of knowledge in the public domain.

An overview of our ‘holistic’ data analysis frameworkBefore outlining what we have elected to label our ‘holistic’ approach to theanalysis of market research data, a brief explanation of why we have opted toalign our approach to data analysis with the word ‘holistic’.

An overview of our ‘holistic’ data analysis framework 11

Why call it ‘holistic’ data analysis?

We favour the word ‘holistic’ because it explains the broader, richer, and fullerway in which new market researchers now successfully operate on the widermarketing information stage, offering strategic advice based on a groundedunderstanding of why customers say what they say. It is a term that neatlyhighlights the way market researchers now operate in a more integrated way,drawing together different types of desk, observation, qualitative and quantitativeevidence into a combined whole, rather than just analysing solitary pieces ofuncoordinated evidence. We believe that the word ‘holistic’ also effectivelyconveys the way in which researchers are now much more ‘engaged’ with, ratherthan remaining ‘detached’ from, the decision-making process.

Of course, the word ‘holistic’ is not perfect. To some, it will suggest anapproach that lacks credibility and does not have any ‘scientific’ underpinning.It is also a word that could be seen as rather faddish. Notwithstanding this, webelieve that the word ‘holistic’ provides a useful shorthand for conveying whatclient organizations now want from the market research industry. Clients arelooking for an integrated, insightful understanding of what all their customerevidence is telling them. They want their data to have been inspected by anindependent third party for its resonance with prior management thinking onthe subject, and they want their data presented in an explicit, transparent, andactionable way that enhances the decision-making process. The word ‘holistic’seems to convey many of these dimensions.

Our ten-stage framework

Our approach guides newcomers to market research through ten stages for betterunderstanding the craft of holistic data analysis. Our framework lays out ideasand suggestions aimed at helping the analyst go beyond the data, to provideinsightful interpretations. But our framework is not intended to be exhaustive.Our model can be no more than a set of general principles which we believe allinterpretations of data, at least in part, should, as a minimum, take into account.Many of the techniques to which we refer have their origin in qualitative research,where the holistic interpretative approach comes naturally. But, at each stage ofour framework, we always demonstrate how holistic data analysis principles canbe applied, in a fluid way, to both qualitative and quantitative evidence.

• Analysing the right problem: we start with the all-important issue of ensuringthat we understand the real problem that drives the analysis requirement. Getthis wrong and no amount of data analysis skill will save you.

• Understanding the big information picture: next, we explain how holistic dataanalysts make use of all the available data on the problem. The holistic analystknows how to combine clues, anecdotes, archetypal evidence, qualitative