Consumer Behaviour and Analytics provides a consumer behaviour textbook for the new marketing reality. In a world of Big Data, machine learning and AI, this key text reviews the issues, research and concepts essential for navigating this new terrain. It demonstrates how we can use data-driven insight and merge this with insight from extant research to inform knowledge-driven decision making.
Adopting a practical and managerial lens, while also exploring the rich lineage of academic consumer research, this textbook approaches its subject from a refreshing and original standpoint. It contains numerous accessible examples, scenarios and exhibits and condenses the disparate array of relevant work into a workable, coherent, synthesized and readable whole. Providing an effective tour of the concepts and ideas most relevant in the age of analytics-driven marketing (from data visualization to semiotics), the book concludes with an adaptive structure to inform managerial decision making.
Consumer Behaviour and Analytics provides a unique distillation from a vast array of social and behavioural research merged with the knowledge potential of digital insight. It offers an effective and efficient summary for undergraduate, postgraduate or executive courses in consumer behaviour and marketing analytics or a supplementary text for other marketing modules.
Author(s): Andrew Smith
Edition: 1
Publisher: Routledge/Taylor & Francis Group
Year: 2020
Language: English
Commentary: Vector PDF
Pages: 216
City: New York, NY
Tags: Analytics; Marketing; Transactions; Social Media; Consumer Behaviour; Microeconomics; Consumption; Psychology
Cover......Page 1
Half Title......Page 2
Title Page......Page 4
Copyright Page......Page 5
Table of Contents......Page 6
List of Figures......Page 7
List of Tables......Page 9
Preface......Page 10
Acknowledgements......Page 13
The context of contemporary marketing......Page 14
Why ignore all that data?......Page 15
Let’s find out what people actually do before we attempt to explain it......Page 16
Data identifies individuals/households......Page 17
Data and insight......Page 18
Analytic inquiry......Page 21
Cause, effect and inference......Page 22
1. What are they; what do they denote?......Page 25
4. What questions do these exhibits raise?......Page 26
Key elements of analytics......Page 27
Descriptive analytics......Page 28
Predictive analytics......Page 29
Purposive research......Page 32
Survey......Page 33
Depth and interpretive studies......Page 34
Neuroscience......Page 37
References......Page 38
Loyalty and repeat purchase......Page 39
Customer value......Page 42
RFM......Page 43
Customer lifetime value (CLV)......Page 45
How churn and switching manifests in reality......Page 47
Person C: Oscillator......Page 49
Data types......Page 50
Ordinal......Page 51
Nominal and categorical......Page 52
Transaction data in reality......Page 53
Activity......Page 55
Data dimensions......Page 56
Data dimensions and visualization......Page 58
Features at the individual level......Page 61
Correlation......Page 63
Patterns and structure in consumer data......Page 64
Association at the individual and aggregate level......Page 65
Individual level......Page 66
Aggregate level......Page 67
References......Page 72
Monitoring in the digital space......Page 74
User and usage insight......Page 80
Words and talk......Page 83
Social network analysis......Page 85
Case 2: Riot at a Black Friday in-store sale......Page 89
Case 3: #DontBuyButtybot......Page 90
Case 4: Glastonbury Festival......Page 91
Conclusion......Page 92
References......Page 93
The importance of considering extant research......Page 94
Cognitive school......Page 95
Behaviourist critique......Page 96
Experimentation......Page 97
The challenge of context......Page 98
The challenge of complexity......Page 99
Exogenous cognition: the link between analytics and the emerging consumer......Page 100
Traditional conceptualization of the consumer decision process......Page 101
The impact of smart technology......Page 103
What is exogenous cognition?......Page 104
1. Funnelling, reinforcement and bias......Page 107
3. Consumer welfare: reinforcement and disruption effects......Page 108
5. Direct to device/consumer – individualized......Page 109
EC and the ‘lens’ through which we view extant consumer research......Page 110
Conclusion......Page 111
References......Page 112
Introduction......Page 114
Utility and needs......Page 115
The economic psychology of price and value......Page 122
Sales promotion effects......Page 127
Deliberation and impulse......Page 130
Deliberation......Page 131
Impulse......Page 135
References......Page 137
Brands and marketing communications as signs......Page 139
Learning and memory......Page 145
Trust and persuasion......Page 148
Persuasion knowledge......Page 149
Social and observational learning......Page 150
Heuristics and perceptual biases......Page 152
Schema theory......Page 153
Framing......Page 155
Responses to and effectiveness of MC......Page 157
References......Page 159
Nature vs. nurture?......Page 161
The socio-cultural realm......Page 163
Rituals......Page 164
Myths......Page 166
Norms......Page 168
Group influence and sub-culture......Page 170
Reference groups......Page 171
Brand communities......Page 175
The socio-familial milieu......Page 176
Consumers and ethics......Page 179
Emotion......Page 183
Risk and innovation......Page 186
Personality and sense of self......Page 188
References......Page 192
Applying acquired and extant knowledge......Page 194
Knowledge-driven marketing......Page 195
1. Data harvest and capture......Page 197
5. Validation and testing/reconfigured algorithm......Page 198
8. Marketing outcome......Page 199
Modular Adaptive Dynamic Schematic (MADS) as a contribution to KDM......Page 200
Scenario 1......Page 202
Utility–hedonic blend......Page 204
Image and semiotics......Page 205
Socio-cultural......Page 206
Emotion......Page 207
Psychological biases......Page 208
Application of MADS......Page 210
A cautionary note on ethics......Page 213
References......Page 214
Index......Page 215
