Humanizing Big Data
Marketing at the Meeting of Data, Social Science and Consumer Insight
(Sprache: Englisch)
Big data raises more questions than it answers, particularly for those organizations struggling to deal with what has become an overwhelming deluge of data. It can offer marketers more than simple tactical predictive analytics, but organizations need a...
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Big data raises more questions than it answers, particularly for those organizations struggling to deal with what has become an overwhelming deluge of data. It can offer marketers more than simple tactical predictive analytics, but organizations need a bigger picture, one that generates some real insight into human behaviour, to drive consumer strategy rather than just better targeting techniques. Humanizing Big Data guides marketing managers, brand managers, strategists and senior executives on how to use big data strategically to redefine customer relationships for better customer engagement and an improved bottom line. Humanizing Big Data provides a detailed understanding of the way to approach and think about the challenges and opportunities of big data, enabling any brand to realize the value of their current and future data assets. First it explores the 'nuts and bolts' of data analytics and the way in which the current big data agenda is in danger of losing credibility by paying insufficient attention to what are often fundamental tenets in any form of analysis. Next it sets out a manifesto for a smart data approach, drawing on an intelligent and big picture view of data analytics that addresses the strategic business challenges that businesses face. Finally it explores the way in which datafication is changing the nature of the relationship between brands and consumers and why this calls for new forms of analytics to support rapidly emerging new business models. After reading this book, any brand should be in a position to make a step change in the value they derive from their data assets.
Inhaltsverzeichnis zu „Humanizing Big Data “
Preface
Acknowledgements
01 This changes everything
The breadth and depth of datafication
What is data?
Defining big data
Qualities of big data
This book
Notes
Part One Current thinking
02 Is there a view from nowhere?
Who are you talking to?
Sources of bias in samples
The upsides of sampling
Bigger samples are not always better
Big data and sampling
Concluding thoughts
Notes
03 Choose your weapons
The perils of vanity metrics
Thinking about thinking: defining the questions
Frameworks to help select metrics
Tracking your metrics
From good data to good decisions
Concluding thoughts
Notes
04 Perils and pitfalls
Dangers of reading data: the pitfalls of correlations
Dangers of reading data: the frailties of human judgement
The pitfalls of storytelling
Mixing up narrative and causality
Is theory important?
Concluding thoughts
Notes
05 The power of prediction
The growth of data available for prediction
How good is our ability to predict?
Understanding the limitations of prediction
Why some things are easier to predict than other: complex vs simple systems
The influence of social effects on system complexity
Building models to make predictions
Learning to live with uncertainty: the strategy paradox
Concluding thoughts
Notes
06 The advertisers' dilemma
Online advertising metrics
Psychology of online advertising
Concluding thoughts
Notes
Part Two Smart thinking
07 Reading minds
The value of linking data sets
Knowing your customers
Understanding who we are from our digital exhaust
The evolution of segmentation
Concluding thoughts
Notes
08 The ties that bind
Why making choices can be so difficult
Simplifying decision-making
The role of influence and 'influencers'
Identifying network effects
The implications of networks for marketing
Exploring the
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importance of social relationships
Concluding thoughts
Notes
09 Culture shift
Seeing the world in new ways
Deconstructing cultural trends
Exploring the lifecycle of ideas through cultural analytics
From verbal to visual: the importance of images
Analysing cultural trends from images
Concluding thoughts
Notes
10 Bright ideas
So what do we need to do?
Centralization vs decentralization
Developing organization-wide networks of experts
Using external networks
Limitations to using networks
Nurturing ideas
Concluding thoughts
Notes
Part Three Consumer thinking
11 Off limits?
How people think about data sharing
Limits to data-mediated relationships
A model for thinking about data-mediated relationships
Overstepping data-based relationships
Looking beyond the data
Concluding thoughts
Notes
12 Getting personal
History of self-tracking
A changing personal data landscape
The relationship between data ownership and empowerment
The pitfalls of personal analytics
Potential solutions for empowerment
Concluding thoughts
Notes
13 Privacy paradox
Teenagers and privacy
The pros and cons of data disclosure
The behavioural economics of privacy
Brand challenges
Trust frameworks and transparency
The trend towards transparency
But does transparency work?
So what should brands do?
Concluding thoughts
Notes
Final thoughts
Index
Concluding thoughts
Notes
09 Culture shift
Seeing the world in new ways
Deconstructing cultural trends
Exploring the lifecycle of ideas through cultural analytics
From verbal to visual: the importance of images
Analysing cultural trends from images
Concluding thoughts
Notes
10 Bright ideas
So what do we need to do?
Centralization vs decentralization
Developing organization-wide networks of experts
Using external networks
Limitations to using networks
Nurturing ideas
Concluding thoughts
Notes
Part Three Consumer thinking
11 Off limits?
How people think about data sharing
Limits to data-mediated relationships
A model for thinking about data-mediated relationships
Overstepping data-based relationships
Looking beyond the data
Concluding thoughts
Notes
12 Getting personal
History of self-tracking
A changing personal data landscape
The relationship between data ownership and empowerment
The pitfalls of personal analytics
Potential solutions for empowerment
Concluding thoughts
Notes
13 Privacy paradox
Teenagers and privacy
The pros and cons of data disclosure
The behavioural economics of privacy
Brand challenges
Trust frameworks and transparency
The trend towards transparency
But does transparency work?
So what should brands do?
Concluding thoughts
Notes
Final thoughts
Index
... weniger
Autoren-Porträt von Colin Strong
Colin Strong is a leading consumer researcher who has worked with a wide range of global brands to help shape their consumer strategies. He uses consumer data to drive insight that was once the preserve of surveys, and to advise on ways to shape new consumer brand relationships. Behavioral science runs throughout his research practice, not only to design experimental approaches, but also to guide data analytics. Currently, he is Managing Director of Verve Ventures, a research consulting firm. He is also a regular speaker at conferences and a contributor to publications including The Huffington Post, Wired, Medialine, AdMap and Market Leader.
Bibliographische Angaben
- Autor: Colin Strong
- 226 Seiten, Maße: 15,6 x 23,4 cm, Kartoniert (TB), Englisch
- Verlag: Kogan Page
- ISBN-10: 0749472111
- ISBN-13: 9780749472115
- Erscheinungsdatum: 01.03.2015
Sprache:
Englisch
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