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Humanizing Big Data: Marketing at the Meeting of Data, Social Science & Consumer Insight
Between tweets, likes, comments, blogs, videos and images, today’s customer is estimated to generate 2.5 quintillion bytes of data per day. How can marketers utilize the ever-increasing amount of data to better understand and interact with their customers?
This book offers advice on how to interpret and incorporate data into an organization’s overall marketing strategy. It is designed to help marketers improve customer relationships, enhance the targeting of their marketing efforts, align marketing activities with ultimate goals and objectives, and gain insight into the effectiveness of marketing campaigns and channels.
Topics covered include: the current limitations associated with big data, the differences between deriving the what, how and why from data, how to use social science to provide frameworks for a smart data agenda, privacy and personal data and the role of market research in a marketing strategy.
This book offers advice on how to interpret and incorporate data into an organization’s overall marketing strategy. It is designed to help marketers improve customer relationships, enhance the targeting of their marketing efforts, align marketing activities with ultimate goals and objectives, and gain insight into the effectiveness of marketing campaigns and channels.
Topics covered include: the current limitations associated with big data, the differences between deriving the what, how and why from data, how to use social science to provide frameworks for a smart data agenda, privacy and personal data and the role of market research in a marketing strategy.
- GenresBusinessNonfiction
224 pages, Paperback
First published June 28, 2014
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437 people want to read
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Displaying 1 - 6 of 6 reviews
January 10, 2017
An extensive literature review. With the downside that it's outdated and Strong often misinterprets the original results and theories. I'm not sure where's the "humanizing" component. Wouldn't recommend it to anyone.
February 2, 2016
My review comes from the viewpoint of someone working in IT.
It is a compilation of "who said what" about big data in other books and sources. There are ~four pages of notes after each (short) chapter.
If you are a novice in the field of digital anything you may find it useful.
As for myself, it reads repetitive, some paragraphs, I have the feeling, were quoted almost verbatim, they were so familiar. It reads as the work of a PhD that desperately needs to fill the pages of his/her dissertation. Unfortunately I did not like it.
It is a compilation of "who said what" about big data in other books and sources. There are ~four pages of notes after each (short) chapter.
If you are a novice in the field of digital anything you may find it useful.
As for myself, it reads repetitive, some paragraphs, I have the feeling, were quoted almost verbatim, they were so familiar. It reads as the work of a PhD that desperately needs to fill the pages of his/her dissertation. Unfortunately I did not like it.
April 8, 2015
For some reason even the phrase “big data” seems to put fear in the minds of many who come across the term, yet in many ways it is just like fixing the chimney pot on your house – it won’t be for everybody but with the right training and tools it need not be impossible, as long as you have the right mindset.
This book manages to take the reader gently by the hand and give them an informed introduction to the world of big data, showing them how it can be utilised in business through a marketing-led perspective. Of course, not every company will generate or have a need for big data, yet for those who do it can be a goldmine of opportunities and potential.
The amount of data being generated can be astounding - especially if a company utilises externally produced data sources – and it can feel as one is drowning in a sea of bits and bytes. The author helps identify possible situations where big data sources can be exploited for marketing and customer relationship management purposes, although the harder task of implementation is left to the reader.
Naturally important issues concerning privacy, data protection and industry best practice are also considered so you hopefully won’t shoot yourself in the foot with your first foray into big data exploitation. In some ways big data might even be a bit of a leveller for companies, allowing the smaller and more agile player to gain market share through their use of big data and intelligent analysis. You just have to be innovative in thought, approach and your use of data-led activities.
Big data does not just refer to the physical amount of data being gathered; it also can relate to the speed it is generated, the range of data being collected and its scope. A lot of the benefits can be realised by sifting through an often fine-grained, relational and flexible series of data for the special nuggets of information that possibly nobody else has yet found to tailor-make your marketing and sales propositions. It might not be a licence to print money, yet it can provide an intelligent, data-led approach to servicing existing customer relationships and attracting new customers without recourse to the old-fashioned shotgun-style approach.
Yet there is resistance, as the author notes: “There is a huge opportunity for brands to make use of big data but it requires a change of mindset. There are many vested interests that have talked about the potential of big data but in a way that maintains a simplistic approach to consumer understanding: allowing the data to ‘speak for itself' rather than thinking about what it means; accepting reductionist views of human behaviour rather than recognizing that a higher-level order of explanation is often needed; using a range of data-derived metrics simply because you can, not because they mean anything; implementing customer management programmes that are efficient because they are data-mediated but not considering the impact on the brand.”
This is a very open, clear book that gives you a lot to think about, even if you have no specific plans or needs to exploit big data. After reading it, you probably will be thinking differently if you had not already been sold on the idea! Looking at the methodologies and structures behind big data usage can still yield benefits in “little data” or “no data” environments. Like panning for gold, you still need to shake the tray and put some effort in…
One good example of the disadvantages of data mining given is relevant in every business situation. Just because the information given says X, it doesn’t mean you have to act on it. The author recounts a business class flight between two European capitals where insufficient catering was loaded so someone had to go hungry. The staff blindly took the data-led approach and decided that the traveller with the lesser status (frequent flyer miles) should receive a downgraded service: a pregnant lady who was gallantly offered the meal of a fellow traveller (with much higher status) when he discovered this brilliant example of customer service, all based on data!
“It is clear that one of the key challenges is for brands to take an intelligent approach to the way in which they critically examine their data assets. I don't think that many organizations have yet properly adjusted their processes for big data sets – a more coherent approach is often required. Once a brand has processes in place that undertake the ‘due diligence' on the way in which data assets are being handled, we can focus on the actions required to drive insight from the data,” notes the author.
Despite this being a very complex, inter-connected subject, this is a fairly light, open and jargon-free read. A pleasurable, thought-provoking book that might be a little shocking for those companies that need a bash around the corporate head with a “clue stick.”
Humanizing Big Data, written by Colin Strong and published by Kogan Page. ISBN 9780749472115, 224 pages. YYYYY
This book manages to take the reader gently by the hand and give them an informed introduction to the world of big data, showing them how it can be utilised in business through a marketing-led perspective. Of course, not every company will generate or have a need for big data, yet for those who do it can be a goldmine of opportunities and potential.
The amount of data being generated can be astounding - especially if a company utilises externally produced data sources – and it can feel as one is drowning in a sea of bits and bytes. The author helps identify possible situations where big data sources can be exploited for marketing and customer relationship management purposes, although the harder task of implementation is left to the reader.
Naturally important issues concerning privacy, data protection and industry best practice are also considered so you hopefully won’t shoot yourself in the foot with your first foray into big data exploitation. In some ways big data might even be a bit of a leveller for companies, allowing the smaller and more agile player to gain market share through their use of big data and intelligent analysis. You just have to be innovative in thought, approach and your use of data-led activities.
Big data does not just refer to the physical amount of data being gathered; it also can relate to the speed it is generated, the range of data being collected and its scope. A lot of the benefits can be realised by sifting through an often fine-grained, relational and flexible series of data for the special nuggets of information that possibly nobody else has yet found to tailor-make your marketing and sales propositions. It might not be a licence to print money, yet it can provide an intelligent, data-led approach to servicing existing customer relationships and attracting new customers without recourse to the old-fashioned shotgun-style approach.
Yet there is resistance, as the author notes: “There is a huge opportunity for brands to make use of big data but it requires a change of mindset. There are many vested interests that have talked about the potential of big data but in a way that maintains a simplistic approach to consumer understanding: allowing the data to ‘speak for itself' rather than thinking about what it means; accepting reductionist views of human behaviour rather than recognizing that a higher-level order of explanation is often needed; using a range of data-derived metrics simply because you can, not because they mean anything; implementing customer management programmes that are efficient because they are data-mediated but not considering the impact on the brand.”
This is a very open, clear book that gives you a lot to think about, even if you have no specific plans or needs to exploit big data. After reading it, you probably will be thinking differently if you had not already been sold on the idea! Looking at the methodologies and structures behind big data usage can still yield benefits in “little data” or “no data” environments. Like panning for gold, you still need to shake the tray and put some effort in…
One good example of the disadvantages of data mining given is relevant in every business situation. Just because the information given says X, it doesn’t mean you have to act on it. The author recounts a business class flight between two European capitals where insufficient catering was loaded so someone had to go hungry. The staff blindly took the data-led approach and decided that the traveller with the lesser status (frequent flyer miles) should receive a downgraded service: a pregnant lady who was gallantly offered the meal of a fellow traveller (with much higher status) when he discovered this brilliant example of customer service, all based on data!
“It is clear that one of the key challenges is for brands to take an intelligent approach to the way in which they critically examine their data assets. I don't think that many organizations have yet properly adjusted their processes for big data sets – a more coherent approach is often required. Once a brand has processes in place that undertake the ‘due diligence' on the way in which data assets are being handled, we can focus on the actions required to drive insight from the data,” notes the author.
Despite this being a very complex, inter-connected subject, this is a fairly light, open and jargon-free read. A pleasurable, thought-provoking book that might be a little shocking for those companies that need a bash around the corporate head with a “clue stick.”
Humanizing Big Data, written by Colin Strong and published by Kogan Page. ISBN 9780749472115, 224 pages. YYYYY
August 3, 2023
In our vastly expansive information age we have never been in more need of true insight. This book is a positive critique of the current tools and frameworks at the disposal of academics, marketers, researchers and business leaders to make sense of data. The most refreshing theme is the author's humanist approach to understanding - consumers, customers, citizens, users - as real people. In a business world overloaded with data, the tendency for businesses is to take a very atomistic approach to the use of data. This book illustrates the need to recognise the more nuanced influences on human behaviour such as context, network effects and our innate irrationalities.
The key messages I took away from this book were:
Misinformation is worse than being under informed. This is an important reminder of how to use data to create competitive advantage and not set off on the wrong path. With a background in market research it's good to see the author apply the same level of critique to existing market research practices as he does to data analytics. This leads him to advocate a middle ground that fuses of both worlds in an attempt to minimise the risk of misinformation.
We are not 1s and 0s, we are human. We must not forget that we, as individuals, are influenced by wider social groups. Our networks and environment influence how we behave and think. There are lots of practical examples of how to apply the social science's rich understanding of human behaviour to how we approach data in the business world.
Strong customer relationships cannot rely on personalisation. Some of the most compelling sections of this book is when the author introduces his own research. The most interesting is the discovery of the uncanny valley effect on brand attachment as a consequence of personalised marketing. Whilst there are increasing returns for brands personalising their marketing, it will ultimately reach a point where it gets too creepy and consumers react adversely towards the brand. This raises lots of questions and debate about how to build relationships with customers in a digital world. As potential solutions, the author discusses data privacy and the use/control of personal data to develop more meaningful value exchanges.
Overall, this is a thoughtful and constructive book that takes a strong viewpoint on how brands can capitalise on the opportunities presented by the data economy.
The key messages I took away from this book were:
Misinformation is worse than being under informed. This is an important reminder of how to use data to create competitive advantage and not set off on the wrong path. With a background in market research it's good to see the author apply the same level of critique to existing market research practices as he does to data analytics. This leads him to advocate a middle ground that fuses of both worlds in an attempt to minimise the risk of misinformation.
We are not 1s and 0s, we are human. We must not forget that we, as individuals, are influenced by wider social groups. Our networks and environment influence how we behave and think. There are lots of practical examples of how to apply the social science's rich understanding of human behaviour to how we approach data in the business world.
Strong customer relationships cannot rely on personalisation. Some of the most compelling sections of this book is when the author introduces his own research. The most interesting is the discovery of the uncanny valley effect on brand attachment as a consequence of personalised marketing. Whilst there are increasing returns for brands personalising their marketing, it will ultimately reach a point where it gets too creepy and consumers react adversely towards the brand. This raises lots of questions and debate about how to build relationships with customers in a digital world. As potential solutions, the author discusses data privacy and the use/control of personal data to develop more meaningful value exchanges.
Overall, this is a thoughtful and constructive book that takes a strong viewpoint on how brands can capitalise on the opportunities presented by the data economy.
October 27, 2015
The ultimate in human intelligence (humint)
This book is mostly about the utilization of the big data generated by humans in their online social interactions. It is a massive and dynamic dataset with valuable links deeply embedded and hidden within it. There are the companion problems of privacy and ownership issues as well. Hardly a day goes by without mention of a major breach of a dataset that exposed personal information to people that could use it for nefarious purposes.
There are some very big plums that can be picked from this dataset, yet there are significant hurdles that must be overcome. Strong does a good job in setting up these scenarios of the value to be acquired as well as some of the major hurdles.
My favorite section of the book by far was the discussion of what is called the “uncanny valley.” This is where pushing a brand or idea forward has a positive response until a critical point is reached where the response reaches a peak and then dramatically declines in a linear manner. The effect was first proposed to explain the phenomenon where robots are met with approval until they start exhibiting too many human traits. Another example cited is where animation was used to create human-like characters for major motion pictures. This is an interesting idea and while not proven, it would explain a great deal about some major marketing failures. It can also explain people reaching a point where marketing hints begins to “creep them out” when they start being too accurate and predictive.
This is a book that does not use technical jargon or expressions to make the points, so the general person working in marketing can understand it. Reading it will at minimum give them some valuable ideas regarding how to execute their next major marketing move. As the political ads for the presidential election are now appearing, it is clear to me that the people running those marketing programs REALLY need to read this book.
This book was made available for free for review purposes and this review also appears on Amazon
This book is mostly about the utilization of the big data generated by humans in their online social interactions. It is a massive and dynamic dataset with valuable links deeply embedded and hidden within it. There are the companion problems of privacy and ownership issues as well. Hardly a day goes by without mention of a major breach of a dataset that exposed personal information to people that could use it for nefarious purposes.
There are some very big plums that can be picked from this dataset, yet there are significant hurdles that must be overcome. Strong does a good job in setting up these scenarios of the value to be acquired as well as some of the major hurdles.
My favorite section of the book by far was the discussion of what is called the “uncanny valley.” This is where pushing a brand or idea forward has a positive response until a critical point is reached where the response reaches a peak and then dramatically declines in a linear manner. The effect was first proposed to explain the phenomenon where robots are met with approval until they start exhibiting too many human traits. Another example cited is where animation was used to create human-like characters for major motion pictures. This is an interesting idea and while not proven, it would explain a great deal about some major marketing failures. It can also explain people reaching a point where marketing hints begins to “creep them out” when they start being too accurate and predictive.
This is a book that does not use technical jargon or expressions to make the points, so the general person working in marketing can understand it. Reading it will at minimum give them some valuable ideas regarding how to execute their next major marketing move. As the political ads for the presidential election are now appearing, it is clear to me that the people running those marketing programs REALLY need to read this book.
This book was made available for free for review purposes and this review also appears on Amazon
January 20, 2016
This title 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.
Displaying 1 - 6 of 6 reviews