Drugi jezik na kojem je dostupan ovaj članak: Bosnian
By: Zenel Batagelj, VALICON
Today (March 10th) is the day when the book Small Data is finally available in our part of the world, technically speaking in Europe, not that far from civilization. The book actually came out about 14 days ago, which was when we could order it, and then wait and wait, trusting that it would come within less than 14 days, when the electronic version was announced. So, theoretically, it came out on 23 February, but today it’s finally available on Kindle.
Aaaaa-ha
In the new “disruptive” world we can – or perhaps we have to – look at every single phenomena that is self-explanatory, such as the release of a book, from a distance. We have to try to understand it in a new, unencumbered way. This is the key message of the last three of Lindstrom’s books about good business insight. For that real Aaaaa-ha, it’s necessary to forget everything you know about the phenomena and really dig deep into what’s really new, how technology in general has changed habits and where the business risks lie and, of course, the opportunities.
So, if we understand the concept of the publishing of a book, that we buy the book and instantly begin to enjoy it, for such people the real date of the book’s roll-out is today. For those who want to have a physical, paper version, that moment is probably when they get to hold the book in their hands. Maybe therein lies the small clue as to why Amazon decided that quick and efficient (books) distribution is a key part of their business model. For those who do not understand English, the release of the book is only when it’s translated into a language they understand. In Slovenia, for example, the book will come out on March 17th, in the edition of Marketing Magazine.
So… where is the business Aaaaa-ha? For now there still exists a time lag between the release of the book in the United States and the electronic release. Assuming that local readers want to read the book in any language, it is very significant that translations come out before the electronic version, otherwise there is a risk of losing a significant number of potential buyers. Marjan Novak – hint hint for next time ;)
They say that there is a silver lining to every cloud, and I witnessed that a few years ago when our apartment burned down. What could possibly be good in that? I instantly got rid of things that had long cluttered the closets, and above all, my darling Mirna got a new kitchen. Who knows when it would have happened otherwise? :) Why this example? Where in such small clues hide unimagined business opportunities – what interesting insight does this story bring, for example, to insurance companies?
So, as I waited for the book, I chewed some of Martin’s recent works. When I finally came to Small Data, I was a little disappointed at first because many examples are repeated throughout all the books, and I can’t shake off the feeling that Martin Lindstrom is the biggest promoter of the LEGO brand in the business community. And yet, when you take a more detailed look at the examples, he always views the same brand from the perspective of the particular book.
Who is Martin Lindstrom?
… apart from being the biggest promoter of the LEGO brand in the business community? If your business is in any way connected to marketing, if you are one of those C* (C-stars, which has nothing to do with the Belgrade Red Star football club fans), if you come from the R&D department, if you are a brand manager or work in an agency, it’s almost impossible for there not to be at least one book by Martin Lindstrom on your shelf.
I first “met” him in 2004, when he published the book Brandsense, dedicated to brands and how we experience them with all our senses. Back then I was interested in this primarily from the standpoint of understanding FMCG brands. Today this book, which is more than a decade old, is still one of the key works for the proper understanding of brand signals in the context of brand identity development.
Martin is Chuck Norris of marketing – he was always the first. He was the first to seriously deal with branding in the context of the internet, he was the first to deal with the senses, and he was the first to tackle the use of neuromarketing and the scope of the subconscious in advertising. Unlike Chuck Norris, he’s not only the first, but he usually leaves behind trends in the business community that last for several years at least.
His last book was named the most important book of 2016 in the opinion of Inc. (and it’s only March) and was declared a “must read” by Forbes.
Small Data
Small Data is a quite unexpected title for Martin. Instead of from a famous author, we would expect such a title from some Davenport as a logical “next-step” in the series of his works dedicated to data and analytics. Small Data – there’s probably not a single hero in the business world who wouldn’t think first of Big Data.
But Martin Lindstrom is a marketing guru and he achieved his goal. In the book foreword, Chip Health – yet another important author – pays great attention to the distinction between big and small. The very first sentence: “In today’s business environment, Big Data inspires religious levels of devotion and Martin Lindstrom is an atheist.” Promising!
But in the book itself you have to wait for the final showdown of the seven chapters of examples of business stories that found their Aaaaa-ha moment in Small Data. Only at the end is there an unexpectedly gentle duel with Big Data – and if we disregard the introduction, Big Data is mentioned only twice until the last chapter, and even in the last chapter it appears a modest 14 times. The feeling is almost the same as if you were to watch a Rambo 10 movie – the film might have a few rounds fired at the beginning, some more at the end, but is on the whole without casualties.
For the examples of the use of analytics, we could hardly say that these are examples of the use of Big Data. It is, in fact, a rather traditional analysis of large databases that can be managed, which, bearing in mind the definition of big data, is certainly not enough. Big Data is in the book obviously for the purpose of the story flow, and to attract more attention. So, pure marketing trick.
If the point of the book was Big, Martin could do that as well, especially given the fact that for the purpose of his book Clicks, Bricks & Brands of 2001, he collaborated with Don Peppers, grandmaster of 1on1 analytics and the father of the ROC – Return on Customer concept.
It’s actually a book dedicated to Small Data, fully and thoroughly, with truly inspirational examples. In marketing, this book could once again provoke a wave of the use of marketing ethnography. It was widely used at the beginning of the millennium, until the beginning of the recession, characterized by syndicated research, the search for instant solutions and the concept that any data is already good-enough. Semiotics, anthropological approaches and ethnography are almost completely lost in such an environment.
I think that the book Small Data will actually sets a new landmark in marketing, which will, at least partially, put an end to the period of instant quantitative good-enough solutions, the period in which form had an advantage over actual content. Bearing in mind that Lindstrom leaves marketing trends behind, I look forward to this – the sun will shine again, the era of content and a deeper insight into business challenges is upon us.
Big vs. Small
The day after the release of the book I reserved time for his first webinar. This is highly recommended for some of the authors. Especially with Martin, whom I think is more than a marketing guru, and is very well acquainted with the principles of the development of business models. His aforementioned book Clicks, Bricks & Brands was, for example, the first book that had an actual on-line supplement, which was even branded – DualBook. Today, due to the development of social networks, that’s really unnecessary, and yet DualBook shows that Martin likes to be first, and what is more, that he likes to brand things.
His books and lectures generally overlap, but not too much – if you read the book, you won’t be bored with the lecture, and vice versa. His online presence is extremely well thought out as well – there are volumes of online materials and they all point to his web page, which is nothing but a landing-page that wants to get to your contact information. The book is actually just the beginning… lectures, conferences, new business-leads. This is how marketing celebrities business model should look like.
At the webinar the relationship between Small and Big was somewhat more equal than in the book, which is logical – there is less time, and you need to state both the introduction and the conclusion. But in addition, the key message, which is perhaps insufficiently stressed in the book, is much clearer here.
1. In a world obsessed with Big Data, the next big thing is the Small Data revolution
If there’s such big hype about Big Data today, that’s certainly not right. In sociology it is clear that if something pulls too much in one direction (ie globalization), there simply must be a counter trend (in that case, localization). Big Data, by definition, simply can’t be all-powerful; it needs the other, soft part – which is Small Data. Small Data does not negate the importance of Big Data, but emphasizes the need for complementarity. Big is not a substitute for Small, nor is Small the substitute of Big. To understand how they supplement each other, it’s necessary to determine what they are both good for.
2. Big Data are just data, their range are correlations
At the core of data concept is analysis rather than emotion. The book has many examples (LEGO, Roomba, Mini …) that explain how Big Data is great for searching for models, anomalies, correlations, but it has many disadvantages because it doesn’t answer “why”. The key is – Big Data alone will never improve our business; for this, it is necessary to understand the Rich, Deep, Small … data.
3. Small Data explain, they are the foundation for breakthrough ideas
An interesting side note – in the 256 pages of the book you will not find a definition of Small Data. Seemingly insignificant behavioral observations containing very specific attributes pointing towards an unmet customer need. Small data is the foundation of breakthrough ideas of completely new ways to turnaround brands.
These are top-notch thoughts, but they still succumb a bit too much to the pressure of accommodating the idea of the book. For more demanding readers coming from data-world, there is too much simplification here. In the search for the meaning of brands and business, Small Data are priceless for the search for new directions. On the other hand, Big Data add value at the level of the processing of individuals, particularly in the service sector. The promise of Big Data somehow goes towards a better understanding of the individual in our databases. Imagine that in addition to the ID of a client you also had a complete profile of everything – all tracks (here we are dealing with other, less detective-like tracks) that the individual leaves behind. The hypothesis that Big Data doesn’t add value on its own is somehow out of place.
Subtexting, Small mining
The title Small Data is obviously a marketing trick, and if you are not yet convinced of this, look at this (promotional) video. After watching the video, it’s clear that Lindstrom is very good at managing the rules of neuromarketing in communication – of course, he was one of the first who really systematically tackled it. The title has nothing to do with the content. It’s better described by its subtitle, “The tiny clues that uncover huge trends”.
Actually, both small and data are problematic. Small is essentially an “oversized” description of detective clues – it’s about something much smaller, hidden from the eyes, the size of a dust particle, hidden from view. And what do these signs have in common with the precise concept of data? Negligibly little.
Small Data also brings two new concepts. The first is subtexting or subtext research, a process of systematically reaching these hidden clues, and how to combine them to develop concepts. The concept of “subtext” has existed for a long time, but it was Lindstrom who introduced it to marketing. Subtexting is the process of the 7C’s, which at first glance are not completely thought out yet, although they show the sequence of activities well enough: collecting, clues, connecting, causation, correlation, compensation and, finally, the concept. It’s certainly an important experiment that could have the potential of ZMET methodology. For my taste it could be better described in the book.
Another new buzzword is small mining, part of the process in which a substitute for analytics is distilled, ie. data mining from the related Big Data. Here, Martin probably went a little too far with his branding-everything mantra, so we’ll probably forget that, but subtexting is worth remembering, keeping in mind quantitative observation – it appears in the book 23 times.
Who really is Martin Lindstrom?
Martin Lindstrom has presented himself in a promotional video – he’s not a trained psychologist, nor a detective, nor a forensic scientist, he is a compulsive collector of clues and a researcher of small data. There’s also a very interesting remark by one of the commentators on the book on Amazon, a priest actually – Martin is a professional observer of people, better than anthropologists, who unlike them has a mission, a clear goal… And all these observers actually represent the “food” for his hidden agenda. From the standpoint of the marketing research of a branding specialist, Martin represents an archetype that all of us can only follow.
So, to summarize … bravo Martin, a top-notch book. My score “a must read by Zenel Batagelj”, if it means anything. BTW, the title is a miss!
P.S.
But the title certainly sells better. Imagine the title “Tiny clues” – would there be an association with Big Data? Probably not … Or the title “Desire Hunter – Discovering the hidden needs of consumers around the world”, would it attract the same attention? Naaaah … see we can learn a lot from the example of the book Small Data ;)