Contact BSI
Derrick Daye
888.706.5489 Email us

Category: Big Data

Big Data

Brands Need Big Insights Not Big Data


Brand Strategy Big Data

For over a decade now, UPS delivery trucks in the USA have avoided making left turns. Analysis of tracking system data found that eliminating left turns – which often left the vehicle idling at an intersection for significant periods of time – would save time and gasoline. This is exactly the sort of insight that allows a company to change things for the better, but it can be really tough to find no matter how much data is available to you. 

The initial UPS analysis was conducted back in 2001 well before the hype about big data, but it does indicate the sort of benefits that might be derived from analyzing the masses of data now available to us in business and marketing. Since 2004, UPS claims the no left turn policy has saved over 10 million gallons of gas and reduced carbon emissions by more than 100,000 metric tons.

Would the tracking data used in the analysis qualify as big data today? That all depends on which definition is used. If all UPS vehicles were included in the analysis – about 90,000 at the time – then it would be big data according to Professor Viktor Mayer-Schönberger. An article in the Financial Times reports that his favored definition of a big data set is one where “N = All,” in other words, you do not need to worry about sample bias because everyone or everything is included in your data set.

That, of course, is still one of the biggest issues facing the use of big data today. Rarely does “N=All.” In his article, “Big data: are we making a big mistake? Tim Harford seeks to highlight why big data might lead us astray, citing the examples of sample bias and also hidden causation as reasons why big data might cause us to make big mistakes.

Read More
Big Data

Customer Behavior, Big Data And Little Insights


Every time I step out of New Zealand and into a big economic region, the two things I notice are the crowds and the scale. Looking out over row after row of A380s parked on tarmacs, wrestling for room on a crowded street in a busy Asian city or seeing the world go about its business in a towering CBD, the immensity of humanity and the pace at which life operates is immediately apparent.

Recently I was struck by something else. Quite literally, at the other end of the scale. I was on a train traveling back into Kuala Lumpar from a meeting when I noticed that everybody around me had on headphones – everybody – and to a man, woman and teenager, they were wearing a look that said “Disconnected from the world”. (Of course that doesn’t just happen in Malaysia. I just happened to particularly notice it on this journey.)

And I remember thinking at the time – I wonder why that is? Were they looking to keep the rest of the world away, or were they in fact taking advantage of the opportunity to lock in some time to themselves? Perhaps both. Perhaps neither. It’s strange isn’t it how we are now at a point where technology allows us to be private in public and then public in private within minutes of each other? And the fact that we might want to do both, and feel quite at home doing so, defies simplistic logic.

Which is exactly the point. We’re not logical – and that leads me, in a lateral way, to Walker Smith’s recent Branding Strategy Insider post about Big Data. The numbers we derive from big data don’t lie, but our readings as brand marketers of what that data really means can be seriously misleading. As Walker says, the presumption is that more data means better marketing. Where we go wrong is what we do with the information we receive. “Humans have a hardwired, built-in propensity for seeing patterns … We are still inclined to see patterns or connections where none exist, a problem that is particularly perilous when we are working with large datasets to make important policy or business decisions.”

Absolutely. Big data delivers big patterns, but of course the patterns that make sense to each of us as individual consumers are much more mercurial. Big data matters for the big picture, but it’s a dangerous predicate on which to encourage individual action.

Read More
Big Data

A Brand Marketers Guide To Big Data


One of the big questions on the table for brand marketers is what to do with Big Data. The presumption is that more data means better marketing, but finding the path from more to better is the challenge at hand.

A big part of this challenge is that the flood of data is misunderstood. The term itself, Big Data, focuses brand marketers on the amount of data, an orientation reinforced by infographic hyperbole about the supernova of bits and bytes sweeping through the brand marketing galaxy. But more data matters only if it’s better.

Getting something better from Big Data goes beyond the data itself. In fact, it depends mostly on the ways in which data are analyzed. What the Big Data revolution has stirred up is less about amount and more about analytics, but this is not something that comes naturally to most brand marketers.

A recent survey of marketing professionals by the IBM Center for Applied Insights found that 40 percent are well behind the curve of the analytics required for Big Data. Another 37 percent are further along, but still “limited” and “struggling.” In other words, a little over three-quarters of brand marketers are not keeping pace with the analytics needed to ensure that Big Data produces better outcomes. As Ari Sheinkin, IBM’s VP for Client Insights, put it in an AdAge op-ed, brand marketers are “stuck in a time warp, channeling their inner Don Draper.”

Most worrisome is the finding from this survey that fewer than one in five of this three-quarter slice of brand marketers brings a “scientific approach” to research and analysis. Relying instead on gut and grit may explain why only 23 percent of all marketing professionals say they are “highly effective” at building value through new insights, only 25 percent at capturing new markets and only 32 percent at engaging individual customers. Big Data alone won’t improve any of this. Indeed, more data will make all of it worse if brand marketers put it to use unscientifically.

The first question brand marketers should ask about Big Data is not what to do with it, but what not to do with it. Knowing what not to do is also the best way to see what can be done.

Read More
Big Data

Big Data: Beyond The Bias


Kate Crawford, a principal researcher at Microsoft Research and a visiting professor at the MIT Center for Civic Media, has written a provocative post on the HBR Blog titled, “The Hidden Biases in Big Data.” She quotes former Wired Editor-In-Chief, Chris Anderson, as saying, “with enough data, the numbers speak for themselves.” Crawford then asks, can numbers actually speak for themselves?

Crawford’s answer is a simple no. She states:

Data and data sets are not objective; they are creations of human design. We give numbers their voice, draw inferences from them and define their meaning through our interpretations. Hidden biases in both the collection and analysis stages present considerable risks, and are as important to the big-data equation as the numbers themselves.

I agree. Data – big or small – can no more speak for itself than a goldfish. Big data just makes a long standing problem… bigger. Data must be cleaned and ordered before it can be used, and what numbers mean depends on how we interpret them. I also agree that what we really need is not big data but, to use Crawford’s term, data with depth. This is what I was trying to get at in my post about big data needing a little help.

Chatting to my colleague Bill Pink, Senior Partner, Creative Analytics at Millward Brown North America, he suggests that making use of big data, or any data for that matter, comes back to first principles:

What question are we trying to answer? Do we understand the people, psychology, human relationships, the category or phenomena under study? The upside of the big data is we now have previously untapped assets to help us answer these questions – mobile collection of texts, social media, set top data on TV viewing… that’s the amazing thing. 

And those new data assets can be used to provide a better explanation than if we did not have those data sets to include in the story. But that assumes a framework, analytic approach and tools to evaluate and integrate the data and reach these conclusions. It’s not the presence of the data that matters, it’s the question to be answered and the ability of the new data to take us to further than we were before.

Read More
Big Data Brand Marketing

Brand Marketing: The Opportunity Of Big Data


Brand Marketing Big Data

The era of Big Data has arrived! Yet, few brand marketers seem to properly understand it, at least from the point-of-view of consumers.

Like Noah and The Flood, magazine covers have been foretelling the coming data deluge. The headline “Getting Control of Big Data” resounded from the cover of the October Harvard Business Review above a drawing of a lion tamer reeling backwards, hat flying. Two years ago, The Economist published a special section on “The Data Deluge and How to Handle It” with cover art of a businessman funneling the downpour of data being collected by his upturned umbrella to water a blooming flower. This past July, trade publication Target Marketing asked on its cover, “Are You Ready for Big Data?”

In August, Time reported a story for its general readership about the ways in which Big Data will revolutionize retail. In October, Bloomberg BusinessWeek posted a “Bloomberg West” video interview with EMC CEO Joseph Tucci who declared that Big Data will “transform every industry.”

The McKinsey Global Institute weighed in last year with a white paper entitled, “Big Data: The Next Frontier for Innovation, Competition, and Productivity.” IBM has established The Big Data Hub online as an overview of enterprise applications, including introductory resources for brand marketers such as an infographic summarizing four areas in which Big Data can optimize bottom-line marketing performance.

Big Data numbers are staggering. An Economist video reports that the quantity of global data is forecasted to be an eye-bugging 7,910 exabytes by 2015, over 60 times greater than 2005. This is three times the number of stars in the universe! Twitter alone generates over 230 million tweets each day, equivalent to 46 megabits of data per second.  In this future, says The Economist, people will live in a world of sensors and software in which their “every move is instantly digitized and added to the flood of public data.”

Read More