By Michael P. Haydock
In this era of Big Data, facts and opinions are flying fast and furiously. Unfortunately, too much of this outpouring is of little consequence. So it’s incumbent on marketers and other business leaders to figure out how to turn raw data into insights that they can act upon.
Consider the type of info that streamed out in the past couple of weeks concerning the holiday movie and shopping frenzy.
News reports told us, for instance, that The Twilight Saga: Breaking Dawn – Part 2 ranked #1 in Thanksgiving weekend domestic box office movie receipts with a whopping $227 million in ticket sales. Meanwhile, the French art film Rust and Bone took in just $30,196 in limited release in two theaters.
Amid a blizzard of dispatches concerning holiday shopping, we heard that during Black Weekend, the stretch between Thanksgiving Thursday and Sunday, the average American consumer spent $423 — roughly $25 more than they did last year.
These “factoids” may trigger a momentary flutter of mental excitement, but what do they actually mean? Rarely are we provided with the knowledge behind the data that makes it useful. Regrettably, this substitution of facts for insights is a fact of life these days–whether you’re a consumer planning a purchase or a marketer trying to make the most of a business opportunity.
At IBM, we interact with some of the most sophisticated companies in the world. We have learned from working with them that in order to get the most out of Big Data, organizations need to craft comprehensive data strategies and to use a variety of tools and information sources that provide both depth and context. But technology alone isn’t enough: They need to assemble interdisciplinary teams of people with deep expertise in technology, statistics, social networking, specific industries and human behavior.
Coincidentally, three initiatives that IBM engaged in over the past couple of weeks show how this approach can produce a sizable payoff from Big Data. We conducted deep analysis of holiday shoppers’ behavior, analyzed social sentiment concerning holiday movie releases, and announced a new analytics center in Columbus, Ohio, that will eventually employ 500 people.
Our retail analytics team peeled back the onion on the rapidly-changing holiday retailing environment. Their research showed, for instance, that on Cyber Monday the number of consumers using mobile devices to visit online retailers increased by 22.4% over last year, while those using mobile devices to actually make a purchase rose 12%. That’s a clear trend that will prompt many retailers to rethink their mobile strategies.
But the team dug deeper and discovered that mobile shopping habits vary greatly depending on the device people own. They found that iPads and iPhones accounted for nearly 20% of Black Friday online sales, compared to just 5.5% for devices running Google’s Android operating system. What does this mean? Prompted by intriguing data points like these, smart marketers search for additional clues and create a complete story that helps them understand what’s really going on–so they can craft more effective marketing campaigns.
Our social sentiment analytics team is doing the same kind of deep analysis concerning the movie business. They hooked up with the USC Annenberg Innovation Lab to sniff out useful insights from millions of public Twitter musings about the most popular movies playing in U.S. theaters. One surprise they uncovered concerned the vampire flick Twilight: Breaking Dawn Part 2. Before its mid-November release, our index showed positive sentiment toward the movie of 90%. Yet on Saturday, Nov. 24, in the midst of the Thanksgiving holiday weekend, the positive sentiment dipped to 75%.
Did that mean consumers were disappointed with the film? Nope. We discovered that many of the people who used words in their Tweets signaling sadness or disappointment were reacting to the emotional moments in the film or to the fact that their beloved series is ending with this installment. The lesson: It’s vitally important to do the extra work of not only measuring the quantity of chatter via social networks but also understanding how people from particular demographic and psychographic groups use language in social media.
Bottom line, you’ve got to see the big picture–especially when you’re mapping out a data strategy. Separate from our holiday retailing project, we’re helping a major retailer develop a strategy aimed at understanding an important demographic group, people from ages 18 to 24. Many of these youngsters are in school or working at their first full-time jobs. The idea is that if the retailer can cement relationships with them at this stage in their lives, it might be able to secure them as loyal customers for life. But, to achieve this level of trust and intimacy, they’ve got to know these people really well. And that takes a lot of work and a lot of expertise drawn from fields outside the scope of traditional market research.
To master the art of data analysis, businesses are going to need lots of people with new skills. That’s one of the reasons IBM is working with mroe than 200 academic institutions to help traditional students and mid-career professionals expand their understanding of analytics and Big Data. The latest such collaboration is with Ohio State University, and is an element of our plan to set up a new analytics center in Columbus.
IBM employs a lot of statisticians and data scientists. In Columbus, our people will work closely with clients from the upper mid-west, including leaders in the retailing and healthcare industries. The focus there will be on Big Data and on applying cognitive computing technology, including IBM’s Watson, to complex problems our clients encounter as they gather and process ever large volumes of information.
Some people say the essence of analytics is finding a needle in a haystack of data. There’s something to that, but we see things a bit differently. Think of the haystack as the context that surrounds any particular piece of information, and that makes it decipherable, meaningful and useful. We want businesses to take all the hay and spin it into gold.
So, bring on the data! It’s up to smart organizations to transform it into insights.