Big data is never far from mind in business these days. So it was not surprising that the topic was front and center at this year’s Montgomery Technology Conference. At the “Monty,” as it is affectionately nicknamed, I had the opportunity to take an active role on the question when I participated in one of the week’s prime-time sessions, “Big Data: Implications for Media, eCommerce, and Enterprises.” My co-panelists included Jon Vein, MarketShare; David Morgan, Simulmedia; Carine Clark, Allegiance; Ravi Viswanathan, NEA; and Eric Best, Mercent. Quentin Hardy, deputy tech editor at The New York Times, posed some very provocative questions as he moderated the highly spirited debate. What is big data? How are businesses beginning to leverage this would-be goldmine of information to optimize both the top line and bottom line? How is big data changing commerce as we know it? And, perhaps most fascinating, what are some of the biggest challenges in realizing its full potential?
(Left to right) Quentin Hardy, New York Times; Carine Clark, Allegiance Inc.; David Morgan, Simulmedia; Ravi Viswanathan, New Enterprise Assoc.; Pelin Thorogood, Anametrix; Eric Best, Mercent; Jon Vein, MarketShare
Let me start by stating the obvious. The biggest challenge about big data is that there is a lot of it. The sheer volume of data being generated (five exabytes every two days…and accelerating!) is producing both a “people” and a “technology” problem. They are related, of course. Cloud-based applications now enable non-IT people to have routine access to big data. However, it is so daunting for the business user to wrestle with information that comes in varieties and volumes never encountered before that people often don’t know what questions to ask of this raw data – or how to do it in an efficient way to derive actionable insights. One of my fellow panelists, NEA General Partner Ravi Viswanathan, summed it up so well: “The question isn’t really about big data, it is about big impact – and analytics is what can deliver that value.”
There’s no question that big data can confer competitive advantage. We now can track the digital breadcrumbs on every aspect of the customer journey as consumers visit websites and brick-and-mortar stores, click ads, monitor their mobile phones for offers, research products and services online, and look for social mentions and recommendations. There’s no longer a clear path to purchase in this multi-channel world.
Advances in analytics – both in technology and accessibility – are starting to enable the business user to make sense out of big data, and marketers are among those most urgently in need of what this data can provide. Big data makes it possible for businesses to crack the customer code, and make the right offers at the right time to the right people through the right channels, essentially transforming an ocean of real-time data signals into right-time marketing.
We are beginning to decipher how, where, and why consumers buy and predict future purchase patterns. Rather than targeting consumers as large groups, we can now reach individuals in personalized ways based on preferences in search and engagement patterns, demographics, and even social and interest graphs. Real-time insights into supply and demand also enable dynamic pricing of goods and services. In this brave new world, “just-in-case” gives way to “just-in-time.” While all this poses privacy concerns for many, the upside to improved relevancy of engagement is so staggering that people – especially younger demographics – are accepting it as the future of commerce.
These advantages are undeniably powerful, but they require marketers to leverage data in ways that have never been possible before. What marketers and other business users need are analytics solutions designed for the people who actually need to make sense out of the data day in and out, rather than for technical teams and data scientists only. The bottom line is that next-generation analytics need to support storytelling with data – verbally, visually, or both.
For some, big data may be the elephant in the room no one wants to talk about. But it’s too costly to ignore. Analytics solutions can address both the “people” and “technology” hurdles keeping business users away from the numbers. The goal is to put useable data in the hands of the people who need it most to drive business results. Powered with big data, drive results they will.
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