Feature story: Venture capitalists are funding startups that can help businesses turn the massive amount of data at their finger tips into decision-making action items. But the big data revolution was born almost a decade ago.
It’s the inaugural Extreme Startups demo day at Berkeley Church in downtown Toronto and its CEO Jeff Lawrence’s turn to evangelize his startup to the congregation – and much like a Sunday sermon, the promises he’s giving are hard to believe.
“We’re doubling the revenue of online stores without them actually having to do any more work,” he says about Granify, his e-commerce startup. “We figure out what will influence each shopper. Then we take action convert those people and get them to buy.”
There’s a secret to converting Web site window shoppers into buyers as successfully as a Jesuit converts pagans to Catholicism. E-commerce wonders like Amazon.com know what it is – an algorithm that can evaluate what a person is interested in and dynamically responds by showing them products they are more likely to want. Because Amazon has a massive IT infrastructure behind its e-commerce site – one that has also become an IT services business of its own – it can collect “big data” on the millions of transactions being completed.
This allows Amazon to convert 18 per cent of its Web site visitors into buyers, Lawrence tells the crowd. Most Web stores convert just two per cent. So Granify will help those stores level the playing field by providing the big data crunching capability that made Amazon successful. Its service provides the IT infrastructure of a larger enterprise operation to any modest Mom & Pop Web shop.
But the “big data” trend that Lawrence refers to doesn’t stop there. It’s an all-pervasive trend in the IT market that sees this buzz word attaining just as much clout as “cloud computing.” More startup firms are seeing the opportunity of building a business on the principle of crunching a huge set of previously unmanageable data and turning it into digestible and actionable nuggets.
It’s a trend that’s moving horizontally across sectors and attracting attention from entrepreneurs and venture capitalists alike. In 2012, $28 billion in IT spending was driven by big data demands, Gartner Research says. It estimates that big data will directly or indirectly drive $120 billion in IT spending next year. Coming into the limelight now, the beginning of the big data movement can trace its roots back a decade.
Elephants never forget
That’s when the emergence of open source systems like Hadoop had some in the IT industry feeling like revolution was in the air, recalls Jason Rose, vice-president of solution marketing for business intelligence at SAP AG. While the notion held by some enthusiastic advocates that open source software would eventually disrupt the enterprise software market hasn’t fully come to bear, it did present a common problem the open source community could sink its teeth into.
“Most enterprises have seen their traditional information stream explode,” Rose says. “There’s suddenly a variety of information coming at you from different angles.”
Traditional data bases can’t make sense of the unstructured and transient data that larger firms wanted to understand. In other words, you’re not going to make Microsoft Access records for every customer that visits your Web site in order to track what path they enter on, what pages they visit, and whether they come back later in the month. You need a framework like Hadoop (named after the creator’s son’s toy elephant, because elephants never forget).
Hadoop and some alternatives offer a batch processing method for unstructured data. Derived from Google’s own file system architecture, it enables an application to call on whole clusters of computers to scour petabytes of data. The Hadoop developer community has grown to include large Web brands that build upon its base model to support their massive cloud-based services. Take Facebook’s Hive infrastructure, for one, it’s used to provide data analysis and queries.
Hive mentality leads to user insights
Hive is being used by Toronto and San Francisco based Kontagent to offer in-depth Web analytics to developers, markets, and product managers. Before big data was a hot term, Kontagent was playing in the market, says co-founder and CEO Jeff Tseng.
“We were the first company to put that online, in the cloud, so people could access it without having to use their own infrastructure,” he says. “All of a sudden you have access to what Google had years ago.”
Kontagent can track Web users down to the individual level and glean their social interactions and behavior across multiple channels. It can answer questions for owners of Web sites, mobile apps, and social apps such as whether users are sticking around after they use an app for the first time. The service is about more than just brute force analysis of multiple data sets. About 10 to 15 per cent of Kontagent’s staff are PhD data scientists developing algorithms to pull the intelligence out of the maelstrom.
As the need to track hundreds of thousands or millions of Web site visitors has grown at multiple Web sites, software solutions like Kontagent’s have grown to meet the demand. Its kSuite platform tracks more than 150 million active users of more than 1,000 social applications. Its customers include Konami, Adult Swim, BBC, Electronic Arts, Warner Brothers, and Pop Cap.
Tseng got into the big data game early with Kontagent, but with venture capitalist interest high and the open-source, cloud-based tools readily available, many other big data startups are spilling onto the scene. They’re addressing all different types of industry verticals – from finance to construction to e-commerce.
Big data for babies
Launching at Startup Weekend in Ottawa last June, Allison Gibbins has founded Simplify Analytics Inc. to get more honest – and therefore accurate – customer research data. Drawing on inspiration from her own pregnancy group, Gibbins has introduced BabySimplify as her’s company’s first Web site. It helps expectant parents figure out exactly what they need, and don’t need, for their baby.
The model is almost the opposite of Amazon’s recommendations algorithm, which always is persuading its visitors to buy more.
“We thought we could switch the model it actually benefits the consumer,” Gibbins says. “You’re not using it to get them to buy more, you’re using it to buy smart.”
The business play for Gibbins is to incent expectant mothers to answer research questions honestly. She’s looking segmentation of that demographic into behavioral categories. Baby monitor companies might just benefit from knowing how stressed out certain mothers are to the sound of a newborn’s cry, for instance. It’s about honing products and marketing messages to the right audience.
Much like SAP’s software business has branched out across 24 industry categories to apply its business intelligence software for specific solutions, startups are now cropping up to serve different niches in the big data market. Next, we’ll see what companies take up the offer to gain better data insight.
“It comes back to organizations fundamentally understanding their business model and how they differentiate,” he says.
Granify customers like Four Corner Store have already accepted the big data gospel. They’ve made more revenue since signing up with Granify, and are using that to bring in more customers via Google Adwords, Lawrence says. That’s just one of 50 customers seeing an average of 103 per cent sales uplifts, thanks to Granify’s team that includes two PhD data scientists.
With results like that, cries of Hallelujah may be heard as the big data revolution continues to unfold.