It’s All About the Platform: What Walmart and Google Have in Common
How do we answer the essential question, “what should we really be selling?”
How do we help our customers connect with their customers and ultimately drive our revenues?
These are some of the pressing questions that two of the world’s largest organizations are tackling in the era of big data. And despite wildly different business models and customer segments, there is at least one approach Walmart and Google share: they’re both building analytics platforms to help solve business issues.
Executives from Walmart Stores Inc. and Google spoke at the IE Group’s recent Predictive Analytics Innovation Summit in Chicago.
Digvijay Lamba, distinguished architect at Walmart Labs, said that the world’s largest retailer is building its Social Genome Platform to drive unexpected insights — and close the gap between decision makers and data scientists.
“What’s happening is there are domain experts — buyers, merchandisers, product managers and others have worked in retail for years and years — these people know the market really well,” said Lamba. “They throw these ideas over the wall to data scientists, who go through the data and come up with these brilliant ideas to answer questions. But there is a wall there. The data scientists are not domain experts. “
“What we want to do is break down the walls,” he added.
To do just that, Lamba’s team is building out its Social Genome Platform. It utilizes external data — social media updates, blogs, transactions, images, media check-ins and location — to map trends across a number of variables, or nodes. Presented as charts and graphs to business users, the information helps Walmart buyers and merchandisers more effectively predict the items that will sell best, particularly in the lead up to big holiday shopping events: Halloween, Black Friday, Christmas.
“The big question we ask ourselves as retailers is: What should we really sell on Halloween [or other holidays],” said Lamba. “Now we have all this external data that is being generated. . . and we can ask all kinds of questions.”
Greg Green, director of Agency Strategy at Google, is also looking to consumer behavior to glean insights that he can pass on to his clients, Google advertisers and marketers.
Green talked about the difficulty of helping his clients understand what’s happening with consumers across channels, when those channels are fragmented — and changing so rapidly.
“What I’ve noticed in the last five years is that things have changed so much faster than they did in the first ten years of my career,” said Green. “Four years ago, half the stuff that I am worrying about now wasn’t even around. And everything is real time. But decision makers have a different perspective. They’re not even worrying about real time. They want to talk about two years ago. But I’m like, ‘look, this big huge event happened 60 days ago and you need to know about it.’ When I say a big event, I am talking about hundreds of thousands of consumers jumping on something. That’s what’s happening.”
Green said things are rapidly changing on the Web front as well.
“Thirty trillion URLS were crawled for search this year. A few years ago, that was only one trillion. There were 500 million Android activations — that’s a super computer in the hands of almost every consumer in the U.S. And they’re no longer just texting. This summer, Google opened up a class called Power Searching; 155,000 people signed up within 30 days to learn how to really search with Google and what to do with it.”
To help its clients connect with consumers across channels and, ultimately, better drive sales, Google has developed the DoubleClick Digital Marketing platform. It looks at consumers across a ‘purchase funnel’ and across channels — video, mobile, search and display — to determine how consumers use each channel at each point in the funnel.
“We’re trying to build a funnel that’s trusted and that’s effective,” said Green. “The platform will make a big difference in cross-channel management and cross-device management, in ways that work operationally and perform well.”