4. On the selling floor
Thanks to the wealth and granularity of data available these days — and the speed at which it is collected — retailers can now gain immediate insights into what is selling and what is not selling, right on the sales floor. That allows them to adjust prices and offers on the fly in order to take advantage of what Guy calls “the retail moment,” which he describes as “the transient opportunity you have where a customer will be responsive to a given offer based entirely on their overall context — who they are, time of day, what they have looked at before and what the offer is.”
Interactive mobile devices in stores offer an important way for retailers to engage customers and collect data about what shoppers are looking for in certain areas, says Paige Handza, retail solutions manager in the end-user computing unit at VMware. That data “can also help the retailer make smarter decisions about what product to place where,” she says, noting that an added benefit of mobile point-of-sale kiosks is that they can make transactions more efficient by allowing shoppers to check out from any location within the store.
5. At the point of sale
Point-of-sale data is the lifeblood of a retail company, says Jake Freivald, vice president of corporate marketing at software company Information Builders. “It's probably more important than any other single data source, because it helps us understand the past, monitor the present, and predict the future,” he says, noting that one Information Builders retail customer, Helzberg Diamonds, calls its nightly upload-and-distribution process for POS data “the pulse of the operation.” POS data, he says, “helps regional managers see what actions they should be taking” — actions that could range from changing upsell offers or dealing with internal store-level issues such as training individual employees on the appropriate way to promote extended-care plans.
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At other times, POS data may need to be integrated with external information for further insights. For example, Freivald says, “if a manager chooses a promotion that's successful elsewhere, a failure to see increased sales might come from bad weather preventing walk-in customers rather than from the promotion itself.”
6. In personalization and targeting
Despite having tremendous quantities of big data and aggregate information on their overall clientele, retailers often capture only small amounts of data on specific individuals, says Rama Ramakrishnan, a senior vice president and chief data scientist at Demandware. “Many retailers face this somewhat counterintuitive ‘little data’ problem,” he says. But thanks to the latest in predictive intelligence based on up-to-the-second data, retailers can leverage data science to personalize content for individual consumers — even those who haven’t shopped at their stores or websites very often.
“By offering more relevant recommendations with concierge-like customer service and personalized specials and promotions,” says Ramakrishnan, “retailers can use data to elevate the overall shopping experience for their customers.”
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