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More Retailers Embracing Big Data Catherine Salfino

If only stocking a store were as simple as sending buyers to Fashion Week and letting them check of f the outf its they like best. While a good gut instinct f or color and silhouette remains, retailers increasingly accept that big data analysis can tell them what they are doing right — and wrong — so they can give consumers a more holistic and customized shopping experience. At tech giant Oracle, Mike Webster, senior vice president and general manager, Oracle Retail, says the biggest challenge f acing retailers is breaking down existing siloed processes and data stores, as in inf ormation that is stored but not used day-to-day. “Customers look at online, mobile and in-store as essentially one thing — the brand they are interacting with,” Webster says. “Retailers must align their business to meet this reality. Successf ul analytics initiatives require data f rom every part of the business that af f ects the customer experience. So it is not only online, mobile and in-store, but also supply chain and promotions.” On average, consumers say they spend about $72 on clothes each month, a f igure that drops to $43 f or those making less than $25,000 and increases to $101 f or those making $75,000 or more, according to the Cotton Incorporated Lifestyle MonitorTM Survey. With the many retail choices available to today’s consumers, harnessing those dollars becomes as much about understanding the stats as it is about of f ering what designers are showing.

“I think it’s right brain, lef t brain,” says T he Doneger Group’s Tom Julian, director of strategic business development. “T hese numbers are f orming the buy dif f erently,” because a planner is now comparing data with what a buyer wants to stock. Doneger’s Roseanne Morrison, f ashion director, adds that data mining can quickly reveal what is not working.

“T he f eedback where we talk about how many times consumers look and how many times it takes them to buy is very important,” she says. “If you’re getting a lot of hits on your site but people aren’t actually buying, something’s wrong.” Webster echoes this, adding that data analysis can also provide a solution. “As retailers move away f rom static reports and toward more f lexible, real-time analysis, business users can drill down into the areas of the business most relevant to them. So, while analytics are being perf ormed across a comprehensive data set, the results are tailored to a business need and presented in an easily understandable f ormat that enables action.” But today’s consumers are not easily pegged. T hey like to shop both in-store (twice a month) and online (one a month), according to the Monitor survey. Even though they pref er the traditional store experience, most (73%) have browsed web stores, and they spend, on average, 100 minutes shopping f or clothes whether they are in-store or online. Making matters harder f or retailers is the f act that customers like to shop around. T he Monitor shows 64% of shoppers are more likely to build an outf it by buying separate pieces f rom dif f erent stores than buying an entire outf it at one store. And those stores vary considerably: (62%) say they shop at mass merchants, f ollowed by chain (57%), department (41%) and of f -price (35%) stores. T he average consumer is also regularly inf luenced by retailer emails, online ads, catalogs, social “likes” and product reviews. Sailthru, based in New York City, brings the many disparate data points about a customer (site, email, mobile, social, of f line/in-store) under one roof in a complete user prof ile of every individual customer, says Cassie Lancellotti-Young, vice president of analytics. “From there, we are able to transf orm the way that brands build relationships with their customers by automating the personalized marketing based on each unique individual’s pref erences, including send time, send f requency, types of products shown, recommended products — even down to pref erred colors, styles and more.” Cotton Incorporated is looking to help brands and stores guide the direction of their of f erings through its Customer Comments Project. To date, the project has analyzed more than 260,000 comments f rom 25 retail websites, resulting in a collection of reviews f or more than 30,000 denim jeans, knit and woven shirts, dresses, pants and activewear. Comments include the positive — “T hey are my go-to shirts f or working out. I stay cool… and I love how comf ortable it is” — and the negative — “I have been buying [brand] f or years…. T his is a company that has lost its way. I was very disappointed in this tee shirt and would not buy another one. Do not waste your money.” Lancellotti-Young says such inf ormation is critical f or craf ting ef f ective marketing strategies. Sailthru’s platf orm stores customer comments as a variable, so stores can easily query against it f or sending custom campaigns and messages, as well as f or assessing the lif etime value of customers based on the f eedback they give. “Our approach allows brands to operate on what is essentially a 1:1 marketing basis rather than a traditional campaign basis,” she says. “T hink about this way: a customer buys something f rom a brand and is then prompted f or product f eedback, where she rates it a 1 out of 10 and writes a nasty review. Two days later, the brand sends the same user an upbeat business-as-usual email as though nothing negative ever occurred. T he brand looks uninf ormed and insensitive, likely resulting in a lost customer f or lif e.”

This article is one in a series that appears weekly on The data contained are based on findings from the Cotton Incorporated Lif estyle Monitor™ Survey, a consumer attitudinal study, as well as upon other of the company’s industrial indicators, including its Retail Monitor and Supply Chain Insights analyses. Additional relevant information can be found at CottonLif inShare

More Retailers Embracing Big Data | Retail Reports  

If only stocking a store were as simple as sending buyers to Fashion Week and letting them check off the outfits they like best.

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