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Massive data flows can make analytics a beast, but new techniques put retailers back in control.
Managing Editor, B2B E-commerce
Ask any retailer, and they probably have a story to tell about managing analytics data. It's a chore many dread, with either not enough data to do much good, or so much data that it's impossible to decide what to do with it all. These days it's more likely to be the latter, as retailers seek to make sense of data streaming in from e-commerce sites, bricks-and-mortar stores, contact centers, e-mail, mobile devices and social networks.
It's one of the toughest jobs in retailing, but if done well it can produce big rewards by attracting customers ready to buy what's offered them.
The key to success, says David Zucker, chief marketing officer of trendy flash-sale retailer Gilt Groupe Inc., is starting out with information that merchandisers and marketers can effectively put to use as they reach out to a broad range of consumers, then building on that data and expertise to run more sophisticated campaigns targeting segments of shoppers with the products they're likely to buy.
Take on too much data, too soon, and merchants and marketers can get overwhelmed. "Getting acclimated with data is step one," Zucker says. "Otherwise, people's eyes glaze over and their heads explode. Merchandising people who aren't accustomed to looking at statistics all day have to first get comfortable with analytics."
Data wish list
As Gilt and other retailers and analytics experts have learned, however, the tools and services for accessing and using analytics data are becoming both more sophisticated and easier to use. "One of the challenges I had for years as a retailer was managing the massive amount of data about customers from web analytics, call centers, e-mail marketing, and our own segmentation of customers," says Eric Tobias, a former co-owner of Batteries.com and now president of iGoDigital, a firm that helps retailers use customer data in marketing and merchandising. "It was difficult to bring all that information together and get a single view of a customer."
To be sure, accessing and using multiple sources of customer data remains a significant challenge for many retailers. A recent study by Unica Software, a unit of IBM Corp. that provides online marketing technology and services, for example, found that 60% of marketers listed "measurement, analysis and learning" at the top of their I.T. wish lists; more than 60% said "turning data into action" was a big organizational issue.
But today, Tobias and others say, new technology and more sophisticated outside services make it more possible for retailers to gather and use data from multiple data sources. With the right mix of technology and expertise, retailers of different types and sizes are finding they can get a better handle on multiple sources of customer data and put it to use to build customer relationships and sales.
Rosetta Stone lifts conversions
One retailer taking advantage of updated analytics software is Rosetta Stone Inc., a publisher and retailer of electronic and interactive language-learning programs. The retailer, which sells online and in physical stores, is using the Online Marketing Suite from Adobe Systems Inc. to better understand where its online customers come from, how they shop on its e-commerce site, and what kind of merchandising and marketing pitches they're likely to respond to, says Shane Li, Rosetta Stone's senior web analyst.
Using the Online Marketing Suite, which makes use of the analytics technology that Adobe acquired last year when it bought Omniture Inc., Rosetta Stone has produced an 8% to 9% lift in its online conversion rate, resulting in a 4% increase in average order value and a 13% rise in revenue per visitor, Li says.
"We have tracking for each marketing channel, so we know where people came from, and we know which groups of visitors were recent demo takers versus which were purchasers," Li says. That's important, he adds, because Rosetta Stone can then respond with the marketing offers shown to be most effective with each customer segment.
Rosetta Stone has learned, for example, that visitors to RosettaStone.com who click a product demo are far more responsive to e-mail offers than visitors that did not view the product demonstration. "Conversion rates are a lot better if we send the e-mail after they view a demo," Li says. To build on that kind of customer activity, the company now places prominently on the lead page for each language an invitation for visitors to enter their e-mail address so they can view an introductory video of its new Rosetta Stone Version 4 TOTALe computer-based language programs.
Rosetta Stone also has found that it can improve conversion rates and sales by placing more videos as well as customer testimonials on other pages of its web site. And it's gleaned some surprising insights about how its customers shop and respond to online content. The data show, for example, that shoppers reviewing materials for one foreign language will often switch to another language program if presented with content about it, helping to reduce cart abandonment. "When shoppers search for a German program, then see an offer for French as well as German, they may switch to French," Li says.
Analytics data can be especially powerful when it comes from more than one sales channel, such as bricks-and-mortar stores and a retailer's web site. Multichannel retailer hhgregg Inc., a chain of about 175 stores selling consumer electronics and household appliances across the southeastern U.S., is using customer data from its store point-of-sale systems along with online data to get a singular, cross-channel look at customers to build more effective online content, says Tobias of iGoDigital, which compiles multichannel shopping data for hhgregg to support its e-commerce strategy.
"Web site analytics alone wasn't really providing the necessary insight to properly merchandise products on the web site," he says. "So we worked with them to get a more singular view of customers across channels." IGoDigital's software uses a unique identifier for each tracked customer, usually an e-mail address the customer provides when making an online or offline purchase.