Customer Insight: Complete the Picture With Cross-Channel AnalysisCustomer Insight: Complete the Picture With Cross-Channel Analysis

Are you looking at store-, contact center- and Web-based transactions in isolation? Employing cross-channel analysis, Best Buy learned that best customers are typically multi-channel customers, and it's now personalizing marketing messages with a complete view of customer behavior. Here's a look at the cross-channel trend and its implications for technology choices and operational decisions.

Doug Henschen, Executive Editor, Enterprise Apps

May 28, 2007

6 Min Read
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You track retail store sales, call-center contacts and e-commerce initiatives, but which customers are interacting through all three channels? More importantly, how do multi-channel interactions relate to customer segments and customer life-time value?

Electronics giant Best Buy is well on its way to answering all these questions thanks to customer data integration and cross-channel analysis. "The idea is to create a well-rounded view of the customer," says Matt Smith, senior director of customer insight. "As we've exposed Best Buy to more and more consumers, we're quickly moving out of the customer acquisition game and into relationship building, so understanding the health of the customer relationship across channels is crucial."

With more and more companies interested in getting a complete view of customers, Web analytics vendors are responding with new products, new partnerships and, in some cases, mergers and acquisitions aimed at supporting cross-channel analysis. The question is, where how far will the trend extend, as it naturally points beyond customer insight into operational concerns such as supply-chain and distribution analysis. It also leads to the question as to whether Web analytics vendors can satisfy all the cross-channel analysis and reporting requirements that might unfold? Here's a look at the short-term opportunities and long-term implications of cross-channel analysis.

Understanding and Targeting Best Customers

Best Buy's move into cross-channel analysis began a few years ago when it began blending Web-site and in-store transactional data in a data warehouse designed for deep analysis of customer segments and trends. That effort revealed that the retailer's best customers were usually multi-channel customers, so over the last two years, Best Buy has moved to add non-transactional clickstream data and, most recently, call center data.

"When you look at some of the typical BI and Web analytics tools, they've been pointed at understanding behavior only in aggregate form - how many bought X product, reported Y problem through the call center or looked at Z page on the Web site," says Smith. "We're beginning to do analysis from the perspective of an individual consumer."

Best Buy uses Web analytics software from Visual Sciences (formerly WebSideStory) to collect and export Web clickstream data to the data warehouse. It also uses the vendor's real-time data visualization and analytics software to reveal cross-channel trends by customer segment. The company also uses Unica's Affinium Insight software to develop rules for particular customer behaviors that can then trigger personalized marketing messages.

"If we see that you're doing research online in the home theater space or we see that you've purchased home theater products in a store, we want to tailor our e-mail and direct-mail messages to help you build the best home theater experience," says Smith.

Next on the agenda at Best Buy is extending the personalization capabilities to the Web site and, ultimately, back to the stores. The first step will require redesign work to free up Web site screen real estate for personalization. The in-store personalization strategy is "complicated," says Smith, adding that it may requiring "a couple of years" to put in place. "We think this will really have power if we can inform the blue-shirted sales associates [in the store] with the same insights we're using to make ink and pixels smarter," he says. "A couple of years ago, if you came in to buy a digital camera, we thought about you as buying a digital camera. Now we understand, through watching customer behavior, that you're really trying to build a solution around sharing memories."

(For more detail, read "Crossing Channels: Q&A With Best Buy's Matt Smith").

If Best Buy can inform a sales associate that a customer is, say, a high-value Best Buy Reward Zone member who has purchased a digital camera, the interaction could focus on complimentary merchandise such as editing software, memory cards, backup storage, printers or other accessories.

Jumping on the Cross-Channel Bandwagon

The Web analytics vendor community is clearly entering a transitional phase. Having spent the last few years consolidating technologies for all forms of online analysis - Web site traffic, keyword search, e-mail campaigns, banner ads, RSS feeds and so on - many vendors now view cross-channel analysis as the next big challenge. In many cases they're responding to customers that are attempting to exchange market segment definitions, reconcile online and offline purchasing information, and correlate Web site visits with in-store purchases.

"Companies are coming to terms with an exposition of data from different channels," says Jim MacIntyre, CEO of Visual Sciences. "Customers want to pull together information from ATMs and kiosks, from interactive voice response systems, from messaging systems and from Web sites."

Visual Sciences and WebSideStory merged last year, but the company recently dropped the Web-analytics-oriented WebSideStory name to reflect the importance of cross-channel analytics capabilities developed by Visual Sciences.

Unica's "Enterprise Marketing Management" software also is aimed at cross-channel analysis, pulling together online and offline customer analytics, event detection, and campaign and lead management.

WebTrends is answering customer demand for offline and cross-channel analysis with its WebTrends Marketing Warehouse, a data warehouse aimed at correlating "high-value events" with account histories, demographics and in-store purchases.

If customers can build a cross-channel warehouse through data integration, will they still need separate analysis and reporting tools for each channel? "Now that technologies are maturing, the Web component is being integrated into the business, and the business people are the ones saying, 'I want to see all these things unified'," says Mark Madsen, principal of research and consulting firm Third Nature. "If you look at the BI market, people are trying to standardize interfaces and tool sets and data access so you don't have to go three places to get the data and do multi-variant analysis."

Looking Beyond Customer Insight

Web analytics vendors have tended to focus on customer issues in part because e-commerce initiatives are often led by sales and marketing types, but cross-channel insight could benefit operational decisions as well.

"If you're running a data warehouse, you're not just looking at sales and revenue, you're looking at inventories, pricing strategies and internal process efficiency," says Madsen. "The trouble is, depending on the company, inventories can be controlled by different business units. Some companies are capable of taking merchandise out of a store distribution center and bringing it back for use on the e-commerce front, but other companies are very segregated and can't easily shift inventories around."

Despite the prevalence of entrenched business units and internal political factions, Madsen says the larger trends are leading toward consolidation. As a result, "the BI functions are getting more centralized in terms of the technologies."

So the cross-channel trend may, in fact, favor general-purpose BI technologies, but for now, executives such as Smith of Best Buy seem to have enough of a challenge their hands. "As our relationship with the customer deepens, we have to figure out how to be relevant to millions of customers at a time," says Smith. Solving all analytic challenges and doing so with a single tool set may be next year's - or perhaps the next decade's - challenge.

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About the Author

Doug Henschen

Executive Editor, Enterprise Apps

Doug Henschen is Executive Editor of information, where he covers the intersection of enterprise applications with information management, business intelligence, big data and analytics. He previously served as editor in chief of Intelligent Enterprise, editor in chief of Transform Magazine, and Executive Editor at DM News. He has covered IT and data-driven marketing for more than 15 years.

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