Posted Date: 4/1/2011

Rethinking Customer Analytics

By Lisa Terry
Capturing the reluctantly spent dollars of today’s post-recession consumer requires retailers to be engaging, personal and relevant. To achieve this, retailers must be able to collect, analyze and act on customer information in near-real time, across all the channels they operate in. Retailers also need to understand how customer behavior differs from channel to channel, while still maintaining a single view of the customer and providing a seamless and relevant shopping experience across all touchpoints.

Relevancy is the ultimate goal for retailers: with relevancy, retailers can go beyond simple customer satisfaction and into the area of customer enthusiasm. Shoppers who are enthusiastic about a retailer’s products, services and overall brand will be more loyal to that retailer—and will be more likely to give that retailer permission to learn even more about them, thus increasing their relevancy capabilities even further.

Yesterday’s analytics technology was never designed for this level of granular real-time response. Retailers looking to take their businesses to the next level must rethink their approach to customer analytics in order to be continually relevant in the face of constantly shifting customer desires.

Data Sources Multiplying
The good news is the unprecedented tide of consumer data available today. In addition to traditional sources such as demographics, psychographics, syndicated data, market research and loyalty/purchase history, retailers can tap e-commerce searches, customer ratings and reviews, redemption rates and activity on social media sites by customers and those who influence them.
Retailers already view customer intelligence technology as providing them with a number of hard benefits. A September 2010 RIS retailer survey reveals that 63.3% of respondents believe customer intelligence helps them increase customer wallet share, and 60% say it supports higher margins, increased comp store sales and reduction of wasted marketing dollars.
Customer data can also inform decisions throughout the enterprise, in areas including:

• Merchandising
• Targeted promotions/cross-sell opportunities
• Marketing
• Product selection/assortments
• Loyalty building
• Optimal location of stores and distribution centers

Unfortunately, access to customer data and the analysis tools required to make use of it has been limited within retail organizations. Many retailers still lack a central repository for customer data that can serve as the basis for an enterprise-wide CRM system. Such a system is essential for activities such as customer segmentation and for deep ad hoc queries into shopping behaviors—necessary for developing the most relevant communication and promotions for each customer group.

Leveraging Advanced Analytics
The more comprehensive a retailer’s view of the customer, the better that retailer is able to understand each customer’s lifetime value, segment customers appropriately, and make informed predictions about shopping patterns—all key to all-channel retailing.

Once a retailer has established strong, timely analytical capabilities and a single view of the customer gleaned from multiple channels and sources, its ability to ensure a relevant customer experience—and a more profitable retail organization—increases many-fold. Capabilities include:

• Relevant, personalized and targeted offers delivered via the customer’s channel of choice, increasing customer satisfaction and incremental revenue while eliminating promotional waste.
• Understanding the variances of customer behaviors among channels, enabling segmentation. For example, one group researches and buys online; another group researches online but buys in the store.
• The ability to impact customer behaviors such as frequency, upsells, cross-sells and market basket size using rewards like tiered loyalty programs, exclusives and pre-sales that are relevant to the customer and enhance retailer profitability.
• Receiving earlier cues to emerging trends, swings in attitudes and the need for changes in customer segmentation.
• The opportunity to differentiate the brand through deep scrutiny of customer sentiment.

Tapping Social Media
Social media adds a new set of challenges to customer analytics, due in part to the unstructured nature of the data it generates. However, solutions are emerging to scrape, filter and segment content from blogs, posts and chats into actionable data. Retailers will also need to find ways to capture non text-based content, such as user-generated videos posted on YouTube.
Historically, retailers have only scratched the surface when it comes to making use of the piles of customer data they already possess. Add social media sentiment to the mix, and they can access a virtual treasure trove of insights into customer behaviors and intentions.

The timing couldn’t be better, because these days consumers award their tightly held dollars to retailers that best cater to their need for customized offers and better value. The ability to offer just what customers want, when they want it, in the way they want to buy it requires robust customer analytics.

Advanced analytical applications leverage a range of techniques to enable deeper dives into customer data, as well as layering this customer data with sales and product information to help retailers segment and market to customers in the ways they find most compelling and
relevant.

The opportunity is now: It’s critical that retailers step up their customer analytics capabilities as they transition to an all-channel approach to business.

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