Why retailers need to focus their analytics on consumers

Big data analytics are transforming many industries, and retail is no exception.

But there’s a difference. Unlike some industries, retail needs to expand analytics programs to focus, not only on internal operations, but also on consumers.

Done right, this can empower retailers to make predictions that optimize decisions and operations for both consumers and products.

For example, you might use analytics to foster new customer-focused programs and events. This could improve customer intimacy and drive brand conversion, retention, cross-selling and up-selling. It could also provide great value for your consumers as they get information and guidance that’s relevant to them

But most retailers aren’t there yet:

  • Many businesses can’t yet observe customer-behavior patterns across their channels. This, in turn, hurts their ability to establish metrics, develop new marketing strategies and plan their products.
  • Many retailers operate disparate IT systems with inconsistent views of customer segmentation across channels. As a result, interventions are often needed from non-business entities.
  • Retailers often lack an aggregate view of their structured data and a valuation of the unstructured context. As a result, they’re unable to drive value from their data.
  • Very few retailers are expert at transforming their marketing and merchandising for the digital world. Even more don’t know where to start.

So what should retailers do next? We’ve identified the 4 core elements of consumer-focused analytics:

360-degree view of customers: A single view of customers, including their entire purchase history, personal demographics, shopping preferences, contact information and loyalty-card details. With this information, retailers can make real-time offers for new products and services, correlated with customer preference and context.

Predictive analytics: Using existing and purposefully collected data, retailers can identify consumer segments, predict their behavior (including churn) and understand their buying behaviors.

Integrated omnichannel communication: Retailers need to provide consumers with easy and consistent ways to communicate with their brand, regardless of channel.

Personalized offers: Recommendation engines can help you treat consumers as unique individuals. Customers are more likely to buy when they receive personalized coupons, targeted recommendations and recommendations from their social media circles.

We’ll be talking more about omnichannel engagement and other topics relevant to the digital transformation in retail, in concert with the National Retail Federation’s big show. Connect with me on Twitter (@mdtricky) and read our new position paper Digital Retail & Consumer: Brand Affinity Through Customer Centricity for more insights.


Michael S. Deittrick is an expert in retail and consumer systems. A thought leader in enterprise architecture and business enablement strategies, he is responsible for enterprise solution development and enterprise strategy for the retail and consumer sector.

 

 

RELATED LINKS

Domino’s slices digital data for customer insights

Big data is useless (and even dangerous) without this key ingredient

Hesitant to adopt machine learning in 2017? This might change your mind

Position paper: Digital Retail & Consumer: Brand affinity through customer centricity

 

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  1. Nice article. Thanks for sharing.

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