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Data Analytics Today: Customizing Products, Services to Match Customer Preference

joedecosmoIn this special guest feature,  Joe DeCosmo of Enova International reflects on how the business world relies heavily on technology to determine customer preferences as a means to deliver personalized service. Joe DeCosmo is chief analytics officer at Enova International, a global financial resource service for under-served consumers. 

Today’s business world relies more heavily on personalization than it ever has before. Not only do customers appreciate customized products and services, but they expect businesses to recognize their preferences and proactively personalize offerings to meet those expectations. Business success today hinges on achieving such intimacy – drawing deeper insights into your customers’ needs to drive better business results.

A growing number of companies are melding their customer-related strategies with sophisticated database and analytic tools to deliver greater personalization in interactions with customers. Some of the most common ways companies generate this customization include:

  • Using predictive models to deliver product recommendations, allowing brands to engage with customers in a highly relevant and timely fashion
  • Employing analysis of customer behavior to guide where to invest resources in product development
  • Leveraging customer data to identify and target priority markets
  • Improving the overall customer experience by providing offers unique to individual customer preferences
  • Applying analytics to operational systems that support critical customer-facing processes to maximize decisions for business leaders

Additionally, companies increasingly are analyzing text to examine how customers describe and perceive a product, brand or service. This approach often generates a deeper grasp of customer preferences, and these insights then let firms develop products and services best suited to individual interests and wants.

Google Now serves as a good example. Google’s intelligent personal assistant uses a natural language user interface to answer consumers’ questions, to suggest recommendations and even perform actions. It even generates and delivers information it expects users will want based on their search habits or even their calendar like driving directions or traffic information for an upcoming appointment

Today, comprehending customer preferences increasingly requires analyzing the avalanche of information companies accumulate from all customer interactions and other emerging communication avenues individuals are embracing. To achieve dividends from this analysis, businesses must understand how to integrate analytics into their operations that scrutinize these mountains of data.

But many companies simply lack the holistic view of their customers’ needs to recognize and react to them in a way that helps forge tight-knit and trusting relationships. Too often, decision-makers are impeded by silos of customer data, poor data quality and misaligned business strategies. These barriers prevent them from developing a comprehensive view of each customer and leveraging the business potential of each relationship.

This is where employing novel approaches can pay off. In the US, a large retailer that relied mostly on anonymous cash transactions launched a loyalty program for customers to earn cash discounts and rewards while also gathering data on their purchases. Suddenly the retailer went from having no data on upwards of 60% of their customers to capturing a majority of their purchases through the program and having that data available for analysis and insights. In another instance, a European retailer, analyzed it’s loyalty club data and found that young families were the biggest spenders. Consequently, the retailer created a baby and toddler club for pregnant women and parents of young children.

The retailer built on this program even more to satisfy that customer base’s needs. It designated special parking spaces close to its stores’ entrances and offered a free magazine providing advice from experts on childcare issues. The result: The company has positioned itself as the retailer of choice for young families, who stand to be loyal customers for decades as their children age.

It’s time for companies to truly listen to their customers, understanding their needs and preferences at every opportunity. Sophisticated analytics can help capture that intelligence, and over time, this evolving journey with customers can deliver a better customer experience – and genuine and lasting customer intimacy that drives bigger and better business results.

 

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