ESTA Technologies - Embark on a Predictive Analytics Mission

BELFAST, Northern Ireland - March 1, 2014 - PRLog -- Good data visibility will allow organizations to make timely predictions that will not only save them money, but also help improve the customer experience. Experts believe that emphasis over the past years surrounded collecting information and using it to gain visibility into the customer journey across different channels. The next step will include a predictive element in that process. Sprint is one company leveraging data to make early predictions. For example, the company realized that customers activating a new smartphone were often contacting Sprint a few days later to inquire about reactivating their old devices for another family member or about recycling options. Sprint added a step to the activation process, asking customers what they wanted to do with their old devices, thus eliminating thousands of calls every year, increasing customer satisfaction, and also positively impacting revenue.

Apart from identifying problems before they happen, predictive analytics can also help organizations determine the next best offer for individual customers. As Davenport notes, recommendations require a clear sense of customer behavior across multiple channels. Further, knowing customers isn’t enough. "You also need to know a lot about your products," Davenport stresses. Zappos, for example, has three departments focused on determining the attributes of different products so that the company can make relevant recommendations to customers based on different criteria, for example style, brand, and size.

Finally, business leaders need to be wary about embarking on analytics projects simply for the sake of doing something with their data. Instead, they need to make sure such initiatives are geared towards solving an existing problem. Therefore, business leaders need to take an inward look and identify the business problems that need solutions. Sridharan agrees, emphasizing that the first step before embarking on an analytics project is to understand the organization’s analytics maturity. She also stresses that organizations need to set aside an experimentation budget for testing before embarking on a new analytics method.