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Predictive Analytics

Predictive analytics is the branch of data mining concerned with the prediction of future probabilities and trends.

What is predictive analytics?

Predictive analytics is the branch of data mining concerned with the prediction of future probabilities and trends. The central element of predictive analytics is the predictor, a variable that can be measured for an individual or other entity to predict future behavior.

With the usage of predictive analytics, organizations with declining survey response rates, can predict and address individual customers in need of remediation. This can, in turn, significantly boost CX program ROI. According to the White House Office of Consumer Affairs, for every customer who bothers to complain, 25 other customers remain silent. Predictive analytics in CX help companies give a voice to the silent majority and helps them recover silent detractors.

Predictive analytics allow you to hear, understand, and proactively engage with customers who may never provide feedback. Even companies that have efficient, well-funded feedback programs in place, usually only hear from 5 to 10 percent of their total customer base. Without data on all your customers at the individual level, you can’t confidently prioritize your limited resources to drive customer feedback.

The idea of combining direct survey data with other forms of customer information to actually predict the concerns and behaviors of all your customers holds tremendous potential—not only for identifying silent customers who may be dissatisfied or upset, but more importantly, for executing dynamic offers, personalized incentives, and customer-focused policies that build loyalty and drive new business.

 

How does predictive analytics help your business grow?

Predictive analytics increases the value of your customer data and your ability to act on customer sentiment. Since the world is overwhelmed with data, marketing messages, and requests for input, many customers tune out the well-intended transactional or relationship surveys from the vendors with which they do business.

Take Amazon for instance. They are considered to be one of the most successful companies in the entire world, and much of their success has been determined by their ability to use predictive analytics. Amazon uses predictive analytics to track what you search for on Amazon and then they dedicate a huge percentage of their screen space to “recommend” products for the user to buy. Each of the products recommended are based on different algorithms using predictive analytic programs. This power to predict has allowed Amazon users to experience shopping in a new, elevated way.

 

Benefits of Predictive Analytics

  • The ability to PREDICT customer sentiment without having to ask
  • The chance to ACT while the experience is fresh and the possibility of reversing negative perception is high
  • The opportunity to recover a customer you didn’t know you were going to lose—and significantly boost the ROI of your CX program in the process
  • The ability to hear from the silent majority and extend knowledge from a small sample to your entire customer base
  • Opportunity to proactively recover customers who would not have otherwise provided feedback
  • Opportunity to gauge respondent population skew vs. actual customer population
  • Opportunity to reduce overall survey solicitation volume and fatigue
  • Opportunity to increase CX program ROI
  • Once increased the better able they are to make strategic decisions