Author: Lucas Pedretti
Predictive analytics for customer retention plays a critical role to accelerate sales in Business-to-Business.
Building customer loyalty successfully and efficiently is what makes business-to-business companies thriving on the long-term. These market leaders actively engage in customer retention prediction. In the end, reliability lives from common purpose, and not from passive “wait and see”.
Furthermore, for companies that are focused on achieving stable and foreseeable sales growth, B2B loyalty programs are unavoidable. Nobody can reliably grow a customer base in the absence of customer retention predictions.
B2B E-commerce in Germany keeps growing – good or bad news?
The Business-to-Business wholesale trade in Germany and the world has changed considerably over the last years and has proven to be exceptionally flexible. It is under a growing threat, nevertheless.
Several trends underpin its transformation. New forms of industrial distribution are emerging, and big manufacturers offering e-commerce are choking the middle-guy. Wholesalers are creating tangible value for their customers while providing new services, not only logistic ones.
Revenue stagnation is a nightmare most managers are scared to dream. If a market is growing in line with the economy and income stagnates, then market share is approximately contracting, and a company is becoming irrelevant. No manager wants that.
Sales Acceleration with Predictive Analytics Software: How to avoid The Causality Trap of Black-Box Machine Learning.
Successful B2B managers use AI-based predictive analytics software to accelerate sales. However, they often want to find for themselves what the characteristics of their main profitable customers and leads are.
You know this situation well. You want to predict success. You would like to create a set of rules that your sales team can follow to avoid customers from churning or to find hidden sales opportunities. Why cannot your AI sales software do that?