Sales leaders in business-to-business (B2B) organisations are under constant pressure to spot new business opportunities.

It is, however, a too often neglected fact, that some of their current customers will churn and recurring revenues will not return.

Besides attracting new customers, succesful B2B firms also direct their efforts into retaining existing ones.

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AI and machine learning are penetrating ever further into the corporate world in Germany. This year we have clearly felt this – in a positive way! Exciting new projects, new customers and interested new partners have accompanied us throughout this year.

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Predictive analytics covers a variety of statistical algorithms from machine learning, predictive modelling and data mining. It analyses past facts and historical data to make predictions about events and to identify the likelihood of future outcomes. Predictive analytics has been around for years, but it was impractical in large-scale sales settings due to an inadequate data analysis infrastructure.

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Business-to-Business (B2B) companies depend on building and developing long-term relationships with their customers to be financially successful.

However, over time, some customers will stop buying or will defect to the competition. Sales managers define this situation as “churn” or “customer attrition”. Managing and reducing customer churn is one of the most important, yet sometimes overlooked job of the sales leader.
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Reduction of customer attrition by implementing a churn prediction software in your sales reporting

Understanding and avoiding customer churn ( or attrition) in Business-to-Business(B2B) organisations can make the difference between a successful financial year or a miserable one.

Every experienced sales leader knows that some customers will eventually churn. Studies in the field of customer retention talk of a 5 to 25 % customer churn per year, depending on the industry. Customer attrition is revenue lost.

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