Managing Sales Behaviour to Improve Sales Performance using Predictive Sales Analytics

Improving sales performance often involves coaching and modifying the way your key account managers work – what practitioners in the field of sales & marketing define as behaviour. Changing behaviour usually leads to better performance in B2B sales.

There are several known theories and models about behaviour that have not been explicitly developed for sales professionals, but about general social practice.

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Why CRM Projects in B2B Fail and How to Make Them More Successful

Many studies over the years have shown a very high failure rate for Customer Relationships Management (CRM) systems. Already in 2001 Gartner estimated this rate to be at about 50%.

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Controlling sales in B2B is increasingly becoming a high-tech game. Since selling cycles in business-to-business are getting longer and sales is getting more expensive, controlling need to look further into the future.

Machine learning, a well-known example of weak artificial intelligence, represents a fantastic opportunity for improvement in B2B sales controlling and business intelligence. It enriches the world of sales analytics with a substantial competitive advantage.

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Getting an edge in today’s competitive market place is vital. For B2B companies, possessing the tools to explore customer behaviour and prioritise leads not only aids productivity but helps boost that all-important bottom line.

Predictive sales analytics has come a long way in the last decade. It is now far more accessible to businesses in traditional industries. For many, it’s a powerful tool in helping to support sales and operations planning.

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B2B companies can, on average, approximately expect a yearly 11 % customer churn rate, found a recent study that.

This cancellation rate fluctuates between countries and industries. Customer attrition can represent a 24 % average in office supplies, 16 % in the insurance industry and 13 % in banking.

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