Predictive Analytics in B2B: 3 Ideen für Vertriebsleiter

Are you a sales manager with Big Data? Here three Predictive Analytics examples for B2B

 

With predictive analytics, big data becomes a big opportunity for B2B sales managers. This big opportunity requires, however, a profound understanding of the sales situation, coupled with an understanding of big data mining models available.

 

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Why CRM Projects Fail

Why CRM Projects Fail

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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B2B-Sales-Controlling

Predictive Sales Analytics – How to use it in B2B Sales Controlling

 
How the sales analytics tools you use impact your sales controlling.

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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customer-attrition

Define and reduce customer attrition in the subscription industry

 
Customer churn definition in the subscription industry

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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All About ERP Data Mining for Sales

All About ERP Data Mining for Sales

 

ERP Data Mining: what we learnt from analysing 100 million of B2B sales transactions.

Data mining is the application of a varied assortment of statistical techniques to ERP datasets. Companies nowadays use data mining to predict outcomes, identify sales trends, prevent customer churn, and dynamically adjust pricing strategies.

Mining enterprise resource planning (ERP) sales data is critical in Business-To-Business, where small improvements in sales efficiency can have a significant impact on results. Mining ERP sales data helps customers to unlock a significant amount of value, discover quick-wins, and to prioritise their sales activities. Automatizing this process is possible today with the help of artificial intelligence (AI).

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