Sales Controlling

erp-kuenstliche-intelligenz

Why is your ERP useless without AI?

Why is a legacy ERP becoming irrelevant in an AI era, and what can you do about it?

Let’s face it. In a few years, we will lose the battle against the terminator. Even without the help of a computer scientist, a sales manager recognizes that the near future will bring considerable changes in his profession – triggered by artificial intelligence (AI).

 

Soon machines will take over the job of a sales manager. There will be artificial thinking selling-machine more efficient than salespeople will ever be, thanks to artificial intelligence. The more data they gather, the better they get. Machines will soon take over. Brace yourself.

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Vertriebscontrolling-Kunstliche-Intelligenz

Artificial Intelligence Example to Rock Sales Controlling in B2B

Machine learning (ML) and artificial intelligence (AI) hold the key to a tremendous improvement in sales controlling efficiency. A software is intelligent if it can solve problems independently and efficiently.

 

The degree of intelligence depends on the level of autonomy, the extent of complexity of the problem, and the efficiency of the problem-solving process. In artificial intelligence terms, researchers speak of “strong” versus “weak” AI – “general” and “narrow” AI, respectively.
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ai-sales

Sales Management in times of Artificial Intelligence – Five tips to redefine B2B Sales

Sales processes, salespeople and sales management should adapt to the brave new world of artificial intelligence. Artificial intelligence is taking over the administrative tasks that consume much of managers’ time. It is doing it faster, better, and at a lower cost. It has pros and contras. AI will redefine management.

In B2B Sales, artificial intelligence (AI) refers to Enterprise Resource Planning (ERP) and Customer Relationships Management (CRM) Systems equipped with machine learning and automatized data mining features.

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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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big-data-small-data

Predictive analytics – how much data do you really need?

 
How Much Data Do You Need For Predictive Analytics?

Predictive analytics is one of the technologies with the highest financial impact in B2B sales. Several popular applications of predictive analytics are becoming “must-have” nowadays.

Sales leaders rely on lead scoring, customer attrition modelling, cross-selling analytics and pricing analytics to prioritise their sales activities and increase their customer lifetime value.

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