Why a CRM System with Predictive Sales Analytics and AI?

Using CRM systems have long been a common practice in large companies today, even if not always successfully implemented. Small and medium-sized enterprises (SMEs) often still have some catching up to do.

Meanwhile, the next expansion stage has long been underway. Predictive sales analytics/artificial intelligence (AI) is being added to the CRM systems.

These systems access the data from enterprise resource planning (ERP) systems and/or the data from the CRM systems in order to make sales more effective and more powerful, while also reducing sales costs in relation to the sales achieved.

What is special about these systems?

Thanks to predictive analytics, these systems can predict the behavior of your customers and prospects quite accurately based on the data in your CRM system/ERP system. This is done by analyzing and comparing customer behavior based on the mass data.The strength of AI systems, after all, lies in recognizing patterns in data volumes that may overwhelming to humans. These systems are particularly successful in the following six areas:

1. Customer Churn

The fact that customers migrate to competitors is completely normal and is usually compensated by the acquisition of new customers. One can accept this or do something against it. As a rule, it is significantly (approx. 10x) cheaper to keep a customer than to acquire a new one. Simply put, AI recognizes the behavior of customers who have churned in the past and alerts the sales force if the same signs start to appear in customers who are still buying.

Your sales force can thus seek a conversation with the customer, determine the reasons, and take countermeasures. Fewer churning customers means lower sales costs with the potential of revenue growth. New customers now don’t have to make up for lost sales, but may now see an increase in sales.

2. Closure Readiness

Similar to the above, AI can detect when a customer is ready to close a deal with you. In the best case, AI can even make suggestions to you about what pricing you can use to close the deal. Similarly, of course, AI systems can also suggest what pricing policy you can use to retain or win a customer.

3. Up- and Cross-Selling

AI can also make suggestions to you in this area. You may already know this from Amazon. However, this is much more difficult in the area of private end consumers (B2C) at Amazon. This is because private end consumers also buy products for others, for example as a gift. In the business-to-business (B2B) area, this is much easier. Companies usually do not buy for others, but for their own needs. Also, as a selling company, you usually have a much smaller product range than Amazon. The AI suggestions based on data mining will therefore be much more accurate and show the potential for cross-selling and up-selling.

4. New Customer Acquisition

Here, too, an AI system can provide significant support. It is worth highlighting here the evaluation of potential new customers/addresses. After just a few contacts with a potential customer, AI can give you estimates of how high the probability of a deal with a potential customer is. However, it must be emphasized here that AI gives estimates and probabilities based on existing, i.e. old data, from your CRM/ERP system.

In the event of drastically changed conditions, e.g. the failure of a competitor, a new salesperson, product innovation, etc., these estimates can quickly become obsolete. Despite AI, people still have to think and decide! If, for example, a competitor leaves the market, your chances increase abruptly, even with customers who were previously hopeless, contrary to the predictions of AI.

5. Pricing/Pricing Policy

If you have many products and/or many customers, a price corridor analysis on product and customer level can show you margins, optimization opportunities and contradictions that can lead to additional sales and/or earnings.
 
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6. Sales Planning

Intelligent sales planning is the key to efficient, effective and cost-effective sales. Using AI, you can manage your sales more effectively and achieve faster closings or sales. With an analysis of customer potential and sales probability, you can focus on the customers with the highest potential and sales probability.

If your product range allows it, you can also divide the customers into groups (ABC analysis) and determine which customers need to be supported by the field sales force and for which ones support by the internal sales force is sufficient. This can go so far that AI makes suggestions as to when the next contact makes the most sense. AI systems learn about the best corresponding practices all by themselves.

More generally, attention should be paid to causality. As mentioned, an AI is strong in recognizing patterns and correlations. However, recognized correlations are not always causally related, but possibly only randomly. However, with a large enough database, you eliminate the random correlations.

Why a CRM system with predictive sales analytics/AI?

A CRM system that integrates an AI tool has several advantages over traditional CRM systems. It allows your sales team to efficiently prioritize sales activities and plan for the future. AI-based sales forecasting keeps you one step ahead of your competition.

I WANT PREDICTIVE ANALYTICS FOR B2B SALES.