The third article in the series of articles by PwC and Dastani Consulting shows how AI can specifically forecasting the purchase probabilities of potential customers in order to significantly increase sales and margins in B2B sales.

In order to be successful on the market in the long term, companies must continuously acquire new customers. KI supports companies in evaluating the attractiveness of customers a priori and identifying suitable addresses. This is because it is capable of interpreting a large amount of content, for example around 5,000 words per website. The type of text and the expressions used are irrelevant. We deliberately dispense with the sales department’s assessment of which criteria are particularly important in the analysis. Instead, AI learns by itself which characteristics predestine a company as a customer.

To do this, algorithms read out the websites of the best existing customers and track down correlations and patterns. Then similar websites are identified and compared. The software evaluates the degree to which a website matches the target company with a measured value. Up to 20,000 different characteristics are included in the forecast. In the end, it is not only clear with what probability a company can be made a customer, but also for which product range it is suitable. In this way, individual product divisions can be developed in a targeted manner. The sales department also learns what sales revenues it can generate with the potential customer and is able to allocate sales staff in the field and also in telesales in a resource-optimized manner.

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The quality of the forecasts even makes it possible to provide sales staff with the contact information without further pre-qualification by telephone. In this way, the sales force can see at a glance who they should visit on their next tour. No matter how the sales territory is defined geographically: the potential can be systematically exploited. Various B2B sectors are already successfully optimizing their new customer acquisition – for example, in the trade with industrial trucks, tools, steel, vehicles, chemicals and workwear.

Traditional evaluation criteria such as industry affiliation and number of employees, but also gut feeling, take a back seat when acquiring a company. Direct marketing campaigns and an intermediate qualification via call centres can also be largely dispensed with, as the potential analysis can be used to assess very precisely whether a visit to a potential customer is worthwhile. This not only increases the targeting accuracy of sales activities, but also makes them significantly faster and more cost-effective.

This article is part of a series on LinkedIn about #PredictiveSales:

1. the potential lies in prediction

2. technical requirements

3. forecast the purchase probability of potential customers

4. identify cross- and up-selling potentials

5. discover the turnover potential of the customers

6. not every goodbye hurts

7. concrete use in sales

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