In the first part of the article ‘Artificial Intelligence in Sales’ you already got to know the application of artificial intelligence in Dynamic Pricing and Predictive Lead Scoring. Now you can read about the additional areas of application artificial intelligence offers us.
Forecasting is used to predict potential sales results using data-driven probability models. Predictive analytics and AI increase forecasting and revenue forecasting. With the help of Customer Value Prediction (CVP) developed by Dastani Consulting, we are able to predict sales development for specific customers and products. These figures can be used to make better decisions. Furthermore, the model serves to give early warning signals in order to avoid major deviations from the targets.
4. Cross- and upselling
Based on CRM and ERP data, AI is able to perform analysis prior to cross-selling to predict the likelihood of successful cross-selling. The sales managers receive information on when it is worthwhile to offer a customer an additional product or an up-selling offer. In addition, the systems are able to evaluate the additional sales potential that exists in the customer and present it for the various sales units down to the individual customer. The subjective assessment of sales is thus compared with an objective evaluation instrument that learns from millions of transactions.
5. Customer satisfaction
Intelligent AI systems are able to improve satisfaction on the basis of customer experience and to learn more with each new data record. AI can be used in different ways in customer service – with chatbots, with a personalized customer approach, or with automated customer interaction to help the customer find the right product.
Artificial intelligence in sales will bring significant advantages in the future. With intelligent AI algorithms, the sales department is able to expand its knowledge about customers and increase the likelihood of closing deals, as it can concentrate on promising customers and address them individually.