In the classic sales structure, many sales employees focus on the active and good customer. However, caution is required: Some customers are visited far too frequently, while others do not fully exploit their potential.
Determining the expected turnover
AI methods have gained considerable added value, at least since the severe crisis situation. The first step is customer value prediction, which makes it possible to forecast the expected turnover of each individual customer for a specific period of time (e.g. for six months). The model derives the value of a customer from past transactions. In this way, the system predicts what turnover a customer should achieve in the next period.
Use of Visit Value Prediction
After determining the general customer value (sales expectation) for each individual customer, this can then be linked to the visit value (sales expectation per visit). The visit value prediction predicts the expected turnover for the next visit, e.g. in the next week. In this way, the visit value prediction can also indicate which visit will turn out to be uneconomical and would be associated with a negative contribution margin. The model is based on past sales and visits.
However, it is not uncommon for visit value predictions to conclude that companies invest too many sales force visits in customers who have low sales expectations. Sales can counteract this by reducing the amount of non-business field sales force visits and replacing them with telesales, for example.
Putting the predictions into practice
Both the customer value prediction and the visit value prediction are able to support the sales department significantly and to use the resources in a more potential-oriented way. The sales department realizes how many and which visits can be better allocated and how much potential its active and inactive customer base offers. In addition, the sales department can identify how well the potential is already exhausted for which customer and focus on unused potential. Released sales resources that are not profitable according to visit value- or customer value prediction can be used differently.
The success is evident
The customer-specific forecast values determined can then also be aggregated to the sales employee level. The performance of all sales visits can thus be objectively assessed. Using the top-down list of the visit value prediction, the sales staff can see which individual customer is to be visited.
Our strategy is to use our forecasts to identify uneconomical visits and reduce the frequency of visits. Furthermore, we invest resources that have been freed up in conquering high-potential customers, in acquiring new customers with high potential and in activating customers with the greatest potential. We also forecast the potential. We estimate that these measures will enable us to increase sales by up to 20% – without having to build up additional sales resources.