The fifth article in the series on Predictive Sales by PwC and Dastani Consulting looks at share-of-wallet analysis to discover the revenue potential of clients. Sales resources can thus be invested in customers who still have an open potential.
Customer Value Prediction shows what can be derived from past orders. Looking to the future, share-of-wallet analysis shows the customer’s full potential. It supplements the customer view with external information. Especially for customers with low sales, it is worth taking a closer look at their sales potential. The share of wallet defines the share of your own sales with a customer in a particular merchandise category as a proportion of the customer’s total budget for this segment, thus showing the maximum amount of sales that could be achieved. The method often reveals hidden potential that exceeds the current sales volume many times over. Well-known B2B companies achieved rapid sales growth by analyzing existing business relationships for further potential and focusing on the relevant addresses.
AI evaluates all available external information about the respective client company, for example industry, number of employees, extracts from the commercial register, annual financial statements, etc. The system uses this information to calculate a sales estimate. The expected turnover is only a part of the total potential: A discrepancy between purchase volume and general market potential indicates that the business can be expanded considerably, since the buyer purchases a significant proportion of the products in the range via a competitor.
The share-of-wallet provides information about the potential that lies dormant in the inventory and how many of the customers are worth addressing more actively. The example of one of our clients illustrates the procedure: An online retailer achieves margins of 5 to 80 percent depending on the product range. However, only 2.5 percent of the 400,000 existing customers in the business sector buy the highest-margin products. We developed a model that forecasts expected values for the various product areas for each individual customer. For the interesting segment of high-margin products, we looked at the customers already buying in this segment. In a next step, we used external data, the websites of these companies and other information to forecast for each customer the probability that they would buy a high-margin product and the revenue that could be generated with it. In this way, we were able to identify a large number of very interesting addressees in the customer base. The share-of-wallet analysis enabled us to invest sales resources in a targeted manner in those customers who most likely still have open potential.
In another case, our value predictions decide which customers the mobile sales force is allowed to visit at all. It is not uncommon for many companies with limited sales and potential to be on the appointment calendar. Such customers can be assigned to telesales after the analysis. In return, the salesperson receives addresses that may currently have little or no turnover, but have great sales potential. This targeted allocation increases sales at constant costs.
This article is part of a series on LinkedIn about #PredictiveSales:
1. the potential lies in forecasting
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