Selling is a process par excellence, especially in a B2B context, where human interactions play a crucial role. AI, Deep Learning and Sales Forecasting can play an important supporting role in uncovering opportunities and thus supporting these interpersonal relationships. Sales teams often have large amounts of data, think of histories with times and amounts of purchase. However, given the amount of data, it is difficult for humans to detect all the relevant things in it. This is where AI, as sales forecasting software, can add value.
This was also the thinking of one of our customers who used the Trendskout AI software platform to mine sales opportunities from data. It is a production company located in East Flanders, employs about 40 people and has an annual turnover of 20 million euros.
Situation: customers and product relationship and sales forecasting
The company in question has a very broad customer base of active customers. The turnover it generates is comparable to the classic 80-20 distribution: 80% of the turnover is generated at 20% of the customer portfolio. In addition to a number of large customers, there are also a large number of smaller customers who only place sporadic orders. On the other hand, this company has a solid but rather limited product portfolio. Each type of product is available in a wide variety of shapes, formats, colours and quantities.
A team of account managers is employed to serve and cultivate the existing customer base. Their task is to work closely maintain contacts with all customers and to upselling to do so whenever possible. Each representative manages a portfolio of hundreds of active clients, so it is impossible to do all of this without help. sales opportunities mapping themselves. As a result, they often fall back on customers with whom they are familiar and lapse into certain routines. Of course, this is a human reflex, but it has led to a lot of problems. missed sales potential.
Discovering sales opportunities with the help of AI
To all this uncovering unused potential an AI software company, with experience in sales forecastingIt was a company that could react quickly and could start working with the available data without months of preliminary study or integration process. The choice fell on Trendskout AI and Auto ML software platform.
The company had already been working for a long time with a Microsoft ERP package in which all transactions with customers over the past few years had been recorded. Since the Trendskout AI software has ready-made plug ins for common software systems and databases, the connection could be be realised quickly without custom programming. This was an important element in the choice of the Trendskout AI software.
The link with the data therefore went smoothly and the construction of the AI model could be started quickly. For this application, the Trendskout analysis "Sales Opportunity Detection"chosen. With this analysis, the Trendskout AI searches for patterns in historical data in order to make future projections. For this purpose, a sales forecasting model is built that relies on all available order data from the past. From this model, the Trendskout AI software then generates monthly forecast indicating which customers to focus on in order to achieve a guarantee optimal turnover.
Practical set-up of the AI application within the Trendskout flow
This analysis was set up according to the simple CONNECT – ANALYSIS – AUTOMATE flow that is characteristic of the Trendskout software. As training dates became a historical dataset chosen from Microsoft Dynamics which contained the transaction & order data over a period of 3 previous years. For the real time analyses and forecasts, as already mentioned, a connection was made with Microsoft Dynamics ERP.
As AI functionality, the "Sales Opportunity Detection"analysis chosen which already provided as standard is in Trendskout. Here, the Trendskout AI software generates a customised AI model based on the supplied data. During the configuration, you can choose over which period the machine should look at future opportunities. predict.
As an automatic step, Trenskout generates the data in tabular form, accessible to the sales team via a easy to consult in a browser interface. It displays a list of customers per vendor who have ordered its by priority where action needs to be taken in the following month supplemented by the expected turnover per customer.
This entire flow was set up within the visualised interface Trendskout, without the need for any coding and within a period of 5 weeks from start-up to delivery.
Determination of next best action
Soon the suggestions generated by the artificial intelligence proved to be a clear added value offer. Each salesperson now clearly knew which customers to focus on each month and this soon bore fruit. After the application had been in production for 3 months, a relative turnover increase of 6% on a monthly basis noted.
After demonstrating the added value of the solution, they wanted to Deepening. The AI model generated a monthly overview of the biggest opportunities and with which customers they could be found. However, each sales person still had to find the proper follow-up action mail, phone call, personal visit, offering a promotion...
To support this as well, the Trendskout AI was used to create a Next Best Action model that suggests concrete actions for a predefined goal: in this case, generating more margin. Specifically, it generates a list of actions for each customer that are most likely to generate a sale. This reduces the administrative role of sales people in the presales phase to an absolute minimum and allows them to focus on the sales process. devote maximum effort to developing deeper relationships with their customers.
Clear increase in turnover as a result
The addition of this analysis resulted in an additional revenue increase of 2.5% 6 months after the initial AI flow was rolled out, which is the total relative turnover increase on 8.5 % brought.
If you also want to get more out of your data and your sales process, you can contact us here.