THE CHALLENGE

Several call centers with hundreds of employees have to be organized to call customers as optimally as possible. The focus is on generating as much additional revenue as possible without making a negative impression on customers.The goal is to call the optimal customer with the right product at the right time. Every sales employee should know what the next best step is for him. That’s why our approach is called next-best-action marketing. The system is intended to learn from feedback from customers and sales staff and thus continuously optimize itself.

SOLUTIONS

The goal is to increase sales compared to working without the data-driven AI solution and improve customer feedback. Our solution:

• Definition of KPI’s, for example: Customer satisfaction on call, sales success, customer reachability, turnover.
• Develop an AI model that can process the historical data and generate recommendations for action
• Ensure a connection to the newly generated data for continuous “live” learning

OUR 4-STEP PROJECT PROCEDURE

1. Initial workshop
2. PoC (Proof of Concept – development of an initial prototype solution to validate the solution concept)
3. Complete implementation of the use cases after successful PoC
4. The solution is delivered as a microservice and integrates

In this particular use case, we formed a Scrum team with customer employees.

Results

The following results were obtained:

• Revenue increases of 2-15% were achieved using the next-best-action approach, depending on the call center, month and product.
• Up to 20% higher probability that calls were answered and the customer was open for a conversation could be achieved

Management summary

Thanks to the trusting and committed cooperationcooperation between the two companies, we were able to achieve noticeable optimizations with regard to the targets set.The investment expenditure amounted to around €70,000. In the course of the project, data quality was improved and the customer’s understanding of the possible uses of the existing dataof the existing data was significantly increased. We have thus created a solution that can be seen as the basis for future data-driven projects.This will benefit all departments in the Group and enable further digital innovations in the future.