The context
In retail, the mission of customer service teams varies greatly in each sector. For fashion and beauty retailers, the focus is on order tracking and returns management. But the process is more complex when the products are repairable, including electronics, household appliances, D.I.Y. or sports equipment.
Historically, after-sales services had a poor reputation in terms of customer satisfaction (chargeable call numbers, lack of contact e-mail, difficulty in reaching an advisor). These used Natural Language Understanding (NLU) technologies that were not capable of automating the end-to-end management of requests. According to Hakim Naili, Director of Services at Boulanger: “When my experience of after-sales service is an obstacle course, if I have to produce Cerfa No. 872 and call several numbers, it’s a real deterrent. And yet, as a customer, it should be painless to have a product repaired under warranty. AI tools can improve the after-sales experience. For sales agents, it is better to help by profiling a customer and focus on the relevance of their advice. For customers, by increasing NPS and eliminating stress. It is a win-win situation for everyone.”
For some retailers, the after-sales service tasks include selling additional services. At Back Market, agents can promote a sale of smartphone warranties. For others at Boulanger, which focuses heavily on repair services (Club Infinity insurance programme), customer service teams promote the benefits of repairs in a number of ways. An example is promoting on an invoice issued following an out-of-warranty repair that it would have been free with Club Infinity. “To date, our after-sales service does not sell our Infinity insurance offer,” said Hakim Naili. “This team does not offer this service as it is highly regulated. We would like them to be able to do so, but we will have to find the right way to do it, while remaining within the regulatory framework. Our technical teams are the best ambassadors for programmes that focus on extending the life of products and preventive maintenance. They know how to highlight the significance of this service and to make it visible.”
The major case studies for AI in customer relations are:
– Order tracking (WISMO: Where is my order)
– Promoting services from agents: AI acts as a co-pilot for customer service employees.
–Handling and monitoring after-sales customer files (faulty products & repair requests).
– Facilitating access to product information. This feature, which is used by many retailers, enables customers who have already identified a product to buy to find more details about its capabilities.
