Customer support on AI steroids

Case study

Customer support on AI steroids

Enhancing Customer Support Operations with AI-Driven Suggestions and Real-Time Assistance to Boost Efficiency and Upsell Opportunities

Challenge

The company wanted to identify how well each individual employee supporting the customer is doing the job. They wanted to understand if they are polite if they offer a satisfying solution but also if they identify the potential for upsell. Technical challenges with implementing the solution were the privacy requirements and making sure that the sensitive data is not being sent outside of client’s premises

Solutions

We created an infrastructure and a voice and chatbot working as a customer support assistant. The chatbot is suggesting the most probable solution for a customer's problem as well as identifying upsell opportunities. The solution consists of the chatbot itself as well as all necessary integrations including speech to text models for understanding what is happening in the conversation.

Technology & Tools

Phyton

LangChain

Nvidia Nemo

LLama

Mistral

Client

The large enterprise leader in the telecommunications industry across the Nordic-Baltic region. Aiming at improving efficiency of their customer support by introducing essential AI infrastructure and services.

Opportunity

Providing customer support representatives with relevant information, and AI generated proposal increases the effectiveness of the Team as well as customer satisfaction. It is also a great first step for enabling more features, including more advanced suggestions for the support representatives as well as fully automating some of the requests.

Delivery

Together with the client’s team we started by identifying already known common challenges tackled by customer service. We identified types of customer requests but also what part of the process could be improved by AI in order to increase efficiency.

We did identify the low hanging fruits by talking to customer service representatives and analysing the historical data including emails and voice calls.

Effect

The solution was introduced from zero to a first working end to end version. It increased customer satisfaction by 20% and significantly increases customer support awareness of the upsell opportunity. At the same time the data collected from the first version will be analysed as an input for the future improvements.