About the client

RS Components, the number one high-service distributor of electronics and maintenance products across Europe and Asia Pacific.


Create a foundation on which disruptive new customer interfaces could be build, therefore contributing to RS Components’ long-term strategic goal to be the market leader in customer experience.

Key Achievements

  • Created innovation infrastruture on which future data driven projects could build.
  • Enabled rapid sales growth without increasing support costs
  • Automated low value customer flows so that representatives can work on high value tasks.
  • Developed AI powered search for product equivalence and compatibility queries.

How we did it

H&C partnered our machine learning experts with the in-house innovation department, customer service specialist team and sales team to form a comprehensive taskforce.


We held a workshop for the entire taskforce and discussed different approaches. After reaching a collaborative consensus, we established initial user stories to guide the development process.


We build the prototype chatbot framework, which was tested by users. From this we went through iterative stages to hone and improve, all the while building on user feedback. A staged rollout to the market gathered early market feedback.


The main technical challenge of this project was the creation of an intelligent chat system. Unlike conventional software, this challenge needed a two-stage development approach of training followed by runtime-operation.

To solve the intelligent chat challenge, we used Diagflow and machine learning to create a chatbot harness, which used annotated chat templates and transcripts from real-life user interactions with customer service. This allowed us to develop a solution capable of maintaining context throughout multiple interactions. It can also clarify user information and answer customer requests by leveraging upstream systems.

Increased capability and accuracy of the intelligent chat system will be achieved using a self-learning system. This uses each and every interaction to expand its training set, making the system smarter and more resilient as more customers use it.


The chatbot aims to increase customer satisfaction by providing faster responses, constant 24/7 availability and lower overall support costs when compared to human agents.

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