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Samsung is selling millions of electronic products every year. As a result the customer service agents from Teleperformance answer thousands of incoming questions per week. The complexity of organizing the customer service center has intensified over the past couple of years. Consumers reach out to organizations via an increasing variety of channels, such as telephone, e-mail, WhatsApp, and Facebook Messenger. On top of that, Samsung’s customers have high expectations of the service levels offered and demand to get assistance instantly, 24/7. Therefore, Samsung is continuously innovating their customer service center to remain a frontrunner in the market and meet the expectations of their consumers in a time and cost-efficient way.
The Collective Memory
Service agents build up a lot of knowledge about various topics when handling service tickets for Samsung. However, service agents do not stay forever, this means knowledge is lost when a service agent leaves the team. New service agents receive the necessary trainings but this is a time-consuming processes. To encounter these problems we have to increase the time efficiency of handling customer interactions, by creating a ‘collective memory’ in which all knowledge of agents is captured to support customer service agents with handling service tickets in an intelligent way.
The Collective Memory contains all historical conversations and captures all interactions that service agents had in the past. Based on this knowledge the algorithm predicts the best suitable answers for new incoming questions and provide these to the service agent. Knwoledge will never be lost again and service agents can profit form each other’s knowledge and get started
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Best matching answers
The intelligent plug-in analyses all incoming questions from different channels such as WhatsApp and Social Media in real-time and assists the human agent with suggesting answers. Based on all historical conversations the solution pushes the answer that is most likely going to solve the question the customer has in two forms:
■ The best-fitting standardized answer for frequently asked questions
■ The best answer that is given by a service agent
Incoming questions can now be easily and timely being answered by the service agents with the most relevant answers. The consumer will never get a faster and more accurate answer anywhere.
Human in the loop
Service agents continuously feed the algorithm with relevant feedback and input. By accepting, adjusting or rejecting the suggested answers the collective memory will become smarter over time.
Get a grasp of context
In contrast to traditional chatbots the collective memory doesn’t have to be programmed, it can learn on its own from the past and is able to understand the context of the conversation. This makes the tool manageable as the same question can be asked in hundreds of different ways.
Our customer success experts would like to help you on your way to always being relevant to your consumers! Discover in the Inspire Product Guide how our AI decisioning engine can significantly improve both conversion and customer loyalty, or request a demo.