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    Samsung intros Collective Memory, an AI-driven customer support service

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    Last updated: November 5th, 2019 at 14:46 UTC+01:00

    Samsung is improving customer service in the Netherlands with the help of artificial intelligence and what the company calls Collective Memory. The latter is an AI-driven customer support solution that leverages machine learning to deliver fast and better customer help.

    Collective Memory was developed by Samsung together with Teleperformance and Building Blocks. The system has been put into place ‘to ensure that consumers do not have to wait unnecessarily‘ according to the Director of Customer Service at Samsung Electronics Benelux, Daan van der Mijden. It can adapt through machine learning and improve its answers based on previous responses and interactions with other employees and customers.

    Collective Memory is an AI-human joint effort

    As with virtually any other AI and machine learning algorithms, Collective Memory makes predictions based on previous interactions and its capabilities are bound to improve in time. But the system won't work independently from other Samsung employees. Collective Memory doesn't replace the human customer service representative, it only aims to streamline the service process and help the employee offer the best solution to customers.

    Collective Memory aims to predict issues and deliver the right answers to customer service employees, who can then decide to reject or modify the answer or pass it along to the customer. Should the employee reject or modify the first solution offered by Collective Memory, the system will analyze that choice and continue to learn and improve.

    In other words, Collective Memory is not just a robot waiting for you on the line when you make a phone call to customer support. It's a man-machine effort that tries to combine the best of both worlds to deliver fast and accurate customer support.

    Samsung already tested Collective Memory and the results are positive. The company claims to have gained 10% efficiency, and this is only the beginning. The machine learning algorithms fed by employees will continue to improve Collective Memory in time, leading to even higher efficiency gains. The system is launching in the Netherlands, and if proven successful in the long run, it will likely be implemented in other markets as well.

    BusinessGeneral AINetherlands

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