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Chatbots dumb automated machines for most consumers: Survey

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New Delhi, Oct 11 (IANS) While chatbots can be fast and convenient to answer simple queries, most consumers still think they are dumb automated machines and prefer a human on the other end, a new survey from global software company Pegasystems revealed on Thursday.

Seventy two per cent of consumers generally find chatbots to be helpful to some extent but 58 per cent rank their chatbot experiences as merely “adequate” — doing some tasks well and others poorly.

Another 18 per cent grumble how chatbots are ineffective or even annoying and only 16 per cent gave their chatbot experience a high-quality rating, the results from 3,500 global consumers showed.

“As chatbots become more pervasive, the quality of the engagement has lagged significantly behind customer expectations,” said Ying Chen, Head of Product Marketing, Platform Technologies, Pegasystems.

Analysts expect chatbot usage to rise significantly in the next two years. According to Gartner, “25 per cent of customer service and support operations will integrate virtual customer assistant (VCA) or chatbot technology across engagement channels by 2020, up from less than two per cent in 2017”.

The most popular chatbot use cases are tracking an order, finding basic information and asking basic questions.

While most brands claim Artificial Intelligence (AI) power their bots, consumers’ top chatbot complaints include not enough smarts to effectively answer questions, lack of context in the conversation and robot-like engagement with few human qualities.

“To truly depend on digital channels as the first line of defence in customer service, smart businesses need to unite their chatbots with the enterprise systems that can do real work — not just fetch bits of random information,” Chen suggested.

At the same time, they must apply advanced artificial intelligence to deliver true personalized interactions in real time, Chen added.


(This story has not been edited by Newsd staff and is auto-generated from a syndicated feed.)
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