These Chatbot Usage Metrics Will Change Your Customer Service Strategy
News News, 21/12/2017
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Chatbots are used in a huge variety of ways, from answering queries to selling products to entertaining the user with stories and games. But bot usage metrics have been scarce; data like chat session lengths, user satisfaction, percentage of escalation to humans, and leading channels and verticals have been amiss.

That’s why I went to Avi Ben Ezra, CTO and co-founder of SnatchBot, an Israeli-based company that boasts over 30 million end users of bots built using their platform. Since May 2017, companies including Accenture, Allianz, Aman BankUber, Veolia and Vodafone have created Bots via SnatchBot’s platform, and they’ve been tracking user metrics ever since.

I had the pleasure of speaking with Ben Ezra recently, to find out more about how SnatchBot was founded, and what they found out about user experience when they started looking at metrics.


How and why did you start your company?

I founded SnatchBot with my brother Henri in order to make chatbots accessible to more people and enterprises than ever before. We have a background in telecoms and realised that a revolution in communications was underway, which we wanted to be part of.

People spend more time now in messaging apps like MessengerLine or WeChat than using Social Media, browsing the web or talking on the phone. There is a huge demand by people for a tool that allows them to communicate with organisations and businesses without having to leave their channels. They don’t want to download apps; they don’t want to be on hold on a phone call; they don’t want to scroll through web browser results. The chatbot is the solution, and this is our mission at SnatchBot: to make the creation of chatbots something that is quick, easy and cost-effective. Our bot building platform requires no coding skills, and we have a wide range of Bot Templates that serve customers in several verticals including customer service, e-commerce, IoT, and banking. By simplifying the creation of chatbots, we can greatly reduce the effort and cost that often comes with building and deploying a bot.

Any bot built on our platform can be easily deployed on any platform or channel with which we’re integrated in a few clicks, so there is no need for a different chatbot for each, and that also greatly saves time and effort. We’re also excited by advances in Artificial Intelligence and have created our own state-of-the art Natural Language Processing (NLP) system.


What are the main challenges facing bots?