4 Important Chatbot Metrics

2019 is a year of capitalising on the amazing progress made in 2018 alone on AI for speech and text. Big questions remain on how to design great conversations — this is not a solved problem but this week we capture an interview with a senior researcher in the space, as well as 4 metrics against which chatbot success can be measured.

This week we’re a bit heavy on the big brands but as you’ll see in our back issues, we highlight the little guys too — so if you have news you think is worth sharing please don’t hesitate to drop us a line.

Also in this issue of Speaking Naturally:

• 🧠Google’s Conversational AI year in review
• 🤫Microsoft’s whisper tech patent
• 🍏Apple’s new Business Chat

Leading the Pack

Google and AI speech and text: 2018 in review
This is a nice summary of how Google’s commercial contributions to AI for speech and text last year in some cases are setting radically new expectations for what we can expect from conversational systems. Have a look at human-like voice assistants virtually indistinguishable from real agents, auto-suggest inside your emails, and a few others.
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Sprint launches Apple Business Chat
Apple Business Chat is a new chat platform launched in 2018 that helps connect people with businesses when using an Apple device including Safari, iMessage, Apple Maps, Spotlight and Siri. You must support human escalation as part of launch: Sprint’s the latest big brand to launch and we believe, the first telco.
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Old Problems, New Solutions

Will we always talk out loud to our devices?
We already have Alexa’s whisper mode and Microsoft looks to be taking this further with its “silent voice input”.
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Smarter Conversations

Measuring Chatbot Performance: 4 Important Metrics
When developing a chatbot, your work is never done. Releasing it into the wild is only the first step: from there, you’ll need to pay close attention to the conversations your users have with it in order to iterate upon and improve the bot.
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Here at CognitionX, we have also identified some excellent qualities we believe contribute to great chatbots, which we’ve called the AACE factor.
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Learn from the Pros

Proactive assistants: Interview with Microsoft’s principle researcher
Being able to remember relevant parts of a conversation and linking it to new discussion is one of the great challenges of conversational AI today. This interview is a great guiding piece on Microsoft’s latest progress.

Interviewing Google, Alibaba, Samsung and more
A podcast we recommend that interviews excutives from Samsung, Google, Nuance, Alibaba, Sensory, CEVA, Abilisense, AvatarMind, Pindrop, and LG. Read our top quotes from the podcast