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Thursday, January 12, 2017

Chatbot Retention Problem

The open question is, how well will people accept non human online interaction?    Bots can be novel, but that is not enough.  Bottom line, they need to provide a faster and more accurate interaction than talking to a human or reading a list of solutions.  They also need to be able to utilize the context of a problem as much as possible. I want a system to detect a problem and solve it without interaction if at all possible.  Bring on intelligent autonomy.   Below some good general guidelines and bot examples.

3 tips on improving chatbot retention   by Stefan Kojouharov  in Venturebeat: 

Chatbot retention has been a real problem. It’s so poor that most people don’t even get past the first two messages. According to İlker Köksal, the CEO of BotAnalytics, the initial drop-off is huge: “About 40 percent of users never get past the first text, and another 25 percent drop off after the second message. Daily retention rate is at a paltry 1–2 percent, and the monthly retention rate for bots isn’t much better, sitting at about 7 percent.” Fortunately, after hacking for the better part of 6 months, a few bots — such as the weather bot Poncho — have found the light and are seeing awesome retention and engagement rates.

There is such a wide variety of chatbot use cases that it does not make sense to compare against the average. You might have a use case that solves a one-time problem, in which event you hope the user never has to come back (such as the DoNotPay lawyer bot). The best way to benchmark is by comparing your bot to mobile apps in your category. At the bare minimum, your goals should be to surpass them.  ... " 

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