What are analytics and how do analytics apply to chatbots?

Modern analytics are way more than a mere count of people who accessed a service and a regional breakdown of the data. They measure how much time users spent on each interface, what call to actions did they respond to, how long their attention span was and there are even heat-map tools that can track what areas of an interface user have been most focused on and interacted with.
In a nutshell, analytics measure the quality of the user experience.

A detail as small as a label on a button can determine the effectiveness of an interface and its success over the competition. Finding and removing the friction points is the key to an high “conversion rate”, which is “the proportion of visitors [..] who take action to go beyond a casual content view or [..] visit”.

In chatbots, it’s important to observe the conversation flows, count the number of “intents” and “entities” successfully decoded over the total number of incoming messages and the number of messages that a user had to type in order for his request to be fulfilled.

The most important action to take in order to improve the effectiveness of a chatbot is to set and manage expectations.

With the upcoming self-driving cars revolution and the democratization of AI, now available in a wide range of personal devices and home appliances, it took very few years to users to become more and more accustomed to technologies that once existed only in sci-fi movies and books.
This often creates expectations in them that go beyond the current state of technology. It is an highly sensitive topic for chatbots, as many users expect to be able to talk to them like they were actual humans (and some less-tech-savvy users can’t always tell they aren’t) and can get easily annoyed if they don’t live up to such expectations.

In spite of the extensive knowledge on user and customer behaviour that we can rely on today, humans can still be unpredictable at times. Manually reviewing all conversations would be an unworkable task and in contrast with the principles of automation and conversational interfaces. Creating the perfect experience requires thorough testing, especially A/B testing, and constant analysis, validation and tuning.

Chatbase can perform very complex analyses of all the conversations between users and bots, measuring the effectiveness of each message, the expectations and suggesting optimizations in a convenient, clean graphical interface. Best of all, it’s even free.