For many, chatbots have already become an indispensable tool when it comes to customer relationships. Due to service automation processes and the costs reduction that this technology provides, there is no denying the fact that its use is very promising for the future. However, in order to be able to derive its benefits, it’s necessary to evaluate its performance – and that is exactly what we will address in this article: metrics in chatbots.
Understand that the indicators analysis that involves virtual assistants’ “behavior” plays an extremely important role in the success of their implementation. As in any other instrument used in the digital environment, the measurement of results is an essential part of improving performance.
With that in mind, we’ll introduce some of the key metrics in chatbots. Continue reading and check it out!
Users reached’s total number
The first metric to analyze couldn’t be other than the total number of users reached, after all, it’s interesting that you know how many people used your chatbots.
The point to note in this case is that if your sample isn’t large enough, the numbers won’t be as reliable as they should be. In other words, if a given chatbot interacts with only 50 users, data absorbed will hardly have the same validity when compared to an analysis with 1,000 users, do you agree?
It is worth mentioning that it’s necessary to distinguish users between active and inactive, determining them for different periods, such as weekly or monthly, for example.
The interaction rate is also a point to be observed. If the chatbot purpose is to sell, many interactions indicate that consumers are interested in your products or services.
However, when a virtual assistant is assigned to solve questions or problems, high interaction rates may mean that users aren’t getting the answers they would like to. In summary, this indicator should be analyzed based on your chatbot purpose.
Clickthrough Rate (CTR)
With the click-through rate, it’s no different: you need to consider the chatbot purpose so you can understand it. To illustrate this, imagine that your job is to send blog updates with the links to the new content. Here, the more clicks, the better.
However, if the idea is to provide an automatic service in which the visitor needs to request system, a high CTR won’t always be a good sign. This may be related to the difficulty that people are finding in getting their answers.
When we talk about metrics in chatbots, the confusion triggers deserve special attention. Basically, they occur in situations in which a virtual assistant isn’t able to assimilate a request: the tool forwards users messages such as “Sorry, I didn’t understand your question”.
This occurrence is characterized as a confusion trigger, which in turn should be taken into account to improve the chatbots.
Finally, it’s worth mentioning that in the internet environment everything must be monitored, because only then will it be possible to achieve the best results.
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