How To Evaluate Your Customer Service Chatbot For The Best Business Results
The number of interactions your customer service chatboat has with your users is an indicator of its popularity among your target audience. The chatbot activity volume actively reflects your customers’ inclination to use customer service chatboats to increase all types of requests – from the simplest regular queries to the most complex questions. By tracking activity, you will be able to find out if your customer service chatboat is being liked frequently and if the number of users is increasing. The use itself can be both voluntary and motivated.
- Voluntary use when users initiate a conversation with your own customer service chatbot
- Quick access, when users start a conversation with your chatbot after receiving a notification
A rising voluntary usage rate is a great indication that users are finding you customer service chatboat useful and convenient and are happily ready to use it regularly in the future. Once you see graph growth enough, you can rest assured that your customer service chatboat is well positioned to steer your customers’ experiences in the right direction.
The bounce rate is an indication of the amount of customer interactions that decrease as a result of successful user experiences. High bounce rate means that Your Customer service chatboats are not being offered for its stated core competencies and are unfortunately ineffective for arbitrary consultation on random topics. You may need to update your knowledge base immediately, reschedule your place during the customer experience and take proactive measures to bring down the bounce rate.
A high retention rate indicates a large percentage of users who are using your customer service chatboat. After some time again and again. A climbing retention rate means that your customers are strongly predisposed to return to your chatbot for their queries. This high frequency of duplication prevention is good news for the relevance of your chatbot and acceptance among your customers.
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The number of sessions that are activated simultaneously with your chatboat is a good indicator of its demand and reliability. You can get a more detailed measurement of its effectiveness by comparing the rate of this usage by open sessions against the average number of open sessions during a given period.
This metric is unavoidable to analyze if you are hitting your goals. Your penetration rate for your target population says a lot about the usefulness of your customer service chatboat among your intended customers. Suppose this target audience session volume is typically low. In that case, you may need to change your customer experience strategies or change your chatbot’s offerings to suit the needs of your focus groups.
The number of questions your customer service chatboat has answered is paramount to measuring its accuracy and accountability. The response volume of your chatbot can be a transparent account of its knowledge base, transparent harvesting capacity, and its agility. And a touchstone is also how far it can go in terms of accuracy and how wide it can be in the unchanged question land.
This indicator helps you evaluate the average length of interaction between your chatbot and its users. This can be a useful metric if you aim to increase the efficiency of the bot as it will help determine the amount of time saved by your customers as well as your service teams.
This indicator tells the time of day when your customers take your advice. Chatbot When there is no one around, there is still a disturbance most actively and in activity. This metric is particularly helpful in determining the benefits of this 24/7 tool, so that you are present to your customers during critical hours of time when your support teams were already unavailable.
How good is your Chatbot Able to understand the user’s questions and develop their existing knowledge base? If your chatbot does not understand the customer’s question, it is either because this question is something that has no meaning for it or because the customer service chatbot does not have the necessary knowledge in the relevant field. For example, a chatboat specializing in furniture sales would not understand a football-related question!
This rate reflects the number of users who were able to get the help they needed solely through the responses given by your chatbot, without later talking to a live support agent. The percentage of sessions your bot manages singly will be as high as the self-service rate, without redirecting to the live agent.
This metric is important because customer satisfaction increases in proportion to the first contact resolution (FCR) rate of your support center, which is the percentage of customer queries that are resolved by your team on first contact. So this The indicator is important for the analysis of your ROI Customer service chatbot Assignment or Project.
When you are regularly evaluating the effectiveness of your customer service chatbot using these metrics, it is imperative to know what your users ultimately think of your chatbot in order to streamline its operations. . Did it help well? Did they feel satisfied? Will they be happy to interact with chatbots in the future?
There are two different ways you can find out:
- You can directly ask users if they felt satisfied with their experience after every support interaction.
- You can provide users with the opportunity to fill out more in-depth questionnaires to get specific information (such as “Were the responses clear?”
This response will allow you to calculate two indicators:
- Satisfaction rate (the average score obtained by your chatboat in the evaluation by your users)
- Evaluation rate (the percentage of sessions in which a user has evaluated your bot’s responses at least once)
It is important to know these key indicators to evaluate the performance of your chatbot. However, the best indicators for evaluating your chatboat are not always the same for every company or every customer service chatboat.