Can We Measure Analytics for Chatbots?

With marketing shifting to conversational user interfaces, Chatbots have emerged as a powerful tool for e-commerce. As companies across the board are adopting Chatbots on Instant Messaging Apps, the question of analytics has crossed every Digital Marketer’s mind. Is there a way to measure the performance of your Chatbot?

It is important to acknowledge that with Facebook’s recent update on Chatbots on Messenger, users can now rate a Chatbot and provide their reviews. However, this is only one aspect of how your business can analyze the Chatbot’s performance.  In order to evaluate the Chatbot’s performance the following metrics should be measured.

 How many users has your Chatbot interacted with?

This number is equivalent to the number of reached users in an analytics view point. It is how many users the Chatbot has established contact with. This number can be a starting point to understand the success of your chatbot. The number of users that the Chatbot reaches can help the business understand how many users have had a successful and complete interaction with the Chatbot on Messaging Applications.

How long does the user interact with your Chatbot?

Once contact has been established with the user, the questions and data points can be measured to understand how long the conversation with the user lasted and can help us understand if the Chatbot was able to maintain the communication flow. For example if the Chatbot understands 10 different “conversational flows” how far has the interaction with the Chatbot progressed and where does it tend to go down. Marketers can user this to amend the conversation to minimise the number of users stopping the conversation.

How many times does the user interact with your Chatbot?

Depending on the purpose of the Chatbot, it may be important to understand the retention aspect of the Chatbot. Do users interact with your Chatbot on a daily basis? Another metric to measure can be the number of users that have “muted” the Chatbot after the initial interaction. For example, in the case of a restaurant booking via a Chatbot is the user more likely to order through the Chatbot again or resort to traditional ways of booking. This can be helpful to measure if a Chatbot is assisting in improving the existing methods or processes for a company.

What is the Conversation Success Rate of the Chatbot?

The Conversation Success Rate, according to us at Oh My Bot ! can be measured by the resistance of communication blocks by the Chatbot. There can be some instances in the conversation where the Chatbot is unable to understand the user. Therefore, it is important to measure the number of times, the Chatbot was unable to process the information which determines how successful the conversation with the user was. For example, if a user asks the question “How old are you?” the Chatbot if not intelligent enough may reply with “I don’t understand that.” which is an obstacle while trying to maintain a successful flow of conversation with the user. These blocks can also help the Marketers train and improve the Chabot constantly.

How many leads has your Chatbot generated?

Chatbots can be an important tool for companies to generate leads as it can request users to input their contact information for the business to get back to them. Therefore, if the user is willing to provide the information to a bot it can be an effective lead generation tool which the brand can measure.

How many conversions have been made on your Chatbot?

For businesses looking to promote their website or products, the Conversion from Chatbot to sales can be measured to understand the performance and efficiency of a Chatbot. How many users clicked on the website through the Chatbot? How many users bought an item by being redirected by the Chatbot? These questions can help Marketers understand if their Chatbot strategy is effective.

While metrics and analysis of Chatbots are still in their initial stages, we can foresee different tools for Chatbot Analytics to pick up in the upcoming years of the Chatbot Revolution.

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