Chatbot metrics to track for best chatbot performance
The choice of chatbot metrics to track comes down to what type of chatbot you are using and what is your overall strategy. We will be covering metrics both for rule-based and conversational chatbots falling into three categories: users, user engagement, or bots’ performance.
User metrics can give you an idea of how many potential clients you can get if you keep increasing engagement.
Total number of unique users
Depending on the chatbot platform you use, the total number of unique users is calculated based on unique devices, unique IP addresses, or shared contact information like phone numbers or email addresses.
Regardless of the specifics, this metric provides a close-to-reality number of individuals who use your chatbots.
Having this information, you can estimate your chatbot’s overall popularity and analyze factors influencing its growth or decline over time or within specific periods.
Knowing the total number of unique users, you can also calculate conversion.
For example, if you have a chatbot that handles pizza orders, you can calculate the conversion from a chatbot user to a customer in a given period.
Let’s say the total number of your chatbot unique users in November is 50,000, and the total number of pizza buyers is 5,000.
Divide your pizza buyers by chatbot users: 5,000 / 50,000 = 0.10. Then, multiply the result by 100: 0.10*100 = 10%. This is your conversion rate from a chatbot user to a customer.
The “new users” metric refers to the people who started using your chatbot only recently. The recency will depend on the nature of your business and can be anything from “subscribed today” to “using your chatbot only for three months.”
This metric helps measure the efficiency of user acquisition activities, like social media campaigns or paid promotions, whether it is Facebook ads or partnerships with influencers.
For example, if you actively promoted your products for the whole month of April, you can compare the numbers of new users in March and April to see if there is an increase and detect whether your campaign was successful.
You can also use the acquired data for segmentation: create a segment for users who joined your chatbot during your April campaign and send them personalized deals or content to move them closer to conversion. You can also ask them about their interests and needs to go for a deeper segmentation.
Measuring chatbot engagement allows businesses to detect whether a chatbot flow is aligned with users’ needs and drives them closer to conversion.
Active users and retention rate
The “active users” metric refers to users who interacted with your chatbot in a given period, while the retention rate is defined by the fact that users keep coming back to use the bot again.
The number of active users provides you with insights into the quality of your subscriber base. By extension, you can estimate engagement and retention since you can see how many users subscribed to the chatbot and forgot about it right away vs. how many still use it.
In Selzy, you have the information about active users front and center on the page that lists all your chatbots — right next to the total of chatbot users.