percentage of users who performed the target action;

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The analysis is based on metrics that track user interactions with the bot. This data includes not only quantitative indicators such as the number of dialogues and response time, but also qualitative ones, such as customer satisfaction and conversion to sales.

Three Directions for Chatbot Analytics
Engagement. Measures how actively users interact with the bot. If the bot helps find the right product, answers questions, or participates in marketing campaigns, a high level of engagement means that users are getting value from it.
To measure engagement, these metrics are typically analyzed:

number of active users per day, week or month;
session duration and average number of messages per session;
Bot return rate: how many times a user re-engages with the bot within a given time.
Conversions. Show how effectively the bot performs tasks aimed at obtaining a specific result: placing an order, booking a consultation, or completing a survey.
What metrics are commonly used for analysis:

the proportion of leads that moved to the next stage of the sales funnel after interacting with the bot;
average time from first interaction to conversion.
Retention: Shows how successfully the bot maintains user loyalty list of netherlands cell phone number and brings them back for repeat interactions. Analyzing this metric helps to determine whether users’ interest is maintained after the first contact.
Metrics for assessing retention:

the percentage of users who returned to the bot after a certain period of time;
the proportion of users who interact with the bot on an ongoing basis;
the number of proactive messages that customers respond to.
It is important to choose metrics that match the objectives and strategy of the business. For example, for e-commerce, the key indicator may be conversion to purchase, and for a bank, it may be customer retention and satisfaction. General metrics such as call duration and engagement level help to get an idea of ​​the bot’s performance, but each company should individually determine the priority indicators.

Metrics for analyzing chatbot performance
Launching bots
Shows what share of users were successfully engaged in active interaction via the chatbot. This is one of the key indicators for assessing the initial effectiveness of the bot. It helps to understand how attractive the idea of ​​using the bot is for the audience and how well the implementation process is set up.

Chatbot Launch Metric Formula
How to improve the indicator: