How to Use a Chatbot for Data Analytics

Why you should use a chatbot for data analytics

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There are various important reasons to use AI agents for data analysis. Still, here we are going to share some of the most important information on data analytics uses that will help you to scale the business.
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Blockers Identification and Removal

The AI chatbot of data analytics is so smart that it will go deeper inside the process and flow to understand why the conversation flow is breaking down. It will understand your user behavior and its actions. It will analyze why the user is getting stuck and, all of a sudden, why the user is taking a different action instead of the desired action.

Chatbot will also check if there is a disconnection with customer support or is abandoned. It will also identify whether the conversation is escalated to an agent or not. A data analytics chatbot will identify the intent of the customer and understand it, and can enhance it to help them by connecting them to agents who need it the most.
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Goal Completion Rate (GCR)

You will only be able to measure the success of the data analytics chatbot by looking at how many users are able to complete the actions you have created in terms of conversation flow. All the KPIs will only be met if you measure all important events and metrics, if you only know that all your customers' needs are fulfilled with the help of a chatbot for data analytics, and if the task is related to the data and related work. Irrespective of the virtual AI Chatbot or any handoff to a live human agent.
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Conversation Logs Analysis

Our chatbot will help your company with some great insights related to the group chat logs at the conversation level, and it will highlight all the multiple/different actions performed by your users/customers that all customers do while making the conversations.

This will help you to understand the pain points of the customers quickly and troubleshoot the problem faster. Chatbot for data analytics will also provide you full conversation history of each customer to analyze it and understand the whole conversation deeply to come to any conclusion before taking a crucial decision.
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End-to-End Data Integration and Analytics

With the help of our AI chatbot for data analytics, you and your team will be able to analyze the chatbot data generated throughout the daily conversation between your customers and the AI chatbot. It will Clean, synthesize, and connect this data to the hundreds of chatbot analytics tools, raw data, and warehouse tools housed in the Segment integration catalog for a unified data view. It will also help you to create analytical decisions concerning the comprehensive analytics to validate customer satisfaction and drive data-driven enhancements.
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Key metrics to track data analytics AI agents

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You have to check the containment rate, where you are going to check the number of conversations in which the chatbot will be able to satisfy your customer without handing over to the human agent. You have to check the coverage of the AI agent in whether it is confident enough to know that it will be able to solve the problem of the user.

Check the total messages the AI chatbot received during each period and divide it by the total conversations during the same period. Then, you will be able to check the average message per conversation.