Customer insight generation: These platforms enable businesses to map popular user paths, tasks, and exit points via chatbot analytics dashboards (in visual context) so that organizations can identify patterns, trends, and correlations that might not get noticed using text-based data analysis methods.Improved data collection: As new data privacy regulations such as the GDPR and CCPA make the process of using third-party consumer data harder, conversational analytics software becomes a tool to collect first-party data insights since consumers are willingly interacting with bots.Relying on chatbot analytics helps businesses avoid potential failures. Many chatbot projects fail due to various reasons including optimizing the wrong metrics.

Better focus: As with other analytics approaches, chatbot analytics enables organizations to track relevant chatbot KPIs to make data-driven decisions to enhance the chatbot performance.

Reasons that make conversational analytics important are: After a business deploys a chatbot, it should track how people are using it. Due to increasing competition in every industry, customer experience has become the key driver in gaining a competitive edge. Maintaining a chatbot does not end with it going live. Requesting a demo from Haptik will allow you to experience the possibilities of conversational AI technologies and chatbot analytics. Haptik also assists its customers with intelligent chatbot analytics that help businesses better understand user behavior by examining the most commonly asked questions, the causes of user churn, the most popular products and services, trending user queries, and more. Haptik helps their clients increase sales, engage customers, and save costs by utilizing chatbots and intelligent virtual assistants. Haptik, a vendor of conversational AI, works with Fortune 500 companies such as like Disney, HP, Unilever, Zurich Insurance, and others. In this article, we cover all relevant question about bot analytics tools and important chatbot metrics that a company needs to measure vis-a-vis the progress of its chatbot/ conversational AI system: What is chatbot analytics?Ĭhatbot analytics, also referred to as conversational analytics, chatbot analytics, bot analytics, chatbot intelligence, is the process of analyzing historical bot conversations to gain insights about chatbot performance and customer experience.

If you are already familiar with web metrics, jump to chatbot specific performance metrics such as message metrics or bot metrics.)Ĭhatbot analytics is an important tool in guiding brands’ experiments with chatbots. That is why chatbots require new metrics in order to get the most out of their benefits. Web focused metrics do not calculate misunderstood requests or message delays.

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