Merely deploying a chatbot is not enough. You need to continuously monitor its performance to determine its effectiveness and how it contributes to improving customer support and employee experience.
With chatbot analytics, you can track key metrics, such as total queries received, issues resolved, cost per case, key search terms, repeat queries, user preferences, satisfaction, and much more; with all the KPIs and data visualization tools available on a centralized dashboard.
Inbuilt functionalities and utilities like conversation transcripts, sentiment analysis tools, functional analytics, visualization, and custom reporting help calculate the return on investment from the implementation of chatbots.
With chatbot analytics tools, you can closely monitor essential metrics, such as the total number of users, engaged users, chat volume, bounce rate, sessions initiated, goal completion rate, key search terms, user preferences, fallback rate, and many more, to enhance user experience and build stronger conversations.
Calculating the cost per issue and KPIs, such as total leads generated, total issues resolved, etc. helps measure the returns on investment to the business from deploying chatbots.
Chatbot analytics helps you identify the recurring queries received by your chatbot and calculate the time taken to address these issues, and subsequently, the annual handling expenses. Developers can then modify chatbot configurations to reduce the time spent handling such cases, leading to a drop in the cost per contact.
Identify customer and employee needs, expectations, recurring queries, satisfaction levels, and much more to train your bot accordingly and make it more user-centric and user-friendly. Understanding how far your users are satisfied with the chatbot’s performance helps identify the number of users returning to the chatbot for support.
BotCore’s chatbot analytics uses conversational flows to help map utterances with user intent. It follows user paths, tasks, and exit points on a visual interface, which helps understand user behavior through noticeable patterns and trends. You can use A/B testing for your flows to select the best one.
BotCore’s conversational AI analytics allows you to view transcripts of past user sessions, including details like user’s information, the number of conversations, chat duration, user utterances, intent, etc. so that developers can adjust bot configurations accordingly. By monitoring conversations in real-time, human agents can interrupt chats, if required.
BotCore’s chatbot analytics tool performs sentiment analysis by mapping keywords extracted from user utterances against human emotions, such as anger, happiness, frustration, and anxiety. Data generated during conversations can help developers improve the user’s interaction with your bot and enable better context switching.
BotCore’s analytics tags user utterances against intent logic, language, channel, etc., groups these utterances using machine learning (ML) capabilities for bot training, and measures the chatbot fallback rate (FBR) to identify instances when the bot failed to meet user expectations.
With capabilities to segment and tag conversations against specific use cases and rules, BotCore’s bot analytics program reports the weaknesses in your bot, identifies the channels with most user traffic, and enables you to focus on high priority conversations.
With BotCore, you can customize your dashboard and visualize performance data using built-in and custom metrics. Data can be filtered, and graphs can be presented as per your business needs. Additionally, you can export the reports generated to other formats.