Why businesses need enterprise visibility and analytics
Analytics empower businesses to track, dissect, and act on data and key metrics together, in a single console, from all angles. They allow you to build a deeper understanding of your customers and your employees and allow you to continually measure, analyze, and refine your chatbot strategy.
60%
of enterprise business leaders say customer analytics is extremely important today, jumping to 79% by 2020
Harvard Business Review
64%
of marketers believe that they need better data for prospecting and 56% report having inaccurate data
Forrester
How Kore.ai’s bot-powered analytics help drive your business forward
Kore.ai provides unparalleled visibility into bot, employee, and customer behavior. Get real-time, actionable insights with all the data and visualization tools you need to measure and analyze your bot from a centralized dashboard.

Bot Engagement
Better understand how users interact with your bots, allowing you to increase user engagement, acquisition, monetization, and retention through actionable bot analytics.
Our platform provides an abundance of data that can be mined to improve performance, including:
- Tasks performed
- Alerts sent
- Total chats and sessions
- Active users
- Demographics
- Top bot tasks
- Top bots within an account
- Session benchmarking
Get as granular as you want with the ability to filter information based on categories like duration, language, and channel.
Conversational Analytics
Build better, user-focused conversation flows that create engaging, memorable experiences for your core audience.
Conversational flows
Gain a deeper understanding of user behavior. Conversational flows map popular user paths, tasks, and exit points within a visual context, helping to surface patterns, trends, and correlations that might go unnoticed using text-based data analysis methods. This includes the top identified intents based on and ranked by usage statistics, user utterances that were not understood or handled by the bot, and common follow-up tasks and sub-intents.Conversational flows are based on total bot-user sessions within a given time period.
Chatbot transcripts
Track the entire user lifecycle. Our platform allows you to view the entire chat history of past user sessions, including things like who spoke to your bot and when, how many conversations they’ve had, and the number of conversation steps involved, as well as monitor current conversations. We help protect user privacy by limiting access to only those with the appropriate privileges and by automatically redacting personally identifiable information (PII).
- Post-session: Transcripts are available for analysis as soon as a session is closed.
- Run-time: Transcripts can be made available in real-time, so all user-bot conversations can be monitored and interrupted by a human agent if needed.
- Task failure identification: The context object, which includes contextual data such as intents and entities extracted, user utterances, and more, is stored within the transcript so developers can easily view, analyze, and adjust bot configurations.
Sentiment analysis
Gain deeper insight into the interactions users are having – whether they are positive or negative – and provide better service to employees and customers. Our platform programmatically predicts user emotions by extracting keywords and topics from user utterances and evaluating them against common user sentiments such as joy, fear, and anger. A score, ranging from -3 to 3, is then generated based on the intensity of the sentiments detected. Sentiment is analyzed on both the individual utterance level and the session level.
Data generated during this process can be collected as feedback from users, normalized, and aggregated to provide product managers and designers the info they need to enhance the user-bot conversational experience and improve context switching.

Functional Analytics
Get the data you need to train and improve your bots performance, including how well they are identifying and executing tasks. Well trained bots mean more conversations, efficient task execution and better productivity.
Intent matching
Give your bots the skills they need to meet user expectations. Our platform records all utterances that were successfully matched to a unique intent and all utterances that did not match to a unique intent.
All utterances are tagged with detailed meta information, such as channel, intent detection logic, language, user, and more. This information can be filtered by intent, user, date, and language.
Utterance grouping
Spend less time combing through chat scripts to find the data you need to effectively train your bots. Our platform groups all utterances based on ML models and semantic similarity, including stop words, spelling corrections, and nouns. Entity values are also extracted and replaced with placeholders. This allows you to quickly identify patterns, select large sets of similar utterances at once, and train your bot.
Task failures
More effectively identify and troubleshoot bot task issues. Our platform records and categorizes all instances where a bot fails to complete a task, as defined by the developer during the dialog creation process. All contextual information is retained, along with the dialog flow, and developers can review the chat transcript or service response JSONs at any time to better understand the underlying causes.
- Tasks aborted
- Alternate tasks initiated
- Chat interface refreshed
- Chat transferred to human agent
- Authorization failed (repeated attempts)
- Incorrect entity provided (repeated attempts and max allowed tries)