Story analysis is a good way to know what part of the conversation users like or do in a frequent manner. Also it shows what part needs to be updated to get more user. In Alice, we provide information as to which component (story/node) of the chat bot is invoked, how many times, along with the % of success accuracy. We also provide a pie chart depicting the same information for better clarity of overall node usage across the bot.
User will select the platform, intent and date range from the filtering options.
All the connected platforms to that project (default all)
Last 7 Days
Last 14 Days
Last 28 Days (default*)
Last 3 Months
After selecting the platform,action and date range options user will get the following analytics:
Name: Name of intent/event with details as help text.
Total Messages: Count of messages with that story in the timeline.
Automated: Percentage of incoming message from users and replied by bot in the time frame.
Distinct Customer: Count of distinct users with that story in the timeline.
Ratio: It shows ratio of the automated messages among the total messages.
Action: View details link will take the user to the conversation log and show the whole conversation of that clicked story name. User can also see that particular story name in the event box above the conversation history table.