Omnitive Converse
v3.1.0
v3.1.0
  • Omnitive Converse
  • Getting Started
    • Accessing Converse
    • Terminology
  • Admin Essentials
    • Libraries and Intent Management
    • Intent & Content Building
      • Create an Intent
      • Editing an Intent
      • Change an Intent's Status
      • Conversation Context
      • Admin Chat Info Panel
    • Teaching Your Bot
    • Improving Your Bot with Unhandled Phrases
    • Chat Analytics
    • Common Space
    • Bot Management
    • User & Roles Management
    • Multilingual Bots
  • Admin Advanced
    • Building Transactional Flows
    • Collecting User Inputs using Slot Filling
    • Ontology Management
    • Data Integrations
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On this page
  • Overview
  • Filter Panel
  • Chatbot Usage Trend
  • Chatbot Performance
  • Engagement
  • User Activities
  • No of Sessions
  • Average Duration
  • Messages Sent
  • Deflection Rate
  • Conversations
  • Content Performance
  • Flow Diagram
  • User Satisfaction

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  1. Admin Essentials

Chat Analytics

PreviousImproving Your Bot with Unhandled PhrasesNextCommon Space

Last updated 4 years ago

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The Analytics component of Converse provides information about the system usage. It allows you to view data concerning metrics revolving around engagement, user performance, user satisfaction & user statistics. These data can be filtered by several parameters, such as the time period, bot, or delivery channel.

Overview

The overview page shows the chatbot active users trend and chatbot performance. To navigate the Analytics page, select the button on the navigation bar.

Filter Panel

The analytics page shows data for ALL bots by default. To access the filter, select the button on the top right hand corner of the page. The filter panel will slide in from the right.

Filter by Bot: To filter the analytics data by bots, select the particular bot by expanding the dropdown panel. The dropdown panel will display all the bots you have permission for.

Filter by Delivery Channel: Filter the analytics data by Delivery Channel by selecting the relevant checkboxes.

Chatbot Usage Trend

This graph shows the data trend lines for:

  • New Users (Red Trend Line) - Unique first time users of the chatbot.

  • Returning Users (Blue Trend Line) - A returning user.

  • Total Users (Green Trend Line) - Total number of new users and returning users.

You can specify the date range to filter the data and the frequency for day, week, or month. You can also filter the bot and delivery channel used.

Chatbot Performance

The Chatbot Performance displays an overview of the top-level metrics that indicate the performance of the bot over the specified period in the Date Range Filter.

Changes in metrics are expressed in either percentages or the absolute value, with the change being obtained by comparing this period vs the last period. For example:

  • If the Date Range filter is set from 7 to 7 May (1 day), the period to compare with is 6 - 6 May (1 day)

  • If the Date Range filter is set from 8 to 14 May (7 days), the period to compare with is 1 - 7 May (7 days).

  • If the Date Range filter is set from 1 to 31 May (31 days), the period to compare with is 31 March - 30 April (31 days).

The following metrics are covered and shown as “cards” on the chatbot performance page:

Name

Interpretation

Description

Total Users

Higher is better

The quantity of users who talked with the chatbot (does not need to be unique users)

Chatbot Rating

Higher is better

The average chatbot rating received

Deflection Rate

Lower is better

The percentage of conversations where the user:

  • obtained a useful answer or;

  • had significant activity,

AND

  • the Escalate intent was not triggered

Total Fallback Count

Lower is better

The total number of instances where the system was not able to understand the user

Avg Session Duration

Higher is better

The average duration from Session Start to Session End

Overall Confusion

Lower is better

The percentage of interactions where the system was not able to understand the user

Engagement

User Activities

This metric shows the overall usage in terms of total number of sessions (conversations) and messages sent by the user.

No of Sessions

The total number of sessions occurs in a given day. It is the sum of all conversations that was conducted between 0000hrs and 2359hrs for a given day.

Average Duration

The average duration is calculated as the Total Session Duration / No. of Sessions

Messages Sent

The total number of messages sent by users and the bot.

Deflection Rate

The deflection rate represents the percentage of conversations where the user obtained a useful answer or had significant activity, and the Escalate intent was not triggered. In essence, it signifies the rate at which a user question / query was fulfilled without needing the help of a live agent.

The deflection rate is calculated by comparing the conversations that had occurred in the current period against the conversations from the previous period. Hence, the deflection rate is dependent on the date range selected.

Metric

Description

Deflection Rate

Deflection describes the scenario where the user was able obtain to useful answer(s) from the chatbot, which may have resulted in him/her not asking the physical customer support helpdesk for help (Escalate was reached)

Deflection Rate % = ( No. of Helpful Conversations + No. of Conversations with significant activity ) / Total Conversations

No Activity

No. of Conversations with No Activity is the Total Conversations:

  • WITHOUT No. of Conversations that Escalated

  • WITHOUT No. of Helpful Conversations

  • WITHOUT No. of Conversations with significant activity

Escalation Enquiries Reached

Sum of total conversations in which there was at least 1 message that was escalated

Marked an Answer as helpful

No. of Helpful Conversations within a period is:

Sum of conversations in which there was at least 1 system message rated to be useful by users

Conversations

Viewing Individual Conversations

Content Performance

The following metric cards are shown in the content performance page:

Name

Interpretation

Description

Total Fallback Count

Lower is better

The total number of instances where the system was not able to understand the user

Overall Confusion

Lower is better

The percentage of interactions where the system was not able to understand the user

No. of Message Sent by User

Higher is better

No. of Message Sent by User

Total No. of Answer Rated Helpful

Higher is better

Total No. of Answer Rated Helpful

Flow Diagram

This page shows the detailed content performance for a specific Intent in the form of a flow diagram. To access the flow diagram, click on the “View Flow Diagram” option.

The following metric cards are shown in the each individual flow diagram page:

Name

Interpretation

Description

Times Asked

Higher is better

The number of times this Intent was triggered

Fall Completion Rate

Higher is better

The percentage of instances where the user reached the final state of the Intent's dialog flow

Fallback Count

Lower is better

The number of occurrences where the user said something unexpected while progressing within this Intent's dialog flow

Confusion Rate

Lower is better

The percentage of interactions where the system was not able to understand the user, while handling this Intent

Positive Rating

Higher is better

The number of instances where a user marked an answer within this flow as correct by clicking on the "tick" icon

Interpreting the Flow Diagram:

Name

Image

Description

State Cards

Shows the number of times a particular subsequent state was triggered.

Exit Reason Popover

Shows the number of drop offs. Drop Offs are instances where the user did not continue using the chatbot (and allowed the session to expire) immediately after this State.

State Card Popover

  • Income: The number of users who reached the state.

  • Outcome: The number of users who completed the state.

  • Drop offs: The number of users who dropped off from the state.

Flow Lines

Shows the number and percentage of users moving from one state to the others.

User Satisfaction

Name

Interpretation

Description

Average Rating

Higher is better

The average rating score based on the feedback given via the Feedback “stars” rating (1-6)

The engagement component of analytics consists of data regarding how the user interacted with the bot. To access this page, select the tab on the left hand panel of the analytics page.

This component captures the conversation with users, alongside with metadata such as conversation ID, start, end, duration of conversation. Conversations can be filtered by clicking on the button. You can also mass export all conversation data as an excel spreadsheet by clicking on the button.

You can view the individual conversation history by clicking on the button under the action column for each conversation. A conversation history pop up will then appear, alongside its relevant metadata and export functionality.