Bot Analytics
Guide to analyzing bot performance and customer satisfaction using LimeChat’s Bot Overview and CSAT Analytics.'
Bot Overview: Product Usage Guide
Purpose
The Bot Overview analytics page provides insights into the performance of your bot, helping you evaluate its effectiveness in handling user interactions and automation levels.
Key Metrics
Bot Tickets
Definition: Total number of tickets handled by the bot over the selected period.
Usage: Use this metric to track how much workload the bot is managing.
Automation Percentage
Definition: Percentage of interactions resolved by the bot without human intervention.
Usage: Analyze automation efficiency and identify areas for improvement.
Graphs and Visualisation
1. Automation Percent Chart
What it Shows: Daily trends in automation percentages over the selected date range.
Interpretation:
Rising trends indicate improved bot efficiency.
Declining trends may signal an increased need for manual interventions or bot issues.
Actionable Insights:
Monitor fluctuations to adjust bot workflows or optimize training data.
2. User Intent Breakdown
What it Shows: Distribution of user intents across various categories (e.g., Track Order, Cancel Order).
Interpretation:
High volumes of "Talk to Agent" may indicate gaps in the bot's capability to handle user queries.
Frequent intents like "Track Order" or "Find Products" suggest popular user needs.
Actionable Insights:
Focus on improving bot flows for intents with high interaction volumes.
Train the bot further to reduce "Talk to Agent" cases.
Filters and Navigation
Time Range Filters
Options: Last 7 Days, 30 Days, or custom time ranges.
Usage: Drill down into specific periods for performance comparison.
Inbox Selection
Options: Choose between different inboxes or communication channels.
Usage: Analyze channel-specific performance metrics.
How to Use Insights
Identify Improvement Areas: Use automation percentage and intent breakdown data to focus on training the bot for intents with high manual intervention.
Enhance Customer Experience: Ensure intents with high volumes are addressed efficiently by the bot.
Track Progress: Regularly monitor the graphs to ensure consistent or improving bot automation over time.
Bot CSAT Analytics - Product Usage Guide
This guide provides a comprehensive overview of the Bot CSAT section in the CRM, explaining its key components, metrics, and how to interpret the analytics for actionable insights.
Overview of Bot CSAT Analytics
The Bot CSAT (Customer Satisfaction) section helps you monitor customer feedback specific to bot interactions. It measures how satisfied users are with the bot’s performance and provides a breakdown of response rates and satisfaction levels.
Key Components of the Bot CSAT dashboard
1. Total Responses
Definition: Displays the total number of responses received from customers for the bot's CSAT surveys.
Usage:
Monitor response volumes over time to ensure adequate feedback collection.
A low number may indicate fewer CSAT surveys being triggered or poor engagement.
2. CSAT Rating
Definition: Shows the average customer satisfaction score, typically rated on a scale of 1–5.
Usage:
A higher rating (e.g., 4/5 or above) indicates strong satisfaction with bot interactions.
Investigate cases with consistently low ratings to identify improvement areas in bot flows.
3. Satisfaction Score
Definition: The percentage of responses marked as “satisfied” (e.g., Happy or Very Happy).
Total number of positive responses / Total number of responses * 100
Usage:
Use this metric to gauge the overall happiness of customers with bot responses.
Aim for a Satisfaction Score of at least 80% for optimal customer experience.
4. Response Rate
Definition: The percentage of customers who responded to the CSAT survey out of the total number surveyed.
Total number of responses / Total CSAT survey messages sent * 100
Usage:
A high response rate (50% or above) ensures more reliable feedback.
If the response rate is low, consider revising the timing or placement of the survey trigger.
5. Response Split
Definition: A pie chart or visual breakdown showing the percentage distribution of different feedback categories (e.g., Very Happy, Happy, Not Satisfied, etc.).
Usage:
Quickly identify the overall sentiment of customers.
Address areas where negative responses (e.g., Sad or Disappointed) exceed acceptable levels.
Bot CSAT Summary Table
This section provides granular insights into the CSAT survey results broken down by specific events or bot flows.
Metrics Explained
Event Name
Indicates the bot interaction type or flow (e.g., FAQ, order status inquiries).
Track which flows have higher/lower satisfaction scores.
Avg. CSAT
The average CSAT rating for the event or interaction.
Focus on events with below-average ratings to improve satisfaction.
Total Yes & No Questions Sent
Total number of CSAT surveys sent to customers during the interaction of respective flows
Ensure enough surveys are being sent to get representative feedback.
% Users Clicked on Yes
Percentage of users who marked satisfaction with the bot (clicked "Yes").
Indicates positive responses; track this against benchmarks.
% Users Clicked on No
Percentage of users who marked dissatisfaction with the bot (clicked "No").
Identify flows where dissatisfaction is unusually high.
Ratings Collected
Percentage of ratings collected out of total Yes/No responses sent.
A higher percentage ensures more accurate insights into customer sentiment.
How to use this data effectively
1. Identify Key Improvement Areas
Analyze events or flows with low Avg. CSAT or high "No" percentages.
Investigate what causes dissatisfaction (e.g., unclear bot responses, incorrect answers).
2. Optimize Survey Timing
Ensure surveys are sent at appropriate touchpoints (e.g. faq, product searrch etc.)
3. Track Progress Over Time
Use historical data to observe trends in satisfaction scores and response rates.
Ensure new updates or improvements reflect positively in the CSAT metrics.
4. Prioritize Events with High Volume
Focus on flows with the highest number of interactions, as they impact overall satisfaction the most.
Implement improvements in high-traffic events to make the biggest impact.
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