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Chatbot Analytics: Track Conversations and Improve Performance Over Time - AIWU – AI Plugin for WordPress
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Chatbot Analytics: Track Conversations and Improve Performance Over Time

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Your chatbot is live and conversations are happening. Analytics tells you what visitors are actually asking, which questions go unanswered, and how your chatbot performance changes over time. This guide shows how to read AIWU chatbot analytics and turn the data into improvements.

Before You Start

You’ll need:

  • A working chatbot that has been live for at least a few days with real conversations (Set Up First Chatbot)
  • Time needed: 5 minutes to review, ongoing monitoring
  • Plan required: Free (basic) · Pro (full conversation history and export)

Where to Find Analytics

Go to WordPress Admin → AI Copilot → AI ChatBots. Click your chatbot, then go to the Analytics tab.

Alternatively: AI Copilot → Analytics for a cross-chatbot dashboard showing all bots at once.

Key Metrics Explained

Total Conversations

Number of unique chat sessions started. A “conversation” begins when a visitor sends their first message. Use this to track overall chatbot adoption — is it growing week over week?

Messages Sent / Received

Total messages from visitors (sent) and from the AI (received). A high ratio of visitor messages to AI messages suggests visitors are asking multiple follow-up questions — either because they’re engaged, or because the first answer wasn’t sufficient.

Average Conversation Length

Average number of message exchanges per conversation. 1–2 messages = visitor got a quick answer and left. 5+ messages = either a complex conversation or the chatbot is struggling to answer clearly.

Resolution Rate (if available)

Percentage of conversations where the visitor didn’t escalate to human support or abandon mid-conversation. Higher is better. Low resolution rate indicates your training data has gaps.

Top Questions

The most frequently asked questions or topics. This is gold — it shows you exactly what your visitors want to know. Use it to:

  • Add missing information to your embeddings training data
  • Update your website’s FAQ page
  • Improve your chatbot’s welcome message to proactively address common questions

Unanswered / Failed Queries

Questions the chatbot couldn’t answer or responded with “I don’t have that information.” This is your training gap list — add these topics to your knowledge base.

Reading Conversation History

Go to the Conversations tab to browse individual chat sessions. For each conversation you can see:

  • Full message thread (visitor question → AI response → visitor follow-up)
  • Session start time and duration
  • Page where the conversation started
  • Device type (mobile / desktop)

What to look for in conversation logs:

  • Questions where the AI gave a vague or wrong answer → add better training data for these topics
  • Questions the AI answered perfectly → identify what made those answers work (good training data, clear question)
  • Conversations that ended abruptly after one exchange → visitor didn’t get what they needed
  • Long conversations with many follow-ups → the initial answer was incomplete

A Weekly Review Routine (10 minutes)

Set aside 10 minutes each week to review your chatbot analytics. This routine catches problems early and steadily improves performance:

  1. Check top questions — anything new this week that’s not in your training data?
  2. Review failed queries — add the top 3 unanswered questions to your knowledge base
  3. Read 5 conversation logs — random sample, look for quality issues
  4. Check conversation volume trend — is usage growing or declining?
  5. Update embeddings if you added new training content

Ten minutes per week compounds significantly over months — a chatbot that improves 5% each week is dramatically better after three months.

Exporting Analytics Data (Pro)

Go to the Analytics tab and click Export to download conversation data as CSV. Useful for:

  • Reporting chatbot ROI to stakeholders
  • Deeper analysis in Excel or Google Sheets
  • Building a training dataset from real visitor questions

Common Issues

Problem: “Analytics shows zero conversations even though my chatbot is live.”
Fix: Make sure conversation logging is enabled in the chatbot settings (sometimes off by default for privacy). Also check that the chatbot is actually receiving messages — test from an incognito window and see if the test conversation appears in the log.

Problem: “Resolution rate is very low (under 40%).”
Fix: Review your failed queries list — these are the topics you need to add to training data. Also check your chatbot instructions: if the AI is instructed to say “I don’t know” too aggressively, it may be refusing to answer questions it could handle. See Train Chatbot with Embeddings.

What’s Next

Last verified: AIWU v.4.9.2 · Updated: 2026-02-25

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