GC Analytics for Guided Conversations

Analyze and Improve Your Guided Conversations with Analytics

In Short
GC Analytics turns your chatbot conversation data into clear, actionable insights; how many conversations start, complete, or get abandoned, where users drop off, and when they are handed to agents. Use it to find friction points and improve your flows with confidence.

What is GC Analytics

GC Analytics turns your chatbot conversation data into clear, actionable insights. You can track how many conversations start, how many complete successfully, where users abandon flows, and when conversations are handed off to agents.

You do not need to be a data expert. The dashboard is designed to help support managers, product owners, and analysts quickly spot issues and make confident decisions.

When should you use GC Analytics?

You should check GC Analytics when you want to:

  1. Measure how effective your conversation flows are.
  2. Identify blocks where customers are getting stuck or dropping off.
  3. Understand peak usage hours across channels.
  4. Reduce agent handoffs and improve conversation flow success.
  5. Track performance after publishing a new flow version.
  6. Monitor how your flow interacts with other flows using Jump blocks.
  7. Track webhook and integration usage to ensure backend actions are working as expected.

What data does GC Analytics show?

GC Analytics focuses on two key levels of insight:

  1. Conversation-level data, which shows how conversations progress end-to-end. Examples include conversations started, completed, abandoned, failed, or handed off to agents.
  2. Block-level data, which shows how individual blocks perform inside a flow. Examples include drop-off blocks, most visited blocks, Jump block usage, and webhook triggers.

Together, these insights help you understand how conversations progress, where users drop off, and how individual blocks perform so you can identify areas for improvement.

Dashboard overview



The GC Analytics dashboard is organized into metric cards, charts, and detailed reports. All data responds to your selected filters such as date range, channel, language, and flow version.

At the top of the dashboard, you can:

  1. Select a date range.
  2. Refresh metrics.
  3. Export reports to access complete or historical data.

Key metrics you should monitor

Each metric below explains exactly what is counted and how it should be interpreted.

Metric What it shows Why it matters
Total Conversations The total number of conversations initiated within the selected period, regardless of how they ended. Helps you understand overall usage and traffic to your flow.
Completed Conversations The number of conversations that reached the final block of the flow. Indicates how often users successfully complete the flow.
Abandoned Conversations The number of conversations exited before reaching the final block. Highlights friction points or confusing steps in the flow.
Average Conversation Duration The average time users spent in the conversation flow. Helps assess flow complexity and user effort.
Transferred to Agents The number of times the Transfer to Agent block was triggered in IM channels (Zoho Desk). Shows where human assistance is still required.
Conversation Failures Conversations that ended due to block-related errors or failures. Points to configuration or integration issues that need immediate attention.
Important
Transfer to Agent data is only captured when a published flow containing a Transfer to Agent block is associated with an IM channel in Zoho Desk. If you do not see this metric, verify that the block is enabled and the flow is published to an IM channel.

See also: Learn more about the Transfer to Agent block ↗

Track conversation growth and success over time in Dashboard.

This section helps you understand how conversations progress over time and where users succeed or drop off.

Conversation Volume Over Time

Shows how many conversations started within the selected date range. Use this to identify growth patterns, campaign impact, or seasonal spikes. This includes conversations initiated by customers across selected channels.



Completion vs Abandonment

Compares the number of completed conversations with abandoned conversations. This chart helps you understand whether changes to your flow are increasing successful completions or causing users to exit early. A healthy flow typically shows more completed conversations than abandoned ones.



Conversation Drop-Off Points

Shows the blocks where the highest number of conversations dropped off before completing the flow. These blocks are usually the first priority for improvement. Review the content, questions, and transitions in these blocks.



Most Visited Blocks

Shows the blocks most frequently triggered in the flow. Highly visited blocks often represent common customer needs. Make sure these blocks are clear, fast, and reliable. Even small improvements in these blocks can impact a large number of conversations.


Identify peak customer interaction times

Visitor Peak Activity Time

Shows the hourly distribution of conversations during the selected period. Each bar represents the number of conversations started during that hour. This helps you plan agent availability, schedule campaigns, and monitor traffic spikes. This is useful even for fully automated flows, especially during campaigns or high-traffic periods.


Jump block analytics

This section is relevant if your flows use Jump blocks to move users within or across flows.

Jump Block Activity

Gives visibility into how conversations move within and across flows using Jump blocks. This helps you understand complex flow paths and reuse patterns. This includes:

  1. Internal Jump Block Usage: Shows how many conversations moved between blocks within the same flow.
  2. Cross-Flow Jump Block Usage: Shows how many conversations moved from this flow to another flow.

Incoming Jump Block Activity

Shows the number of conversations that entered this flow through Jump blocks from other flows. Use this to understand which other flows rely on this flow and where users are entering it. Each row displays:

  1. Destination block in this flow.
  2. Source flow and block name.
  3. Total incoming conversations.
  4. Percentage of increase/decrease in the value compared with previous equivalent time period set in filter

Language and integration insights

This section helps you understand how users interact with your flow across languages and integrations.

Most Preferred Language

Shows the number of conversations handled in each language during the selected period. Languages are ordered by usage, with the most preferred language listed first. This metric responds to date, version, and channel filters, but not the language filter.



Webhook Triggers

Shows how many times each webhook was triggered during the selected period. This helps you monitor integrations and identify unusual spikes or drops in webhook usage. Sudden spikes or drops may indicate integration issues or changes in flow behavior.


Using filters effectively

Date filters

You can filter data using:

  1. Last 7 Days
  2. Last 1 Month
  3. Last 3 Months
  4. Last 1 Year
  5. Custom Dates

Important
Metrics older than three months may not displayed in the dashboard view due to data volume. Use Export Report to access complete historical data.

Jump block filters

Refine Jump block insights using:

  1. Number of Jumps (Maximum)
  2. Number of Jumps (Minimum)
  3. Rate of Increase
  4. Rate of Decrease

Webhook trigger filters

Analyze webhook usage with:

  1. Number of Triggers (Maximum)
  2. Number of Triggers (Minimum)
  3. Rate of Increase
  4. Rate of Decrease

Exporting reports

You can export analytics reports to download complete data or share insights with your team. Exporting is useful when:

  1. You need to access larger data.
  2. You want to share analytics with stakeholders outside the product.
  3. You want to perform deeper analysis using spreadsheets or BI tools.

Understanding exported report columns

When you export a report, the file contains columns that go beyond what the dashboard shows. The sections below explain every column in each report type.

Conversation and ticket information

GC Analytics provides conversation-level metrics such as the total number of sessions, completed sessions, and abandoned sessions. However, the exported analytics reports do not currently provide a mapping between individual conversation sessions and the ticket IDs created from those conversations.

When a ticket is created from a Guided Conversation, the ticket is created using the Zoho Desk Create Ticket API. The generated ticket ID and other ticket-related details are managed and stored in Zoho Desk.

Therefore, GC Analytics cannot currently generate or download a report that lists each conversation session together with the corresponding Zoho Desk ticket ID.
To retrieve ticket IDs and ticket-related details, use the ticket information available in Zoho Desk. If you need to maintain a conversation-to-ticket mapping, capture the required identifiers as part of your ticket-creation or integration workflow.

Session Report

This report shows conversation volume, outcomes, and duration broken down by language, flow version, and channel.

Column What it means
Language The language in which the conversation was conducted.
Version The published flow version that was active during the conversation.
Facebook Messenger / LINE / Instagram / WhatsApp / Telegram / Web Number of sessions on each channel for that language and version combination. Each channel appears as a separate column.
Total no. of session Total sessions across all channels for that language and version row.
Avg. duration taken to complete (mins) Average time in minutes a user spent in the flow before completing it. Only counts sessions that reached the final block.
Total No. of completed session Sessions where the user successfully reached the final block of the flow.
Total No. of abandoned session Sessions where the user exited before reaching the final block of the flow.


Session Activity Report

This report shows conversation volume distributed by hour and channel, useful for identifying peak usage times.

Column What it means
Hour The hour of the day (0–23) during which the sessions occurred.
Channel The channel on which the sessions took place — for example, Web, WhatsApp, or Instagram.
Sessions Number of sessions for that specific hour and channel combination.
Total Sessions (Hour) Total sessions across all channels during that hour of the day.
Avg Sessions Per Channel The average number of sessions per channel during that hour.

Blocks Report

This report aggregates block performance by type across the entire flow and includes cross-flow jump activity.

Column What it means
 Block Name
The name you assigned to the block in the flow builder.
Block Type The category of block — for example, Message, Jump, Webhook, or Question. Each row represents all blocks of that type in the flow.
Unique Visits Number of distinct conversations that passed through blocks of this type at least once. (Indicates the number visitors were redirected to another flow if a Jump block is used. 
Repeated Visits Number of times blocks of this type were revisited within the same conversation.
Drop Offs Number of conversations that exited the flow at a block of this type without completing.
Outgoing Jump Flow Name The destination flow name for outgoing jumps from blocks of this type. Displays a dash if not applicable.
Incoming Jump Flow Name The name of parent flow from which user is redirected from. Here, the current flow will be considered as destination. Displays a dash if not applicable.
Incoming Jump Count The total number of conversations that arrived in this flow from other flows via Jump blocks for this block type.

Understanding conversation failures

The Blocks Report provides block-level performance information, such as visits and drop-offs. However, it does not currently identify the exact block or technical reason that caused an individual conversation to fail.
A conversation can fail for several reasons, including:
  1. An Integration block failure
  2. A Webhook failure
  3. Network or connectivity issues
  4. The flow being disabled or deleted while a conversation is still in progress
  5. Other flow execution or configuration issues
GC Analytics currently does not provide detailed failure diagnostics or a downloadable report that identifies the exact failure reason for each individual conversation. If you are investigating failed conversations, review the relevant flow configuration, integrations, and webhooks involved in the flow.


Integration Report

This report shows how often each webhook or integration was triggered, broken down by channel.

Column What it means
Block Name Whether the trigger came from a Webhook block or an Integration block.
Web / WhatsApp / Instagram / Telegram / Messenger / Line Number of times the webhook or integration was triggered on each channel. Each channel appears as a separate column.
Total no. of Triggers Total trigger count across all channels for that service row.
Last Triggered The date and time the webhook or integration was most recently triggered. Use this to confirm the service is still active and responding.

Tips to get the most value from GC Analytics

  1. Review drop-off points after every flow update.
  2. Track completed conversations and agent transfers together.
  3. Use peak activity time to plan staffing.
  4. Compare metrics after publishing a new version.
  5. Fix block failures before optimizing content.
Tip
Always focus on what customers are trying to achieve, not just the numbers.

Troubleshooting the Transferred to Agents metric

If conversations are being transferred to agents but the Transferred to Agents metric does not show the expected count, verify that you are viewing the flow version that was live when the Transfer to Agent block was executed.

When troubleshooting a discrepancy:

  1. Check which flow version was published and active when the conversation was transferred.
  2. Select the same flow version in GC Analytics.
  3. Compare the Dashboard and Reports using the same flow version and applicable date and channel filters.
  4. If different flow versions are shown in the Dashboard and Reports, verify that they correspond to the version used when the transfer occurred.

This helps ensure that the transfer activity is being evaluated against the correct flow version.




Frequently Asked Questions

Q: Do I need to be a data expert to use GC Analytics?
A: No. The dashboard is designed for support managers, product owners, and analysts to quickly spot issues and make confident decisions without specialized data skills.
Q: Why can't I see data older than three months in the dashboard?
A: The dashboard view may not display metrics from the last three months due to data volume. To access older or complete historical data, use Export Report.
Q: What is the difference between conversation-level and block-level data?
A: Conversation-level data shows how conversations progress end-to-end (started, completed, abandoned, failed, or handed off). Block-level data shows how individual blocks perform inside a flow, such as drop-off blocks, most visited blocks, Jump block usage, and webhook triggers.
Q: Which blocks should I improve first?
A: Start with your Conversation Drop-Off Points — the blocks where the most conversations exit before completing the flow. Review the content, questions, and transitions in those blocks first.
Q: Is peak activity time useful if my flow is fully automated?
A: Yes. Even for fully automated flows, the hourly distribution helps you monitor traffic spikes and plan around campaigns and high-traffic periods.
Q: Does the language filter affect the Most Preferred Language metric?
A: No. The Most Preferred Language metric responds to date, version, and channel filters, but not the language filter.
Q: What does a sudden spike or drop in webhook triggers mean?
A: Sudden spikes or drops may indicate integration issues or changes in flow behavior, so they are worth investigating to confirm your backend actions are working as expected.
Q: Does exporting include all metrics?
A: Exporting provides the available analytics data for the selected filters, including the data available in the Session, Session Activity, Blocks, and Integration reports. However, exported reports do not currently include a mapping between individual conversation sessions and Zoho Desk ticket IDs or detailed failure reasons for individual conversations.
Q: Can I share GC Analytics with my team?
A: Yes. Exported reports can be shared with stakeholders who do not have access to the product.
Q: Can I identify which block caused a conversation failure?
A: Not currently. GC Analytics does not provide detailed failure diagnostics that identify the exact block or technical reason responsible for an individual conversation failure. The Blocks Report provides aggregate block-level information, such as visits and drop-offs, but it does not identify the root cause of individual conversation failures.