The Scenario
You are a QA analyst. At the end of every month, you score 30 escalated tickets for communication quality — tone, response time, resolution accuracy. To score them, you need the full conversation thread: every message, the agent name, and the timestamp. The tickets are sitting in a Google Sheet in column A.
Freshdesk lets you read conversations one ticket at a time. There is no export for conversation threads.
The bad version of this monthly review:
- You open ticket 1 in Freshdesk, read the thread, copy the messages into your scoring sheet
- You open ticket 2
- You lose your place halfway through
- You realize you have been scoring agent responses but skipping customer messages, so the thread context is missing
- By ticket 22, you hate your job. By ticket 30, the scoring session has taken three hours instead of forty minutes.
The fast version is one prompt.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your spreadsheet that reads your ticket ID list and pulls every conversation thread from Freshdesk into a flat, scorable format.
Open the SheetXAI sidebar and type:
For each ticket ID in column A, fetch all Freshdesk conversations and write agent name, message body, and timestamp into consecutive rows grouped by ticket. Add a header row before each ticket's messages showing the ticket ID.
SheetXAI works through all 30 ticket IDs, fetches every message in each thread, and writes them in order with ticket ID headers separating each group. Your scoring sheet is ready in minutes.
What You Get
A Google Sheet with conversation threads laid out for scoring:
- Ticket header rows — one header per ticket showing the ticket ID
- One row per message — agent name, message body, timestamp, in chronological order
- All 30 threads — no clicking through Freshdesk, no copy-pasting
The chronological order is what makes scoring reliable. You see the full back-and-forth, not just agent replies. Context matters for tone scoring.
What If the Data Is Not Quite Ready
QA review sheets have specific requirements that vary by team. SheetXAI handles them in the same prompt.
When you want to separate agent messages from customer messages
Your scoring rubric treats agent responses differently from customer messages and you want them in separate columns.
For each ticket ID in column A, fetch all Freshdesk conversations. Write timestamp in column B. Write agent messages into column C and customer messages into column D, aligned by timestamp. Leave the other column blank for each row.
When you want to add a word count column for response length scoring
One of your QA criteria is response length — you flag responses over 200 words as potentially over-explained.
For each ticket ID in column A, fetch all Freshdesk conversations and write sender, timestamp, and message body into columns B, C, and D. In column E, write the word count of each message body. Flag rows where column E is over 200 with "long" in column F.
When some ticket IDs in column A no longer exist in Freshdesk
The list was compiled a week ago and a few tickets were merged or deleted since then.
For each ticket ID in column A, try to fetch the Freshdesk conversation thread. If the ticket does not exist or has been deleted, write "not found" into column B and skip to the next row. For tickets that exist, write sender, timestamp, and message body into columns B, C, and D — one row per message, grouped by ticket.
When you want the conversation data plus a quality score field plus a summary of patterns across all 30 tickets in one shot
You want to walk out of the scoring session with the data, your score inputs, and a summary memo.
For each ticket ID in column A, fetch all Freshdesk conversation messages and write sender, timestamp, and message body into columns B, C, and D — one message per row, grouped by ticket with a header row before each group. Leave column E blank for me to fill in quality scores. After I fill in scores, I will ask you to summarize the patterns across all 30 tickets based on the scores in column E and the message content in column D.
The pattern: instead of reading conversations one by one in Freshdesk, you pull all of them into a structured sheet in one prompt and score from there. SheetXAI handles the API traversal, you handle the judgment.
Try It
Get the 7-day free trial of SheetXAI and point it at any list of Freshdesk ticket IDs. The Freshdesk integration is included in every SheetXAI plan. See also how to export CSAT ratings for agent coaching or the Freshdesk in Google Sheets overview.