The Scenario
You are a support director. Q2 just ended and you have a coaching session scheduled for next Tuesday with your five lowest-performing agents based on customer satisfaction. The problem: you have not pulled the CSAT data yet, and Freshdesk's built-in reporting does not export in a shape that makes per-agent averages easy to calculate.
The bad version of this Friday afternoon:
- You navigate to Freshdesk's satisfaction reports section
- You click Export and get a flat CSV with one row per survey response
- You open it in Google Sheets and pivot it manually by agent name
- You realize agent names have inconsistent spellings across the export
- You spend two hours cleaning and aggregating
- You go into Tuesday's session with a messy spreadsheet and three agents who actually do not belong in the room.
The fast version is one prompt.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your spreadsheet that pulls CSAT data from Freshdesk and computes the analysis you need in one pass.
Open the SheetXAI sidebar and type:
Fetch all Freshdesk satisfaction ratings submitted in the last 90 days and write ticket ID, rating, agent name, and submitted date into columns A through D. Below the data, add a summary table showing average CSAT score per agent sorted from lowest to highest. Identify the 5 lowest-rated tickets overall and list them in a separate section with ticket ID, agent name, and rating.
SheetXAI pulls the responses, writes the flat data, computes the per-agent averages, and builds the coaching shortlist — all in the same prompt.
What You Get
A Google Sheet with three sections:
- Raw CSAT data — ticket ID, rating, agent name, submitted date — one row per survey response
- Per-agent summary table — average score per agent, sorted lowest to highest, so you can see the full picture at a glance
- Bottom 5 tickets — specific tickets with ticket ID, agent name, and rating — the conversations you will review in the coaching session
The sorted summary is what makes the meeting preparation fast. You are not looking at a flat list trying to mentally average by agent. The worst performers are at the top.
What If the Data Is Not Quite Ready
Real CSAT exports from Freshdesk have quirks. SheetXAI handles them in the same prompt.
When agent names have inconsistent spellings
Some responses logged the agent as "J. Smith" and others as "John Smith" because of how different ticket sources capture the display name.
Fetch all Freshdesk CSAT ratings from the last 90 days. Normalize agent names in column C — treat "J. Smith" and "John Smith" as the same person. Write the normalized name back into column C. Then build the per-agent average table below using the normalized names.
When you want to split CSAT by product area using ticket tags
Your team handles two product lines and you want to know if CSAT differs between them.
Fetch all Freshdesk CSAT ratings from Q2. For each rating, also pull the tags on the associated ticket. Write ticket ID, rating, agent name, submitted date, and tags into columns A through E. Below the data, build two summary tables: one for tickets tagged "product-line-A" and one for tickets tagged "product-line-B", each showing per-agent average sorted lowest to highest.
When you only want ratings for tickets that were first-response resolved
Part of your coaching framework only looks at tickets resolved in a single reply. You want to filter to those tickets before calculating agent averages.
Fetch all Freshdesk CSAT ratings from the last 90 days. For each, check if the associated ticket had only one reply before being resolved. Include only those tickets in the analysis. Write ticket ID, rating, agent name, and submitted date into columns A through D, then add the per-agent average summary below.
When you want the full quality picture — CSAT plus response time plus ticket volume — in one table
You want a combined agent scorecard, not just CSAT.
Fetch all Freshdesk CSAT ratings from Q2. For each agent, calculate: average CSAT score, average first response time (in hours) from the associated tickets, and total ticket volume. Write a summary table with one row per agent showing those three metrics, sorted by CSAT ascending. This is for a coaching session, so put the lowest performers first.
The pattern: instead of exporting raw data and building the analysis in a second step, you ask for both in one prompt. SheetXAI pulls the Freshdesk API data and runs the aggregation inline.
Try It
Get the 7-day free trial of SheetXAI and open a blank Google Sheet, then ask it to pull your Q2 CSAT data and build the agent summary. The Freshdesk integration is included in every SheetXAI plan. See also how to export ticket conversations for QA review or the Freshdesk in Google Sheets overview.