The Scenario
You are a sales coach at a fintech startup. You have been running call reviews in Gong for a full quarter — 200 scorecard submissions, 8 reps, across three skill categories: discovery, objection handling, and closing.
Now the quarterly coaching session is on Thursday. You need to walk in knowing which skill category scores lowest on average across the team, and which reps are dragging down which categories. Without that breakdown, the session is forty minutes of gut-feel conversation with no data behind it.
The slow version:
- Export scorecard data from Gong — if the export even includes scorecard detail
- Open the CSV, find the scored questions, figure out which ones map to which category
- Build a pivot table to average by category per rep
- Cross-reference which rep is below average in each category
- Format the output into something you can show in the meeting
- By Wednesday evening you have a half-finished analysis and a growing headache.
The fast version is one prompt before lunch.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your spreadsheet that reads Gong's scorecard API directly, so you do not have to build a pivot table by hand.
Open the SheetXAI sidebar and type:
Fetch all Gong scorecard submissions from January 1 to March 31 and paste them into this sheet with columns: reviewer, reviewed rep, call date, scorecard name, and each scored question with its value. Then for each scoring category, calculate the average score across all submissions and write a summary to a new sheet called "Category Averages" sorted from lowest to highest.
SheetXAI pulls the submissions, writes the raw detail into the active sheet, and builds the Category Averages tab — sorted so the weakest skill is at the top. You walk into Thursday's session knowing exactly where to start.
What You Get
Two populated tabs:
Main tab — one row per scorecard submission:
- Reviewer name, reviewed rep name, call date, scorecard name
- One column per scored question with its numeric value
Category Averages tab — one row per skill category:
- Category name and average score across all 200 submissions, sorted lowest to highest
The sort is the finding. If objection handling averages 2.4 out of 5 and closing averages 4.1, you spend Thursday on objection handling. You did not need to calculate that — SheetXAI did.
What If the Data Is Not Quite Ready
Scorecard data from coaching tools is often inconsistent — questions get renamed, new categories get added mid-quarter, some reps have far more reviews than others.
When scorecard question names changed mid-quarter
Someone renamed "Discovery Quality" to "Discovery" halfway through Q1. Your averages table has two separate rows for what is really one category.
Fetch all Gong scorecard submissions for Q1. Normalize question names so that "Discovery Quality," "Discovery," and "Disc." are all treated as "Discovery" before calculating category averages. Write the normalized raw data to the main sheet and the averaged summary to a new "Category Averages" tab sorted ascending.
When you want per-rep breakdowns, not just team averages
Team averages tell you where the gap is. Per-rep breakdowns tell you who owns it.
Fetch Gong scorecard submissions for Q1. For each rep, calculate their average score per category. Write results to a new tab called "Rep x Category" with one row per rep and one column per category. Highlight cells below 3.0 in red.
When some reps have far more reviews than others
A rep with 40 reviews and a rep with 5 reviews should not carry equal weight in the team average.
Fetch Gong scorecard submissions for Q1. Calculate weighted category averages — weight each rep's contribution by their number of submissions so reps with more reviews carry more weight. Write the weighted averages to a "Category Averages" tab sorted ascending, and include a column showing how many submissions went into each rep's score.
When you want the full setup: raw data, category averages, per-rep breakdown, and coaching priorities in one go
No pre-built sheets, just the blank workbook and a Thursday meeting to prepare for.
Fetch all Gong scorecard submissions from Q1. Write the raw submission detail to a "Raw Scorecards" tab. Calculate team-level category averages and write them to a "Category Averages" tab sorted from lowest to highest. Calculate per-rep averages by category and write them to a "Rep x Category" tab, highlighting cells below 3.0 in red. Finally, in cell A1 of "Category Averages," write one sentence naming the weakest category and the two reps with the lowest scores in it.
The pattern: the pull, the aggregation, the rep-level breakdown, and the coaching callout are all one ask. You get the full picture before lunch.
Try It
Get the 7-day free trial of SheetXAI and open a blank sheet, then ask it to pull your team's Gong scorecard data for any date range. The Gong integration is included in every SheetXAI plan. For related workflows, see how to compare manager coaching activity across your team or the Gong in Google Sheets overview.