The Scenario
You run sales enablement for a mid-size SaaS company. Every week you pull a call coaching report for the team's Monday session. Your process: log into Specific, filter conversations by date range, export what you can, clean the CSV in Sheets, then format a table with company name, contact email, call source, and date. It is Friday at 4 PM. The coaching session is Monday at 9 AM.
The bad version:
- You log into Specific and navigate to the conversations view. The export button gives you a CSV with column names that don't match what your coaching template expects — 'created_at' instead of 'created_date', 'source_type' instead of 'source'.
- You open the CSV in Sheets, rename the columns, sort by date descending, and filter for the 20 most recent records. Three rows are missing company names because the conversations weren't linked to a company at call time.
- You spend 20 minutes looking up the missing companies manually in Specific. Your coaching template is built around 20 rows; you have 17 usable ones. You adjust the session plan. Again.
You are supposed to be building coaching content, not wrestling with export column names on a Friday afternoon.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It reads the sheet, connects to Specific through the built-in integration, and can pull conversation records directly into the sheet — already shaped the way your template expects them. No CSV download, no column rename, no manual company lookup.
Fetch the most recent conversations from Specific and write conversation_id, contact_email, company_name, source, and created_date into this sheet — one row per conversation
What You Get
- Up to 20 (or however many you specify) recent conversations pulled from Specific and written into the sheet starting at row 2.
- Columns populated with conversation_id, contact_email, company_name, source, and created_date — using the field names you asked for, not Specific's internal names.
- Rows where company_name is absent marked with a blank or a placeholder so you can see which conversations lacked company linkage at call time.
- No CSV intermediary, no reformatting step.
What If the Data Is Not Quite Ready
You need conversations filtered by a specific date range
Fetch all Specific conversations created between 2026-05-01 and 2026-05-14 and write conversation_id, contact_email, company_name, source, and created_date into this sheet — one row per conversation, sorted by created_date descending
Some conversations are missing company associations
Fetch the 20 most recent Specific conversations and write conversation_id, contact_email, company_name, source, and created_date into columns A through E — for any row where company_name is missing, write 'UNLINKED' in column F so they can be reviewed separately
You only want conversations from a specific source
Fetch all Specific conversations where source is 'inbound' and write conversation_id, contact_email, company_name, and created_date into this sheet — limit to 30 rows, sorted by created_date descending
Full pull-and-format in one shot
Fetch the 20 most recent Specific conversations, write conversation_id (A), contact_email (B), company_name (C), source (D), and created_date (E) into this sheet, sort by created_date descending, flag rows with missing company_name as 'UNLINKED' in column F, and flag rows from source 'outbound' as 'OUTBOUND' in column G
Pull the data, apply the flags, and have the coaching report ready before you close the laptop.
Try It
Get the 7-day free trial of SheetXAI and open any Google Sheet you use for call coaching — then ask it to pull the most recent Specific conversations directly into the sheet, already formatted for your review. See also how to audit your company records or export all contacts for a hygiene check.