The Scenario
The sales ops lead pulled 800 2Chat contacts into Excel last week and dropped them in a shared workbook — phone, name, creation date. The same workbook already has a CRM export on Sheet2: account name, phone, last purchase date, deal stage. Someone in leadership wants to know which 2Chat contacts haven't made a purchase in 90 days and whether they're still active deals. The quarterly review is Friday.
The bad version:
- Try to VLOOKUP the 2Chat phones against the CRM phones — realize the formats don't match (2Chat stores +1XXXXXXXXXX, CRM stores it as (XXX) XXX-XXXX), and the formula returns nothing.
- Normalize both columns manually, fix the VLOOKUP, start matching rows.
- Find that 200 entries in the CRM have no phone at all — they were matched by email, which isn't in the 2Chat export.
- Build the 90-day filter by hand, then start flagging active vs. inactive deals one by one.
The quarterly review is Friday. This is a Thursday afternoon job if you do it manually. Nobody on this team has a Thursday afternoon to spare.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Excel workbook. It reads both sheets, joins the data on phone number after normalizing both sides, and writes the enriched result — no manual VLOOKUP, no format-fixing required.
Sheet1 has my 2Chat contacts exported: name in column A, phone in column B, creation date in column C. Sheet2 has CRM data: account name in column A, phone in column B, last purchase date in column C, deal stage in column D. Match each 2Chat contact to the CRM row with the same phone number (normalize both sides to E.164 before matching). Write the last purchase date to column D and deal stage to column E on Sheet1. Flag column F with "no match" for any 2Chat contact with no CRM entry.
What You Get
- Sheet1 enriched with last purchase date in column D and deal stage in column E for every row that matched a CRM record.
- Column F flagged "no match" for 2Chat contacts with no corresponding CRM entry.
- Phone normalization applied before matching, so format differences don't produce false negatives.
- No manual VLOOKUP, no format-fixing, no row-by-row comparison.
What If the Data Is Not Quite Ready
CRM phone numbers are formatted with dashes and parentheses
Before matching, normalize the phones in Sheet1 column B and Sheet2 column B to E.164 format. Then join on the normalized phone and write last purchase date to Sheet1 column D and deal stage to column E.
I need to flag contacts who haven't purchased in 90 days
After enriching Sheet1 with last purchase dates from Sheet2, add a column F that flags any contact whose last purchase date is more than 90 days before today as "re-engage" and any with no purchase date as "unknown." Leave column F blank for recent purchasers.
Some 2Chat contacts appear multiple times in the CRM
When matching 2Chat contacts to CRM rows by phone, if a phone appears more than once in Sheet2, use the row with the most recent last purchase date. Write that date and deal stage to Sheet1 and add a note in column G: "multiple CRM records — most recent used."
Full cleanup, join, flag, and summary in one shot
Normalize all phones in Sheet1 and Sheet2 to E.164. Join Sheet1 to Sheet2 on phone — where duplicates exist in Sheet2, use the most recent purchase. Write last purchase date to Sheet1 column D, deal stage to column E. Flag column F: "re-engage" if last purchase > 90 days ago, "unknown" if no purchase date, "no match" if no CRM entry. Then create a "Summary" sheet with counts for each flag value and a breakdown of no-match contacts by their 2Chat creation date month.
That's the quarterly review output. One prompt instead of a Thursday afternoon.
Try It
Get the 7-day free trial of SheetXAI and open the Excel workbook where your 2Chat export and CRM data both live, then ask it to join them by phone and surface the gaps. Related workflows: Export Your 2Chat Contacts Into a Google Sheet and the 2Chat integration overview.