The Scenario
You're a sales ops analyst. Overnight, 500 new inbound leads landed in the sheet from the latest webinar. Your job this morning is to run them against the existing 2,000-row customer list before the SDRs start dialing — because calling an existing customer and treating them like a cold lead is a fast way to a complaint.
The problem: the webinar form collected "Acme Solutions" while your CRM has "Acme Solutions Inc." The names don't match, so a VLOOKUP returns nothing and the SDR dials anyway.
The bad version:
- Sort both tabs alphabetically, open them side by side, and eyeball 500 names against 2,000 — a process you've done before and which takes three hours and still misses transposed words.
- Write a formula combining SEARCH and IFERROR to find partial matches, which fires on too many false positives to be useful.
- Ask the dev team to run a fuzzy match script — they'll get to it after their current sprint, which ends in two weeks.
The SDRs start calling at 9 AM. It's 8:15.
The Easy Way: One Prompt in SheetXAI
SheetXAI reads both tabs of your Google Sheet and calls Interzoid's organization match score endpoint to compare names across them.
For each prospect name in column A, compare it against every customer name in Sheet2 using Interzoid's org match score and write the best-matching customer name and its score into columns B and C.
What You Get
- Column B: the closest matching customer name from Sheet2 for each prospect.
- Column C: the similarity score (1-99) for that match.
- Any prospect scoring above 80 flagged automatically for review before the SDR call list is finalized.
- Rows with no close match left blank in column B so the SDR team knows which are genuinely new.
What If the Data Is Not Quite Ready
Column A has inconsistent formatting — some names are all caps, some include domain
Before comparing, strip domain suffixes and normalize casing for all names in column A, then run the Interzoid match score against Sheet2 and write results to columns B and C.
You want to score in both directions — prospect vs. customer and customer vs. prospect
Take the name pairs in columns A and B and use Interzoid to score their similarity, writing the score to column C and marking any row above 80 as a likely duplicate.
The customer list in Sheet2 is itself dirty — some names are blank
Before matching, filter Sheet2 to rows where column A is not blank, then compare each prospect in Sheet1 column A against that filtered list and write the best match and score to columns B and C.
Full dedup workflow in one pass
For each prospect in Sheet1 column A: compare against Sheet2 using Interzoid org match score, write the best matching customer name to column B and the score to column C, then flag rows where column C exceeds 75 as 'LIKELY EXISTING' in column D and sort descending by column C.
The SDRs get a clean call list. The likely-existing accounts get routed to account management instead.
Try It
Get the 7-day free trial of SheetXAI and open your Google Sheet with both the prospect list and customer roster — ask SheetXAI to cross-check column A against your existing accounts before the morning call list goes out. Then see the spoke on deduplicating company names by match key or the full Interzoid overview.