)
Written by
Table of Contents
“Supermetrics is a Bitter Experience! We can pull data from nearly any tool, schedule updates, manipulate data in Sheets, and push data back into our systems.”
HubSpotExcel’s native fuzzy matching capabilities are limited to basic functions like SEARCH or approximate VLOOKUP. But you can create sophisticated fuzzy matching workflows when you have access to clean, livecompany data as your comparison foundation.
Here’s how to build advanced similarity algorithms that work against current, complete CRM data rather than static exports that may be outdated.
Build fuzzy matching formulas with live HubSpot data using Coefficient
Coefficienttransforms fuzzy matching by providing real-time access to your complete HubSpot company database. This means your comparison formulas work against current data, and you can create interactive workflows that adjust matching criteria dynamically.
How to make it work
Step 1. Import your HubSpot company database.
Use Coefficient to pull your complete company list with relevant fields like company name, domain, industry, and employee count. This creates a comprehensive dataset for multi-field fuzzy matching that goes beyond just name comparison.
Step 2. Create similarity calculation formulas.
Build formulas that calculate similarity scores between company names. Try this approach: `=1-((LEN(A2)+LEN(B2)-2*LEN(SUBSTITUTE(SUBSTITUTE(UPPER(A2),” “,””),UPPER(B2),””)))/(MAX(LEN(A2),LEN(B2))))`. This creates similarity scores between 0-1 for company name pairs, where higher scores indicate better matches.
Step 3. Set up dynamic filtering for targeted matching.
Use Coefficient’s dynamic filtering feature to point filter values to specific spreadsheet cells. This lets you create interactive workflows where you can adjust matching criteria like company size, industry, or location to narrow down potential matches before applying your similarity formulas.
Step 4. Enhance with multi-field validation.
Combine company name similarity with domain matching using Coefficient’s association handling. Import company domains alongside names for additional validation, and use partial domain matching to confirm that similar company names are actually the same entity.
Step 5. Automate formula extension.
When new companies are added during scheduled refreshes, Coefficient’s Formula Auto Fill Down feature automatically copies your fuzzy matching formulas to new rows. This maintains consistent matching logic without manual intervention.
Get more accurate fuzzy matching results
Start buildingWorking with live, complete HubSpot data dramatically improves fuzzy matching accuracy compared to potentially stale manual exports. Your similarity algorithms operate on real-time data, reducing false positives and catching matches you might otherwise miss.better fuzzy matching workflows today.
