What causes mismatch between HubSpot and Dedupely duplicates

The duplicate count doesn’t match, here’s why

If you’re seeing fewer duplicates in Dedupely than in HubSpot, don't worry: It’s not a bug, it’s a matter of scope. Dedupely follows your rules exactly, and HubSpot uses internal logic that isn’t visible or configurable. Unless your match logic and merge rules setup mimics that logic, the results won’t align.

The match count depends on how you define a duplicate, not how another tool flags it. To resolve the gap, start by reviewing your match logic, not your sync status.

What Dedupely actually looks at

Dedupely checks exactly what you tell it to. You can define this using Search Pads with specific per-field match options, which include:

• Fields to compare, like First Name, Last Name, Email, Company Name, and custom fields
• A match option for each field, like Exact match, Similar match, Fuzzy match, Similar Words (Any Order) match, or Domain Root match

If a duplicate doesn't match exactly as you set your Search Pad, it is excluded, as there is no partial logic. This means the quality of your match results depends entirely on which fields you include and how you match them. Don’t rely on default setups; review every field and match option being used.

More on Search Pads here.

Learn how to build a Search Pad system to find all your duplicates with this guide.

Exact match conditions may limit what shows up

Matching Phone Numbers or First Names using Exact match often blocks valid duplicates, but consider that formatting differences alone can break the match. For example:

• “+1 555-123-4567” and “5551234567” will not match under Exact match
• “Horizon Labs Inc.” and “Horizon Labs Incorporated” will not match, even if they refer to the same entity

If you want more accurate detection, try Similar match where formatting or minor variation is expected. This includes Phone Numbers, Names, and, in some cases, Emails.

Tip: In Dedupely, you can test match options by cloning a Search Pad, changing one field from Exact to any other match, and running the scan again. The difference in results is usually immediate.

How to evaluate match results after a change

After running a scan with updated match logic, check what kinds of records are being matched

Look for patterns in the new matches:

• Are the duplicates real, or just similar?
• Are certain values triggering noise (like partial company names or reused emails)?
• Are blanks causing weaker matches than intended?

Use this review to decide whether to keep the change, adjust the match options, or add another field for balance. Iteration is about the quality of matched duplicates.

What you control, you can trust

The strength of Dedupely lies in its precise reflection of your match logic.

If you want more matches, be lenient with your match options. If you want thorough control, sharpen them. Either way, you define what qualifies as a duplicate. That clarity gives you results you can explain, troubleshoot, and improve, without guessing.