How do I find out which trade show attendees are already in my CRM?

Export your existing CRM contacts, then compare your event export against that export using fuzzy matching on name and company together. Email-only comparison misses most existing contacts in event exports because email is frequently missing or inconsistent. A tool like Clean by Similarity API compares both files and flags which attendees likely already exist in your CRM before anything gets imported.

Why does importing a trade show list create duplicate contacts in HubSpot?

HubSpot deduplicates contacts on email address only. If a contact in your event export has no email, a different email than what's in HubSpot, or any variation in their email address, HubSpot creates a new record. This is expected behavior — HubSpot has no way to match on name similarity. Comparing your list against a HubSpot export using fuzzy matching before importing is the only way to catch these before they become duplicates.

What percentage of trade show leads are typically already in a CRM?

It varies significantly by event and company maturity, but for companies that have been doing events for several years, 20–40% of badge scans at industry-specific conferences are often existing contacts. Broad consumer events tend to have lower overlap. If you're attending the same conference repeatedly, overlap increases each year.

How do I handle trade show contacts who have no email address?

Fuzzy match them against your CRM export on name and company. Contacts without email are the primary reason email-only matching fails for event exports — they're exactly the records that create new duplicates on import. If the fuzzy match finds a likely existing contact, verify manually and update the existing record rather than importing a new one. If no match is found, import them as new contacts but note the missing email field.

Should I import trade show leads immediately after an event?

Only after comparing against your existing CRM data first. Importing immediately without checking overlap creates duplicates that are time-consuming to fix after the fact. The pre-import comparison takes 20–30 minutes and prevents hours of cleanup. If speed matters, import the net-new contacts immediately and handle the matched group separately with appropriate follow-up sequencing.

Can I do this comparison inside HubSpot or Salesforce directly?

Not with fuzzy matching. Both CRMs let you upload a list and check for matches on email address or Record ID — but not on name or company similarity. To catch name variants and contacts without matching emails, you need to compare the files outside the CRM using a fuzzy matching tool, then import only the net-new records.

How to Find Net-New Contacts from a Trade Show Lead List

Quick answer: Export your existing CRM contacts, then compare your trade show list against that export using fuzzy matching on name and company together. Email-only comparison misses contacts with no email in the event export, contacts who gave a different email at the event, and name variants. The result tells you which attendees are net-new, which already exist in your CRM, and which need manual review.

You just got back from a trade show with 300 badge scans. Some of those people are existing customers. Some are active prospects already in your pipeline. Some filled out a form on your website last year and are already in your CRM under a slightly different email or name. And some are genuinely new — people your team has never spoken to before.

Importing all 300 without checking creates a mess: duplicate records, reps reaching out to existing customers with "introductory" messaging, inflated lead counts in your pipeline reporting, and marketing campaigns that treat known customers as cold prospects.

The alternative takes about 20 minutes and tells you exactly which leads are net-new before anything touches your CRM.

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Why Badge Scans Are Hard to Deduplicate

Trade show exports are harder to match against CRM data than other list types for a few specific reasons.

Email is often missing or unreliable. Badge scanners capture whatever is on the conference badge — typically first name, last name, company, and job title. Email is frequently absent, or is a generic company address rather than the person's actual email. HubSpot deduplicates contacts on email address only. Salesforce deduplicates on email or Record ID. Without a matching email, both CRMs create a new record regardless of whether the person already exists.

Company names are inconsistent. Conference badges are filled out by attendees, not standardized by a data team. Your CRM might have "Salesforce" and the badge says "Salesforce.com, Inc." Your CRM has "3M" and the badge says "3M Company." These are the same companies — but an exact-match comparison treats them as different.

Names vary. Someone who submitted a demo request as "Jennifer Walsh" may have registered for the conference as "Jen Walsh." Your CRM has one version, the badge export has the other. No exact match.

You've met these people before. Every recurring conference has repeat attendees. People who attended last year, filled out your form, talked to a rep, are already fully in your CRM — and their badge just got scanned again.

The Standard Approach — and Where It Breaks

Most teams either import everything and clean up after, or try to VLOOKUP the event export against a CRM export on email address.

Import everything first: Creates duplicates immediately. You'll find them in HubSpot's Manage Duplicates tool or Salesforce's duplicate report — but merging them after the fact is slow, records split activity history across two contacts, and it requires someone to manually review each pair.

VLOOKUP on email: Only catches records where both files have the same email address. Everyone without an email in the event export, and everyone whose email differs between the two sources, appears as a non-match and gets imported as a new record. In a typical trade show export, this misses 30–60% of the actual existing contacts.

How to Do This Properly

Step 1: Export your CRM contacts

Pull a full export of your existing contacts including first name, last name, company name, and email. From HubSpot: Contacts → Actions → Export. From Salesforce: Reports → New Report → Contacts. Save as CSV.

Step 2: Prepare your trade show export

Make sure it has separate columns for first name, last name, and company. If the export gives you a single "Name" field, split it before comparing — "John Smith" in one column is much easier to work with than the full string.

Step 3: Run a fuzzy match across both files

Upload both files to a comparison tool that supports fuzzy matching across multiple columns. Clean by Similarity API lets you upload two files, select matching columns in each, and returns three groups:

Matched — attendees who likely already exist in your CRM
Net-new — attendees with no close match in your CRM
Similarity scores — so you can review borderline matches before deciding

Match on first name + last name + company name together, not email alone. The combined signal is what catches "Jen Walsh at Acme Corp" matching "Jennifer Walsh at Acme Corporation" in your CRM — neither the name nor the company matches exactly on its own, but together they're clearly the same person.

Step 4: Review the matched group

For records the tool flagged as likely existing, verify before deciding what to do:

High confidence match (score > 0.85): Skip on import. If the trade show export has fresher information (new job title, direct number), update the existing CRM record manually or via a targeted import using the Record ID.
Medium confidence (0.70–0.85): Review manually. Could be the same person with an unusual name variant, or two different people at the same company with similar names.

Step 5: Import only net-new records

Take the net-new group and import it as your actual new leads. These are the people worth the introductory outreach — the ones your team genuinely hasn't spoken to.

What to Do With the Matched Group

Finding out that 80 of your 300 badge scans already exist in your CRM isn't wasted effort — it's useful information.

Existing customers who attended: They should receive a "great to see you at [event]" follow-up, not an introduction to your company. Routing them correctly prevents an embarrassing interaction.
Active prospects already in pipeline: The rep who owns that account should know they attended. Add a note or activity to the existing record rather than creating a new lead. The scan is engagement data, not a new lead.
Contacts you haven't spoken to in a while: They're in your CRM but cold. The event attendance is a reactivation trigger — worth a different message than either a cold intro or an existing customer follow-up.

Separating these groups before import means each one gets routed correctly from the start.

Key Takeaways

Badge scanner exports are harder to match against CRM data than most list types — email is often missing, company names are inconsistent, and name variants are common
Email-only comparison misses 30–60% of existing contacts in a typical trade show export
Fuzzy matching on name and company together catches the variants that exact-match tools miss
Separating net-new from existing attendees before import prevents duplicates, incorrect routing, and embarrassing outreach to existing customers
The matched group isn't wasted — it's segmentation data that determines what follow-up each person should receive