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Data Cleaning for Event Registration Lists: How to Deduplicate, Validate and Standardise Attendee Data from Eventbrite, Cvent, Splash, Hopin, Registration Spreadsheets and Walk-in Sign-up Sheets By Email Extractor Published October 10, 2026 6 min read
event registration data cleaning deduplication attendee data event management
On this page Event Registration Data Challenges
Event registration data is among the messiest data any organisation handles. Attendees register through multiple channels (website, email, phone, walk-in), use different email addresses for different registrations, misspell their own information and change details after registering. Event organisers need clean data for badge printing, session capacity planning, post-event follow-up, sponsor lead delivery and attendee analytics:
Data problem
How it happens
Impact
Duplicate registrations
Attendee registers twice (different browser sessions, confirmation email did not arrive, registered through group and individually)
Double badge printing; double catering count; double charge; inflated attendance numbers
Email typos
Attendee types "gmial.com" instead of "gmail.com"; transposes letters; omits domain extension
Confirmation email bounces; attendee does not receive event details; post-event follow-up fails
Multiple email addresses
Attendee registers for conference with work email, registers for social event with personal email
Two separate records for one person; duplicate outreach; inaccurate unique attendee count
Name inconsistencies
"Bob Smith", "Robert Smith", "R. Smith", "Bob Smth" (typo) across different registrations
Badge printing errors; check-in confusion; CRM matching failures
Company name variations
"IBM", "I.B.M.", "International Business Machines", "IBM Corp.", "IBM Corporation"
Sponsor lead reports overcount unique companies; group registration matching fails
Registration status confusion
Registered, cancelled, transferred, waitlisted, checked-in, no-show across different systems
Cancelled attendees receive event communications; no-shows counted as attendees
Multi-source data
Eventbrite (CSV), Cvent (XLSX), Splash (CSV), Hopin (CSV), walk-in sheets (XLSX), sponsor registrations (CSV), speaker registrations (manual), VIP list (email)
Different column names, formats and data structures; no single source of truth
Data Cleaning Workflow
Step 1: Collect all registration sources
Source
Export format
Typical fields
Common issues
Eventbrite
CSV
Order #, First Name, Last Name, Email, Ticket Type, Order Date
Multiple orders per person; email in "Attendee" row not "Buyer" row
Cvent
XLSX or CSV
Registration ID, First, Last, Email, Status, Registration Type, Company
Multiple registration types (attendee, exhibitor, speaker) in separate exports
Splash
CSV
First Name, Last Name, Email, RSVP Status, Check-in Status
RSVP'd vs. checked-in discrepancy; walk-in registrations added manually
Hopin
CSV
Name, Email, Ticket Type, Registration Date, Check-in
Online and hybrid events; virtual attendance data separate from in-person
Walk-in sign-up sheets
XLSX (transcribed)
Name, Email, Company (handwritten, then transcribed)
Handwriting legibility; incomplete fields; missing email; typos in transcription
Sponsor registrations
CSV or XLSX
Sponsor company provides list of their attendees; format varies
No standard format; may include non-attendees; company employees, not all attendees
Speaker / VIP list
Email or XLSX
Manually compiled by event team
Informal; may use personal emails; status unclear (confirmed vs. invited)
Group registrations
CSV or manual
One contact registers multiple attendees; individual attendee data may be incomplete
Group contact email appears on all records; individual attendee emails may be missing
Step 2: Extract and deduplicate email addresses
Upload all registration files to Email Extractor . The tool:
Processes each file regardless of format (CSV, XLSX, TXT, HTML)
Extracts every email address from every field in every file
Deduplicates case-insensitively (bob@example.com and Bob@Example.com become one entry)
Presents the unique list for download
Download results as "CSV with sources" to see which registration source each email came from. This helps identify:
Emails that appear in multiple sources (registered through multiple channels)
Emails that appear only in walk-in data (not pre-registered)
Emails from sponsor lists that do not appear in main registration (sponsor-only attendees)
Step 3: Identify and fix common email issues
Issue
How to identify
How to fix
Domain typos
Sort by domain; look for "gmial.com", "gnail.com", "yahooo.com", "outlok.com", "hotmal.com"
Correct obvious domain misspellings to the correct domain
Missing TLD
Emails ending in "@gmail" or "@company" without .com/.org/.net
Append the most likely TLD (usually .com for consumer domains)
Role-based addresses
info@, admin@, office@, sales@, support@
Flag as likely not personal attendee addresses; may be group registration contact
Disposable addresses
Domains known as temporary email providers
Flag for verification; attendee may not receive follow-up
Internal test registrations
Event team's own email addresses used for testing
Remove from attendee count and follow-up lists
Duplicate with variation
john.smith@example.com and johnsmith@example.com May be different people at the same company or may be the same person; flag for manual review
Step 4: Reconcile across sources
After extracting unique email addresses, reconcile with the original registration data:
Task
Method
Purpose
Match emails back to full records
Use email as the key to match deduplicated list against original registration files
Each unique email gets one master record with the most complete name, company and registration data
Resolve conflicting data
When the same email has different names or companies across sources, use the most recent or most complete record
Accurate badge printing and sponsor reports
Identify unmatched registrations
Registrations with no valid email (walk-ins with illegible handwriting, group registrations without individual emails)
Flag for manual follow-up to collect email
Status reconciliation
Determine final status for each attendee (registered, cancelled, transferred, checked-in, no-show)
Accurate final attendance count; correct follow-up targeting
Post-Event Data Cleaning
Task
When
Why
Merge check-in data with registration data
Day of event
Identifies no-shows; confirms actual attendees vs. registered
Session attendance reconciliation
Day of event or next day
Session capacity data for future planning; personalised follow-up by session attended
Lead scan data integration
1-2 days post-event
Sponsor and exhibitor lead scans need matching against registration data; deduplication against registration list
Post-event survey matching
1-7 days post-event
Match survey responses to registration data for attendee type analysis
Final attendee list for sponsors
3-7 days post-event
Sponsors paid for attendee list; must be clean, deduplicated, with registration data attached
Metrics
Metric
Typical range
Impact of data cleaning
Duplicate rate in raw registration data
5-15% of records
Cleaning reduces inflated headcount by 5-15%; corrects catering, seating and badge counts
Email bounce rate on confirmation sends
2-5% before cleaning; under 1% after
Cleaning prevents 2-4% of attendees from missing confirmation and event details
Badge printing errors
3-8% before cleaning; under 1% after
Name standardisation reduces reprints and check-in delays
Post-event follow-up delivery rate
85-92% before cleaning; 95-99% after
Cleaned email list ensures post-event survey, recap and sponsor offers reach attendees
Unique company count accuracy
Overcounted by 10-20% before cleaning
Company name standardisation gives sponsors accurate company-level attendance data
Sponsor lead report accuracy
15-25% duplicate rate in raw lead scan data
Deduplication gives sponsors accurate unique lead count; prevents duplicate sales follow-up
