Ticketing & Events
October 1, 2025 ¡ Last updated on March 14, 2026
Recipe: De-dupe Your Database
# Ticketing operations
# Recipes for success
Makes: Clean, accurate audience data you can trust
The Tomorrowâs Audience research by Indigo-Ltd and Spektrix shows that 54% of 2023 audiences were new, and that first-time attendees engage differently than returning ones.
This foundational recipe helps ensure your first-time audience data is accurate by removing duplicate records. Clean data gives you confidence when measuring audience loyalty, sending targeted communications, and avoiding over-messaging.
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What you need
- Access to Autotags, Normal Tags, and Customer Groups in Spektrix
- Understanding of the âPotential duplicateâ metric
- Staff time to work through duplicate records
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Time required
 Prep: 5 minutes
Cook: 1â2 hours (over several weeks)
Maintenance: 30 minutes per week
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What will this help me achieve?
- Accurately identify true first-time attendees
- Prevent double-counting and spam risks
- Improve CRM quality and staff confidence when viewing customer records
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Concepts weâll be using
- âPotential Duplicateâ Metric: Identifies customer records that may be duplicates based on shared data
- Autotags: Automatically applied tags that flag records for follow-up
- Normal Tags: Manually applied labels, such as âNot a duplicateâ
- Customer Groups: Adds a visual marker in the sales interface for flagged records
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Prep
- Create a Normal Tag called âNot a duplicate.â
- Set up an Autotag using the metric âPotential duplicate = trueâ and exclude records already tagged as âNot a duplicate.â
- Create a Customer Group that highlights customers with the âPotential duplicateâ tag. This will show a coloured box in the sales interface.
- Train your team to apply the âNot a duplicateâ tag to verified records. This automatically removes them from the flagged group.
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Activate
- Use Advanced Search to find customer records with the âPotential duplicateâ Autotag.
- Review each flagged record manually in the sales interface.
- If records are duplicates, merge them.
- If they are not, apply the âNot a duplicateâ tag to clear the flag.
- Repeat this process regularly to clean up your database.
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Try this twist
Add a weekly admin task to check for new potential duplicates. This helps ensure your data stays clean and accurate over time.
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More to explore
 âď¸Â  How to find Potential DuplicatesÂ
Detailed guidance on identifying and reviewing customer records flagged as potential duplicates in Spektrix.
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