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Pavilion

How Pavilion cleaned up duplicate member records in Salesforce

  • Data quality
  • Deduplication
  • Salesforce
The product is exactly what we need -- it's got a nice interface, the UX is well designed, and it's easy to configure.
of Pavilion's active Salesforce members had duplicate records
6%
found among active members and merged
350duplicates
saved versus resolving each duplicate by hand
29hours

Pavilion runs a global community of go-to-market professionals: 12,000 members across 100 cities, all tracked in Salesforce. During a CRM migration, the team found that 6% of its active members were duplicates. Plauti found and merged those records, and now flags new duplicates as they're created.

The cost of scattered email addresses

Pavilion's members often sign up more than once under different addresses. Tom Andrews, Senior Director of Systems & Insights at Pavilion, described the pattern: "One of the main issues we had was in the member space. People sign up with different email addresses. They might sign up with their work email and then decide to switch to their personal email. And it becomes really difficult for us to manage."

Salesforce sits at the center of that work. As Tom put it: "Salesforce is, in my opinion, the most important tool we've got internally, and alongside our actual platform, it's crucial." Pavilion's previous CRM had served the company while it was smaller, but the team needed Salesforce's partner ecosystem of tools and apps to fix its data quality and start mining insights from a large member base.

The duplicate emails created problems beyond the inbox. Overlapping accounts risked lost data, confused billing, and complications for a digital product launch already on the calendar. Rupa Sunkari-Partridge, Operations Analyst at Pavilion, added a further wrinkle: "We have many members in our database who aren't active. Merging active members' duplicates matters more right now than merging inactive members'."

Pavilion needed a way to clean up its Salesforce data without slowing its next stage of growth.

Migrating to Salesforce without carrying the duplicates

As Pavilion prepared to move to Salesforce, the scale of the problem became clear: about 25,000 duplicate records surfaced in the existing data. Sorting through that volume by hand wasn't realistic, and the migration itself was too large to curate record by record.

The team's plan: move the data into Salesforce first, then use a dedicated tool to clean up the existing duplicates and catch new ones as they were created. That let Pavilion migrate on schedule and clean up afterward, rather than holding up the whole project to sort data manually.

Detecting duplicates at the point of entry

Plauti runs inside Salesforce and checks incoming records against more than 20 matching algorithms. For Pavilion, running inside Salesforce itself was the standout feature: it let the team catch potential duplicates as members signed up, rather than finding them later during a cleanup pass.

That mattered because members often used more than one email address over time. Plauti gave Pavilion a single, combined view of those addresses, so the team could tell when two records belonged to the same person.

Filtering merges to protect active members

Tom Andrews, Senior Director of Systems & Insights at Pavilion, pointed to one feature in particular: "The feature of Plauti that we loved, and one I haven't seen elsewhere in the market, is being able to pull multiple email addresses from multiple fields into one combined field and use that to detect duplicates. Some of our members have up to seven email addresses on file, split across different fields on different records."

Rupa Sunkari-Partridge, Operations Analyst at Pavilion, said filtering matters because so many records in the database are inactive: "Being able to filter each job we run to get the data we need is crucial." She also recalled the onboarding call, where the team walked her through the platform and how to customize it -- including a quick-merge feature that applies the field-level rules Pavilion sets for each merge.

Results: fewer duplicates, less manual work

Among Pavilion's active members, Plauti found that close to 6% were duplicates, about 350 records. Tom Andrews at Pavilion estimated each one would have taken roughly five minutes to resolve by hand -- close to a full workweek of manual cleanup avoided.

A database the Pavilion team trusts

The benefits went beyond the hours saved. Both Tom Andrews and Rupa Sunkari-Partridge at Pavilion said they trust the database more now that it holds clean, reliable data. That confidence reaches members too: billing and communications now reach the right person, because each member has one record instead of several.

What Pavilion says about working with Plauti

Tom Andrews, Senior Director of Systems & Insights at Pavilion, described the rollout in plain terms: "I was impressed with the whole process. Plauti's team was helpful, and the onboarding was straightforward. The product is exactly what we need -- it's got a nice interface, the UX is well designed, and it's easy to configure."

For Pavilion, the win was the duplicates merged, the hours saved, and a database the team now trusts as it keeps scaling to serve members around the world. "I'm happy with the entire experience," Tom said.

Hungry for more?

Frequently asked questions

How many Salesforce records did Plauti find duplicated at Pavilion?

Plauti found that about 6% of Pavilion's active members, roughly 350 records, had duplicate entries in Salesforce.

Does Plauti stop new duplicates from being created, or only clean up existing ones?

Both. Plauti merged Pavilion's existing duplicates and now checks records as they're created inside Salesforce, so new duplicates are caught at the point of entry.

How much time did merging duplicates save Pavilion's team?

Pavilion estimated each duplicate would have taken about five minutes to resolve by hand. Merging roughly 350 of them with Plauti saved the operations team about 29 hours.

Can Plauti match records across multiple email fields?

Yes. Pavilion combined multiple email fields (some members have up to seven addresses on file) into one field and used that to detect duplicates across records.

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