Blog·August 11, 2026

How Long Does It Take to Clean Up Duplicate Contacts in Clio?

One of the first questions that comes up when a law firm realizes how many duplicate contacts it has is pretty predictable: how long is this going to take?

Unfortunately, there isn't a particularly satisfying answer like "500 contacts an hour." A firm with a few thousand potential duplicates might have a much easier cleanup than another firm with half as many. It depends on what those duplicates actually look like.

A lot of them are easy. James Smith and Jim Smith have the same phone number and email address. Someone filled out an intake form in all caps and created another contact. A staff member entered a referral source who was already in Clio. An integration created a new record instead of matching the one that was there.

You don't need a committee meeting for those.

Then you get the weird ones.

Maybe two contacts have similar names and share an address, but they're actually a father and son. Someone changed their last name. Two people at the same company share the main office number. An older contact has information the newer one doesn't. The longer a firm has been using Clio, especially if its data came through other systems first, the more likely it is to have accumulated situations that aren't obvious from a name alone.

That's why the number of contacts in your database isn't a particularly useful way to estimate the work involved. Even the number of potential duplicate groups only tells you so much. What really matters is how many of those groups require someone to stop and investigate.

And someone should.

There are plenty of parts of contact cleanup that software can handle, but deciding that two people are definitely the same person shouldn't be one of them. Your staff knows things about your data that an algorithm doesn't. They recognize clients, family members, referral sources and opposing parties. Sometimes a potential match that looks questionable on a screen is immediately obvious to the person who has worked with that client for five years.

The opposite is true too. Two records can look almost identical and still be two different people.

If someone approves a group for merging, that doesn't mean they need to sit there while everything happens. A merge can involve more than changing a name and deleting an extra contact. Information associated with those contacts has to end up in the right place, and their relationships to matters need to remain intact.

That processing takes time, particularly when you're working through Clio's API, but it doesn't need to consume an employee's time. A much more practical workflow is to review a batch, start the approved merges, and go do something else while they process in the background.

That distinction becomes pretty significant when you're talking about thousands of duplicates.

Trying to clean an entire database in one heroic push isn't especially useful either. If your firm has spent ten years accumulating duplicate contacts, nobody gets a prize for fixing all of them by Friday. Rushing through ambiguous matches just to make the number go down is a good way to trade duplicate data for bad data.

Work through it in batches. Fly through the obvious ones. Spend time on the ones that actually require judgment. Leave something alone if you aren't sure.

The other thing firms tend to discover is that cleanup isn't really a one-time problem. You can get the database looking beautiful and still have duplicates start appearing again next week. Staff will enter contacts differently. Clients will submit new intake forms. Integrations will sync data. Imports happen. Humans continue being humans.

Maintaining clean data is a very different job from cleaning up years of accumulated mess.

Once the backlog is gone, regular scans can catch new duplicates while there are still a handful instead of several thousand. At that point, contact cleanup stops being a giant project and becomes routine maintenance.

That's ultimately how we think about it at MERGEguard. The goal isn't to automate every decision or claim that thousands of duplicate contacts can disappear overnight. It's to automate the tedious parts so your staff spends its time on the part they're actually qualified to do: deciding whether two records belong to the same person.

Everything after that should be the computer's problem.

If you're ready to tackle your backlog, start at mergeguard.net.