In order to take advantage of the latest staffing tech and supercharge your firm’s operations, you’ll need a solid foundation of clean data. Data hygiene might not sound as exciting as, say, generative AI, but your tech will only take you so far if the data it uses is inaccurate, incomplete, or missing entirely.

It’s time to spring clean your data to ensure it isn’t holding you back from moving your firm forward. Let’s explore how.

What is data hygiene?

Data hygiene /ˈdadə,ˈdādə ˈhīˌjēn/ (noun) – The process of ensuring your database contains data that is accurate, error-free, correctly formatted, and complete.

Why data hygiene matters:

Find the information you need quickly.

If your records aren’t accurate, they won’t be included in searches, automations, analytics features, and AI, limiting the usefulness (and value) of that data and your overall ATS/CRM.

Trust and leverage a single source of truth.

Without data integrity, your recruiters and sales teams will look elsewhere to find the information they need, slowing down day-to-day processes, hampering communications, and creating headaches.

Enable easier recruiting and sales processes.

With the information your team needs at their fingertips, they’ll be able to have a more complete view of their candidates, prospects, and clients, making recruitment and business development that much easier.

Did you know? Top-performing firms are 50% more likely to say they can rely on their database.

Learn more.

Source: GRID 2024 Industry Trends Report

Common issues causing poor data hygiene

Human error and entry mistakes

Inputting large amounts of data manually can lead to simple entry mistakes in spelling, capitalization, and accuracy. Though these may seem negligible, they can add up – having incorrect or inconsistent data in fields can prevent records from appearing in searches and automations.

Poor workflows and business processes

Maintaining data integrity requires constant maintenance. If your team isn’t regularly updating your database, it can quickly become full of outdated information.

Improper parsing from external sources

Improper parsing of candidate or client records en masse from external sources can result in importing records with missing or incomplete information – or even inputting the right data in the wrong fields.

If your database isn’t useful to your team, they’ll look to other external sources for their information, resulting in an underutilized ATS/CRM that prevents your business from reaching its full potential.

Because everything is in Bullhorn, I can quickly go in and see people they’ve already contacted, where certain stages are, provide additional insights, and really just help. It helps keep our recruiters contacting the same people over and over
Michael Johnson Founder, Growing HVAC

How to clean your database

With a combination of improved workflows and smart solutions, you can transform your database from an archive of old, outdated info to a goldmine of information for your business.

Cleaning your database can seem like a monumental task, so we’ve broken it down into key phases to keep things manageable.

Phase 1

Audit your database

Phase 2

Get rid of duplicates

Phase 3

Capture missing data

Phase 4

Archive stale data

Phase 5

Establish data governance

1. Audit your database

Before you dive in, evaluate the state of your ATS/CRM. Here are a few metrics to help you understand the current state of your database – and what steps you might need to take to clean it.

Percent of database that is usable

Which records have contact information? Which records are outdated?

Percent of database that is engaged

How recently have your candidates and clients engaged with you? When was the last time records have been updated?

Administrative hours required by recruitment and sales

On average, how many hours per week (or per day) do your recruitment and sales teams spend on updating records? Are records updated manually or through automation?

Looking for more measurement tools?

Check out these 9 essential Connected Recruiting KPIs to help you track the success of your recruitment process.

Audit your database with these three steps:

1. Determine the root cause of dirty data.

If it’s due to human error, you’ll want to work to establish stronger data hygiene practices and workflows.
If it’s due to an integration issue or incorrect parsing, you may want to troubleshoot these, ensure your API connections are updated, and work with your IT team to resolve these issues.

2. Examine the structure of your database for two key things:

  • Is it easy to navigate?
  • Can you quickly move between records to find the information you need?

You may want to redefine your data model to ensure data is stored and structured in a logical organizational framework.

3. Establish goals.

Having something to work towards can make the tangible benefits of data hygiene pay off. For example, you might want to increase ATS/CRM adoption or boost engagement or conversion rates.

Setting these goals can help you track your progress and help your team better understand the importance of data hygiene.

Pulse check

So…how’s your database looking?

We have lots of duplicates.

A lot of data seems out of date.

We have records with missing information.

It’s looking good!

2. Get rid of duplicates

Having a clean database means that all of your information is in one place — not spread over two or more duplicate records.

Instead of deleting duplicates entirely, try merging them so you still retain important information that might be contained within those extra copies.

Tip: To merge duplicates within the Bullhorn ATS, choose one record to be primary, which will remain intact, and enter the duplicate record to be secondary. The notes, emails, tasks, appointments, and file attachments will be transferred from the secondary record to the primary record. Once you’re ready, you can use the actions drop-down on the primary record to merge the two.

Advanced tip: Bullhorn Marketplace partner Kyloe offers tools to give you full control of how duplicates are identified and merged and remove duplicates in bulk.

Learn more here.

3. Capture missing data

Working with incomplete data can be frustrating, and locating a record that doesn’t have the information you need can feel like hitting a dead end.

Finding records with missing data and updating – or archiving – can make your business development and recruiting processes more efficient.

When it comes to completing records, start with contact information; make sure everyone has either a phone number or email on file. There’s no point in having a candidate or client in your system if you can’t reach them!

Once you locate records with missing data, you can either track down that information and complete it or, if those records belong to a disengaged candidate or prospect, archive them.

Tip: You can find records that do not have a phone number and/or email on them by using the Additional Search Criteria function to exclude all numbers from the phone number field and/or the @ symbol from the email field. Doing so will populate your search with contacts whose phone numbers and emails are missing.

Advanced tip: If you have an old database, and have since made changes to any of your fields, like category or skill codes, you can bulk update those values using Bullhorn Automation.

Learn how in this Automation in Practice.

Advanced tip: Instead of manually filling in missing information, have candidates provide their information themselves and sync it to your database. You can do so with Bullhorn Automation; there are a number of blueprints that reach out to candidates with missing information and parse their responses directly into the appropriate fields. There are also Blueprints where you can copy information from one place to another, so if you know information on a placement record, you can copy it to a candidate record or submission record.

Check out this Automation in Practice to learn more.

4. Archive stale data

If stale data hasn’t been used or updated in some time, it may be time to archive it. Doing so will streamline your teams’ workflows so old records don’t get in the way of finding the information they’re looking for.
Rather than deleting data, archiving it simply tucks it out of view instead of getting rid of it entirely.
Who knows? The information you have on that candidate you haven’t spoken to in years, or that hard-to-reach prospect might come in handy someday.

Tip: To find stale data, add Last Date Modified or Last Note in your additional search criteria. You can then change the status of old records to “archive” en masse. To un-archive a record, you can simply change the status to anything else.

Advanced tip: You can have Bullhorn Automation set candidate statuses to archived for you. For example, you can build an automation that finds active candidates that haven’t submitted in the past 180 days and automatically sets their status to archive.

Check out this how-to guide.

5. Establish data governance

To ensure that your data is continuously cleaned, it’s crucial to establish a data governance framework.
Here are a few considerations to guide your thinking:

Is there a standard operating procedure when it comes to inputting new data?

What does a typical data entry workflow look like?

Who is responsible for owning and maintaining certain pieces of data?

Is there a person or team dedicated to maintaining the master data files and the overall health of your database?

Is there a training protocol in place to help new hires understand how to use your database?

Don’t forget to pay attention to the details! Data standardization is an important part of establishing data governance.

Here are a few details to pay attention to:

Mailing addresses

Are street names spelled out, or are you using abbreviations?

Phone numbers

Do you include country codes or parentheses?


Are these required fields for contacts? Do you abbreviate items like Jr.?

Tip: Owners can make certain fields required to ensure that necessary information – especially contact details – are added prior to saving a new record.

Learn how in the Bullhorn Knowledge Base.

Best data hygiene practices

Regularly audit your database to ensure consistent data health (or better yet, set up automations that can do this for you).

Create a database-first mindset by building better, more extensive searches that can surface high-quality candidates already in the ATS.

Consolidate your tech stack data into one place for end-to-end business analysis to answer questions such as:

  • Where are your holes in the talent funnel?
  • How are your front-office efforts driving business outcomes?
  • And what’s the ROI on your tech investments?

With solid data hygiene, you’ll build the foundation for a tech stack that can help take your business to new heights.

Ready to get started?