5 CRM Data Clean Up Tips

Best Practices

In today’s world, companies rely on data to manage the end-to-end sales process, power marketing automation campaigns, deliver exceptional customer service, and so much more. In fact, the data in your CRM database is among your most valuable business assets.

To keep these critical business functions running smoothly, you need CRM data that’s complete, accurate, well organized, and up to date — but that’s easier said than done. Depending on the size of your company, you may be dealing with hundreds, thousands, or even millions of customer data records. And CRM data changes constantly as new accounts are added, new interactions are recorded, and contact details are updated.

Over time, it’s easy for CRM data to become disorganized and outdated. In fact, it’s almost inevitable.

That’s where CRM data clean up comes in. Cleaning up a cluttered CRM may not be as straightforward as tackling a messy closet, but it’s far more important — because bad CRM data can have serious consequences for your business. In this blog post, we’ll explore the ins and outs of CRM data clean up, including the top causes of bad data, tips for data cleansing, and best practices for keeping your CRM data clean and consistent.

 What is CRM data clean up?

PErson performing CRM data clean up

CRM data clean up (also called “CRM data cleansing”) is a set of processes that are used to improve the accuracy, validity, and consistency of the data in your CRM. Data cleanup can fix a multitude of problems, including:

  • Outdated contact information
  • Incomplete customer records
  • Duplicate entries
  • Missing data fields
  • Typos and spelling errors
  • Inconsistent formatting
  • Extra spaces
  • Invalid records
  • And more

Why you need a CRM data clean up

Most companies only think about data cleanup on two occasions: when they’re implementing a CRM for the first time and when they’re migrating to a new CRM. But CRM data is constantly evolving, so there’s significant value to implementing a regular schedule (and process) for CRM data clean up.

Think about all the ways CRM data can go bad:

  •  Web forms get filled out with typos and other errors
  • New contacts get added to your CRM with incomplete information
  • Multiple teams add the same contact to your CRM, causing duplicate records
  • Customer data collected over the phone is typed into the CRM incorrectly
  • Prospects enter fake or “burner” contact info to avoid sharing their personal data
  • Formatting conventions are applied inconsistently or ignored
  • Contacts get a new title, phone number, or email address — or leave the company altogether
  • Companies merge, relocate, rebrand, or go out of business

In fact, it’s estimated that up to 25% of CRM records may contain errors and duplication rates may be as high as 30%. All that bad data can have serious consequences for your business, including:

  • Wasted time as sales reps sort through inaccurate or outdated contact information
  • Inability to move prospects through the sales funnel efficiently
  • Lack of visibility into previous customer interactions and purchase history
  • Limited ability to segment audiences and target marketing campaigns
  •  Missed cross-sell and upsell opportunities
  • Inaccurate sales forecasts and performance analysis
  •  A disjointed or confusing customer experience

Data cleansing lets you identify records that are outdated, inaccurate, or incomplete and take steps to eliminate these issues from the CRM database before they have a chance to damage your business. If you see the warning signs of bad data — including duplicate records, missing fields, old information, and other data errors — it’s probably time for a CRM data clean up.

Tips for CRM data cleanup

You’ve heard the old saying, “An ounce of prevention is worth a pound of cure.” That’s especially true when it comes to your CRM data. If you take the time to conduct a thorough CRM data clean up, you’re far less likely to encounter serious data-related problems down the road.

Wondering where to start? Here are five important steps to cleanse your CRM data — and keep it clean for as long as possible.


Tip #1: Fix formatting issues and standardize formats

Formatting issues are among the most common problems with customer data. This includes things like capitalization in name fields, phone number formatting, state abbreviations, etc. While inconsistent formatting might seem like a minor issue, it can cause major headaches.

For example, name fields are often used to personalize email communications. When someone receives an email with their name uncapitalized, it can create a negative, unprofessional impression of your business. Inconsistent formatting can also make search and segmentation difficult, as records may be missed if the format doesn’t match the specified parameters.

Formatting issues should be addressed at the start of your data cleanup, to improve the effectiveness of deduplication and other efforts. Duplicate records may not be detected if the same data is entered with different formats (e.g., 555-555-5555 vs. (555) 555-5555 or CA vs. Cal).

Once you’ve taken the time to fix formatting issues, it’s important to create standards for data entry — in order to prevent problems from re-emerging. One of the most effective ways to standardize data formatting is to set property limits for key CRM fields, rather than allowing free-form text entry. For example, if you only allow two characters in the state field, you’ll never have to correct “Mich” to “MI” again.


Tip #2: Consolidate and standardize data fields

Data fields in CRM data clean upIt may seem counterintuitive, but more customer data isn’t always a good thing — because the more data you have in your CRM, the harder it is to keep clean. Of course it would be nice to know every detail about every lead, prospect, and customer, but excess fields in your CRM create additional opportunities for data entry errors, formatting problems, and duplicate data.

Instead, think about the fields that add the most value and the CRM data you use most — then consolidate your CRM records down to the most essential fields and standardize on that list of data points. You can also minimize the data requested in your web forms to prevent data bloat and improve the rate of form completes.

Once you’ve set standards for CRM data fields, one way to avoid future inconsistencies is by defining different user roles with varying permission levels. This way, only high-level users will have the ability to add or delete fields from a CRM record.


Tip #3: Merge duplicate records

Duplicate records are almost inevitable as your CRM database grows. Leads are captured through a variety of channels and systems — like outbound prospecting, web forms, industry events, social media interactions, inbound phone calls, and more. If there’s any inconsistency in the CRM data entry, a duplicate record may be generated.

When customer data is scattered across multiple records, it can be difficult to locate the information you need. Duplicate records also create challenges like unreliable forecasting and an incomplete view of the customer’s history with your company. That’s why deduplication is such a critical step in the CRM data cleanup process.


Tip #4: Create standard practices around data entry

In order to keep your data set clean and organized, you need to implement standard practices for CRM data entry and ongoing data quality. Start by identifying your most common sources of bad data. As you worked through your CRM data cleanup, did you find a high volume of duplicate data? Consistent formatting issues? Old records that were never purged?

Understanding the ways in which your customer data goes bad will help to inform your new standards and practices. Elements of your overall solution may include:


  • Creating formal guidelines on naming conventions and data formatting
  • Training sessions to educate and engage regular CRM users
  • Reducing the number of free-form text fields in your CRM records
  • Defining user roles and setting permissions to limit the number of people with editing ability
  • Developing a process for purging records after an extended period of inactivity

Tip #5: Implement a schedule for CRM data clean up

A one-time CRM data clean up is a good starting point, but it’s only the first step in a long-term solution. Even with the addition of formatting standards and naming conventions, there will always be typos, data entry mistakes, and other human errors. It’s simply impossible to keep your data clean without regular cleansing. So set a schedule for periodic CRM data cleanup — whether that’s monthly, quarterly, or annually — and stick to it.

Make the most of your CRM data with Insightly

A clean, well-organized CRM database empowers companies to drive more sales and deliver an exceptional customer experience every time. The key is to ensure that your CRM data is complete, current, accurate, and accessible to everyone who needs it.

Insightly CRM includes a powerful data migration tool that makes it easy to populate your instance with clean, downloaded data. 

Once you get your CRM data cleanup is complete, you’ll want to use that data to power all your critical business functions. Insightly is the only CRM solution that aligns sales, marketing, and services on a shared data platform to deliver a single, unified view of every customer — and unprecedented cross-functional transparency. 

Get started with a free trial of Insightly CRM today, or request a personalized demo to see how our simple, scalable solution can help your company achieve its business goals.

Additional helpful links

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