data standardization
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Have you ever gone to use data from your CRM, maybe in marketing automation, only to find that inconsistencies in the data are causing issues and embarrassing errors that could harm your company's reputation? Everyone has.

Standardized data, often referred to offhand as data normalization, is a critical piece of the puzzle when it comes to ensuring CRM data quality. Standardizing data improves data quality and fix many common data issues on its own. 

A lack of standardization results in low-quality data. Companies lose 12% of their potential revenue, on average, due to bad data. 

This causes many issues, including:

  • Harm reporting and forecasting by making your data difficult to search and filter. Standardization makes data queries and filtering easier and more predictable.
  • Embarrassing marketing automation errors that harm your reputation. Ever sent an email to “jane” instead of “Jane”? Or worse yet, refer to someone as “{First Name}”? These small errors break the veil of one-to-one personalization and harm your company’s reputation.
  • Balloon your marketing budgets. Inconsistent data can cause you to send bad emails, send direct mail materials to the wrong address, and ultimately cause a lot of waste in your marketing budget.
  • Break integrations with important software. For example, inconsistent phone numbers could cause problems with a sales team’s auto-dialer software, leading to missed opportunities.
  • Slow down data cleansing processes. When data has inconsistencies , there are many different types of issues that can crop up. These can be difficult to identify in the CRM or in Excel with VLOOKUP and will slow down your teams as they require by-hand editing to rectify them.

For these reasons, data standardization in your CRM system is absolutely critical for teams across your organization, including marketing operations, sales operations, and revenue operations teams. Most business processes can be improved with improvements to data quality.

In this article, we’ll break down a simple step-by-step process that companies can follow to put them on the path toward standardized CRM data.

  1. Audit and Take Stock of Your Data
  2. Remove Clutter From Your Database
  3. Know & Evaluate Your CRM Data Collection Methods
  4. Define Your CRM Data Standards
  5. Standardize Data
  6. Insycle — Put Your CRM Data Standardization on Autopilot

1. Audit and Take Stock of Your Data

To understand how serious your CRM data standardization issues are, you have to take a look at what you have in your database.

This audit should look at standardization issues, but should also look at other data-related issues that might be gumming up your processes as well. Raw data is almost certainly rife with errors. Any human input data is. In general, you want to make sure that your CRM data is:

  • Correct
  • Clean
  • Complete
  • Properly Formatted (standardized)
  • Verified

There are multiple ways that you can audit CRM data. You could audit it by-hand. In larger companies, this will likely be a process that will require attention from multiple different people. Additionally, you can use advanced Excel functions to isolate problematic data. Both of these will be time consuming and are likely to miss some of your data errors. Companies with larger databases will likely need to program a custom solution or find a suitable third-party tool, as Excel can only run smoothly with so much data at any given time.

The first time that you conduct a CRM data audit will always be the most painful. Once you have fully audited and cleansed your data, you can implement a data maintenance process that will make it less cumbersome in the future.

Ideally, no customer data that does not meet that criteria would ever find its way into your CRM systems. However, any company that collects a wealth of customer data will have some issues and errors that are present.

Related articles

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Sharing CRM Data: Why Exporting is Painful and How to Automate It

Salesforce Duplicate Management: How to Automate Salesforce Deduplication

2. Remove Clutter From Your Database

Before we can begin standardizing data so that it can be used throughout the customer lifecycle, we want to make sure that we are doing so from a solid starting point.

While some data problems create a chicken-and-egg scenario (data that would be better off standardized first, then cleaned), a good general rule of thumb is that clean data will be easier to work with and evaluate. Those case-by-case scenarios can be identified and prepared for in the auditing stage.

We recently published a guide to data cleaning. In that article, we outlined some of the common types of CRM data issues that companies experience. These serve as a good starting point for keeping track of the different issues that you’ll need to fix during the data cleaning process before you can begin working toward standardizing your data:

  • Duplicate data. Duplicate data in HubSpot and other platforms is a big problem because it breaks the single customer view that your marketing, sales, support, and success teams rely on to evaluate their engagements with prospects and customers. It splits the context of those interactions between two or more records. It also leads to more of the embarrassing mistakes that harm a company’s reputation — such as emailing or mailing marketing messaging twice to the same customer or prospect.
  • Irrelevant data. Unnecessary data that takes up vital storage space within your CRM.
  • Redundant data. Data contained in two fields (or across multiple records) that are trying to convey the same thing. For instance, “Location” and “City” may convey the same data in two separate fields, taking up space and leading to confusion when your team goes to use the data.
  • Inaccurate data. Standardizing your data doesn’t do you much good if you are standardizing inaccurate data. Make sure that you have data verification or enrichment plans in place to ensure that the data that you are collecting is accurate.
  • Low quality data. Data that is non-personalized or generally low quality. This can include organizational emails like,, or free email accounts for B2B companies. Another example would be emails that have bounced when previously mailed.

With these issues out of the way, you’ll have a clear path toward standardizing your data.

Free Customer Data Health Assessment

3. Know & Evaluate Your CRM Data Collection Methods

Part of improving your CRM data quality and data standardization is having a firm understanding of how that low-quality data is making its way into your CRM system. Knowing your CRM data collection methods and the complications that surround those methods can help you to take the appropriate steps to limit further data quality and standardization issues.

Consider your business requirements when collecting data. What data do you absolutely need to collect. What data is less important for your business processes?

Some common considerations when it comes to data collection methods include:

Customer-Facing Data Input Forms

When you rely on your customers to supply their information (as most companies do) you are going to have unavoidable data issues. Consider what information you are asking your customers to provide and what data it may be best to collect in another way, such as through a data enrichment service.

Make sure form fields have proper validation in place so that you are sending clean, standardized data into your CRM.

Employee-Facing Data Input Forms

Just like customers, your employees can make mistakes when inputting data into forms too, and just like those customer-facing data forms you need to evaluate what you are asking your teams to input and whether or not the forms have proper validation in place for each field.

Additionally, employee training on the importance and best practices of data quality and the impact of bad data on your business can go a long way toward reducing internally-caused customer data issues.

Third-Party Customer List Imports

Importing data from another platform can often lead to data issues and standardization. You may import a lot of redundant data because another platform uses different field titles to refer to the same data.

Say you were importing a third-party list into Pipedrive. If you don’t have Pipedrive deduplication processes in place, you are likely to create duplicate records. Knowing the issues that are common with imports from each third-party platform is important for reducing data issues.

Or maybe you have data from a recent event that you appeared at. There can be all sorts of issues with outside data — data in all caps, titles that don’t match conventions, picklist values that are unverified, etc. You can almost always count on outside data lists differing from your own data in a variety of different ways.

Your CRM data collection methods are the gears that are responsible for feeding new data into your CRM. Most data errors and issues will start there. Taking steps to rectify those issues before they take place can limit a lot of standardization problems.


Of course, integrations are all around great for businesses. They ensure that our critical software solutions are talking to each other and sharing data where available. However, integrations are another common source of data issues.

One software may categorize data uniquely, use different fields to describe the same information. Salesforce and HubSpot integration is a common need for companies that are looking to connect and sync their sales and marketing operations. However, it can lead to a number of common problems including the creation of duplicate contacts and companies, complicated account hierarchies that lead to errors, and issues with sync timing.

Integrations simply add too much value to avoid, but you can be certain that nearly any integration between two separate systems will cause some unintended data consequences that you’ll have to figure out how to deal with.

4. Define Your CRM Data Standards

To standardize your data, you have to have your standards defined. These standards are defined by a set of rules for each field.

For instance, some of the different standards that are commonly set for CRM field data include:

  • First names should be capitalized and contain no spaces, numbers, or extra characters. You may also want to remove middle names, and titles like Mr. and Ms. so that you can use the first name in campaigns without worrying about awkward outcomes
  • Phone number formatting should be specific and consistent, like 123-456-7890. As opposed to (123)-456-7890, 123.456.7890, or 1-(123)456-7890. It’s best to use an international standard like E.164 that is uniform and is supported by most software and hardware products.
  • States should be expressed using a consistent convention, either verbose such as “Washington” or abbreviated, such as “WA”. The key is to ensure consistency across all the systems and apps that you use.
  • Emails should follow the standard email format of “” You may consider limiting free email services like Gmail and Hotmail, or at least have a way to identify and filter for free email domains so that you can treat them as a segment. Limiting data sources can help to improve quality and make data standardization easier.
  • Website URL should include the full “http://www.” and not just “,” and use a separate field to store just the domain name “”
  • Job titles standardized to popular acronyms, such as “CEO” instead of “Chief Executive Officer.” You can choose either option, the key is to maintain consistency.

These are just a few examples of the different types of standards that you can set for your CRM data. The standards that you choose will depend on how you plan on using that data. For instance, a sales team with an auto-dialing solution might need phone numbers standardized to a specific format to work with their software.

If you use multiple systems, they all need to speak the same language to communicate with each other. That way you can ensure that you have data consistency across your platforms and create and aggregate reports from different sources.

How you standardize your data will depend on your business requirements. But with the right processes in place, you can always have clean data to improve your marketing, sales, and support campaigns.

5. Standardize Data

With standards in place, you can begin the process of fixing standardization issues throughout your customer database. For smaller companies, using Excel functions and VLOOKUP might be powerful enough to fix most of your standardization issues. Larger companies with more CRM records may need to invest in a third-party solution to manage data at scale on a continuous basis.

Implement proper form validation and data cleaning processes to ensure that data is standardized and clean when it hits your CRM. The best way to keep a customer database clean is to make sure that bad data never makes its way into it in the first place!

Try to keep your expectations in check. In large databases, it is impossible to avoid quality and standardization issues at some level. There will always be errors that you’ll need to fix manually. But by making standardization and proper data collection a priority, you’ll greatly reduce the amount of time that you have to spend dealing with these issues.

Insycle — Put Your CRM Data Standardization on Autopilot

Insycle is a modern customer data management solution that makes it easy for companies to clean and standardize data in popular CRM platforms like HubSpot and Salesforce. Insycle makes data transformation easy.

Insycle empowers you to subtly change your role. Instead of spending time chasing down and fixing bad data, you can take on a more strategic role to define standards and take a big-picture approach to customer data management. Insycle does all of the heaving lifting.

You won’t have to settle for a standard “on paper” that can be hard to follow and maintain. Through Insycle, your standards are enforced and processed automatically. This helps to create alignment between teams, who are free to focus on high-impact activities instead of spending their time fixing data errors and engaging in data entry. With Insycle, you’ll never have to go through a crazy “data cleaning sprint” again. Your data will always be clean and consistent.

Using Insycle, you can:

  • Audit your CRM data with the Insycle Health Assessment to pinpoint more than 30 of the most common customer data issues across your database. Insycle identifies common data issues in CRMs. 
  • Clean your CRM data using pre-built templates, or create your own templates to address your organization’s unique data issues.
  • Filter and search customer data to find problems that arise from your data collection practices.
  • Define your data standards and create templates and processes for maintaining them.
  • Standardize your CRM data automatically. Set scheduled data cleaning and data standardization processes to run at regular intervals.
  • Preview changes to your data before they go live.
  • Align teams on data standards and ensure that your customer data serves as a real-world example of how clean data can make a difference.
5 Steps for CRM Data Standardization



Insycle makes CRM data standardization simple to implement. Want to start standardizing your CRM data today?

Fill out the form below to sign up for your free 7-day Insycle trial.


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