Salesforce Data Cleansing: A Comprehensive Guide

Nikita R.

Media-savvy content creator, with a curiosity for all Salesforce experiences.

Updated: Jan 13th, 2025

Your business should participate in data cleansing tasks and processes to keep information accurate and consistent in Salesforce. When you have clean data, you can expect to create error-free and reliable reports. Reports are crucial artefacts that assist managers in making decisions about business operations.

Join us in the article below as we explore topics about data cleansing in Salesforce to get a better understanding of this critical process.

What is Salesforce Data Quality and Cleansing?

Starting at the very beginning, when talking about data quality in Salesforce, we are referring to the following standards:

The accuracy of data.

The completeness of data in your database.

The consistency of accurate data across your platforms.

The reliability of your Salesforce data.

It is important to have high-quality data since it is used to make decisions in businesses. Salesforce data is often studied to improve customer interactions. For these reasons, keeping data integrity in Salesforce high should be a main priority in your company. Ensuring you maintain high-quality data in Salesforce can be achieved with a meticulous data cleansing process.

Data cleansing consists of tasks to identify and remove invalid information from a data set. To clean Salesforce data, you need a process, which could look something similar to this:

• Check that your data is standardized. This means examining your data formats, such as phone numbers and addresses.
• Inspect Salesforce Data Cloud for any duplicate records. If you can identify them, you can go ahead and merge them.
• Look at your data to see if it meets your business’s rules and validation criteria.
• Scrutinize your database for any missing data. You can then add data to complete your profiles.
• Scan your data to see if you need to delete any outdated information.

Data Cleansing Examples

In Salesforce, data cleaning does not have to be a completely manual process. The CRM giant has many tools to support your SFDC hygiene practices, such as the Data Import Wizard. Let’s take a look at a few examples of how you can clean data in Salesforce.

1. Removing Duplicates

You want to remove duplicate data in Salesforce to uphold data integrity. A few tools from Salesforce can assist you with finding and deleting duplicate records. To locate your duplicated entries, we suggest using the rules built into Salesforce to assist with data management.

To begin managing data, you want to ensure you have set up your matching rules. These rules tell Salesforce what can be considered a duplicate record. If configuring these rules sounds too complicated, try Salesforce’s standard matching rules to get started before tackling the custom matching rules options.

In Salesforce, you can then set up rules to identify identical data and stop the creation of new duplicates. Your duplicate rules configuration can also inform users that there are equivalent records in Salesforce. Although the duplicate rules system future-proofs data entry, it can also be beneficial for identifying duplicated records in the present moment.

Then, you can use the Salesforce Data Loader app to export data. We suggest using it to remove unwanted data from Salesforce.

2. Correcting Typographical Errors

Typos can negatively impact business operations, especially when it comes to customer interactions. For example, if you are working with misspelled email addresses, your teams run the risk of sending a message to a customer or lead without getting a response. This huge missed sales opportunity can hold your business back from growth.

If you have a project scheduled to fix typos in Salesforce. Make sure to check your:

Customer Names

Physical Addresses

Email Addresses

Other Data Stored in Salesforce

Then, you can use the Salesforce Data Loader app again to export your data into a spreadsheet. Now, you can sift through the details and manually correct them before uploading them back into Salesforce with the Data Loader app.

If you do not have time to check all your data, you can create a report in Salesforce to quickly scan for typos. For example, reports have a filter feature that allows you to find all the email addresses that do not have the “@” in a field.

We can agree that these are pretty manual methods for cleaning your data. If you have the resources or budget, an automatic way to correct typographical errors in Salesforce is through Apex triggers and classes:

Salesforce developers can write Apex triggers that automatically fix typos.

Salesforce developers can write Apex classes when you need to detect and correct errors.

3. Standardizing Data Formats

It’s important to know what data formats Salesforce supports so that you can standardize your business artifacts. This step will ensure that your data is consistent across all platforms and stays accurate for your reporting needs.

When working in Salesforce, you have access to many fields:

Text

Number

Date

Picklist

We recommend that you understand and configure your fields well on your standardization journey. Here is a quick guideline for Salesforce fields:

3. Filling Missing Values

As you can imagine, incomplete data can manifest difficult times for a business. Essentially, missing data yields inaccurate information. So, when you use this incomplete data to create reports, your decisions based on these insights will, unfortunately, be incorrect. These vague results can have drastic consequences for your business depending on the direction you need to take.

The first step to adding missing values to data in Salesforce is to find out where you have gaps. Then, you can add data to Salesforce to ensure completeness that supports accurate reporting.

You can use the Data Import Wizard in Salesforce to upload your data into the database. The Data Import Wizard is a user-friendly tool that gives us a guided interface to add data to Salesforce without requiring coding skills.

4. Salesforce Data Validation

You could also use Salesforce’s validation rules and features to ensure data integrity. Validation rules are customizable, so teams can use them to impose standards for data entered into Salesforce. Check them out as they work with simple or complex criteria.

Teams often use validation rules to make sure that fields are mandatory and require input from a user. Another good use of validation rules is to ensure fields only accept email addresses in the correct and standard format.

5. Deleting Unnecessary Data

We spoke about removing duplicates earlier, but sometimes there is data in Salesforce that you no longer wish to keep. These could be old or inactive Salesforce records that have not been viewed in years. To make sure that you are only managing relevant data and to declutter your database, you should delete irrelevant information.

If you need to delete small batches of data, then you can simply manually remove them in Salesforce:

1. Go to your object’s list view and choose the records you want to take out.
2. Now click on Delete.

If you need to delete a large volume of data, we suggest using an app like Data Loader to speed up the process. Alternatively, you could use Salesforce Inspector or another trusted third-party app to do the job. Either way, choose an efficient tool that can find and delete bulk data based on:

Record Type

Creation Date

Custom Filters

We hope to see you soon!

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