Common Data Quality Issues in Salesforce and How to Fix Them

For anyone that uses Salesforce, maintaining your data quality is often at the top of your list. Falling victim to poor data practices can lead to problems for your business, such as inaccurate reporting, inefficient processes, and missed opportunities for your Go-to-Market team. By understanding and addressing these issues, you can ensure your Salesforce data is accurate and up-to-date.
Blue sky with white cloud

So now, let’s take a deep dive into how these issues can bog down your organization, so you can take control of your Salesforce data!

Issue # 1: Duplicate Records Prevent Informed Decision Making

Duplicate records can be a significant issue regarding data quality in Salesforce. They can arise from data entry errors, manual entry mistakes, or even unintentional data imports. In addition, duplicate records can affect a business’s ability to measure customer relationships and make informed decisions. Therefore, identifying and removing duplicate records in your Salesforce org is crucial to ensure data accuracy. 

The Solution #1

There are several ways to identify and eliminate duplicates in Salesforce. The simplest way is to search for matching values in the fields likely to be the same in duplicated records, such as names and email addresses. You can also use Salesforce’s built-in duplicate management tools to detect and remove duplicate records from the system. Finally, you can use third-party tools and services to scan your Salesforce data for duplicate records.

Once you have identified duplicate records, you must decide how to handle them. You can delete the duplicate records manually or use the merge tool to combine the information from two or more records into one. Merging your records will ensure that the data is consistent and up-to-date. However, merging records should be carefully performed as it could potentially lead to data loss if not done correctly.

Duplicate records can significantly affect your Salesforce data’s accuracy and business operations. Therefore, taking the time to identify and fix them is an essential step in ensuring the quality of your Salesforce data.

Issue #2: Inconsistent Salesforce Data Leads to Confusion

Inconsistent Salesforce data is another one of the more common data quality issues users face. It occurs when conflicting information is entered into different records or fields within a record, leading to discrepancies and confusion in your system, causing it to be less reliable.

For example, if you have two contacts with the same name but different addresses, it may be challenging to determine which contact is which without manually looking through each record. If you have an issue like multiple contacts, you set yourself up for errors in your reports and analytics and create frustration among your users.

The Solution #2

The best way to prevent inconsistent data from entering your Salesforce instance is to set up validation rules. These pre-defined rules require all data to meet specific criteria before saving the data. For example, you can set up a rule that checks for duplicates before creating a new record or enforces a consistent format for phone numbers and email addresses.

Here are some steps to set up validation rules in Salesforce:

  1. Click the Setup icon (Gear) and choose Setup.
  2. Click on Object Manager and select the object you want to add the validation rule to. 
  3. Choose Validation Rules from the menu on the left (at the bottom).
  4. Click the New button in the top right of the screen.
  5. Give the rule a Name and Description. If you are activating the rule immediately, check the Active  If not, uncheck the box.  You can come back and activate/deactivate rules after they have been created.
  6. Create the true/false condition for the rule.
  7. Click the Check Syntax button to verify your criterion is correct.
  8. Scroll down the page and enter in the text of the error message you want to display when the rule criteria evaluates to false. 
  9. Click the Save button.

By setting up these safeguards, you can ensure that all of the data in your Salesforce instance is accurate and consistent, helping you make better business decisions and the opportunity to understand your customer base better.

Computer graphic with different data issues

Issue #3: Incomplete Salesforce Data Means Missed Opportunities

Having incomplete Salesforce data in your org can lead to many roadblocks. Incomplete data most commonly occurs when necessary fields or information need to be included or answered, such as contact information, product specifications, or even financial figures. When data is incomplete, it can prevent your Salesforce users from effectively using the platform and could lead to making incorrect decisions for your business. 

The Solution #3

Fortunately, there are steps you can take to identify and fix any incomplete Salesforce data that might be lurking within your org. The best way to approach this issue is by creating a list of mandatory fields and comparing it to existing records. Addressing and updating any discrepancies as soon as possible is critical to maintaining your Salesforce data. In addition, it’s essential to implement a verification process to verify fields are accurate before entering any record into the system. Proper verification will help maintain the accuracy of your data and ensure that all records are complete and up-to-date. 

Issue #4: Invalid Data Clutters Your Salesforce Org

Invalid Salesforce data can occur when a field in Salesforce does not contain correct information. One example of invalid data is a value that doesn’t fit within a specific field’s accepted format, such as a phone number without the required number of digits. It can also have a wrong value, such as an incorrect address. 

Invalid data can be particularly frustrating because it often takes more work to identify the issue. In addition, some Salesforce users sometimes need to clarify what data needs to be corrected, as it may not stand out among the other records. Unfortunately, when this happens, you might only realize you have invalid data once you try to use it.

The Solution #4

So how do you fix invalid data in Salesforce? The best way to prevent invalid data is to create detailed rules and guidelines that precisely describe what type of data should be entered into each field. These rules will help ensure that your team is only adding valid information. Additionally, regularly check for any incorrect entries, and make sure to delete them. You can also enable validation rules in Salesforce to help you detect invalid data and provide corrective actions. 

Finally, you can use Salesforce Audits and Reports to scan your database for potentially invalid data. Reviewing your data with this tool can help you identify and address any potential issues before they become problematic.

Issue #5: Out-of-Date Data Leads to Inefficient Processes

Out-of-date Salesforce data is a common issue that can arise in any system. In Salesforce, this can present itself in several ways. For example, out-of-date data can include fields that are no longer relevant to your business, records that have not been updated in a while, or contact information that is no longer valid. This type of data can harm your system, leading to accurate reporting, decreased productivity, and efficient processes.

The Solution #5

It is vital to have a strategy for regularly reviewing and updating it to ensure that your Salesforce data remains up-to-date. If you have access to tools like Apex triggers, you can automate the process of data updates. These tools allow you to set specific dates for fields to be updated and trigger specific processes when meeting certain criteria. Additionally, you can set up scheduled jobs or dashboards that provide regular updates on the state of your data.

In terms of preventing out-of-date data, it is crucial to ensure that your Salesforce users know the importance of maintaining accurate data. Take time to train users on proper data entry techniques and the appropriate methods available to update existing records.

Best Practices for Data Quality Management

Salesforce is a powerful tool, but it’s only as effective as the data that’s entered into it. That’s why maintaining data quality is essential for any organization using Salesforce. Here are some best practices for data quality management:

  • Establish clear guidelines for data entry. All users should understand what data is required and how it should be formatted.
  • Use data validation rules to ensure that only accurate and complete data is entered into Salesforce.
  • Create custom fields and page layouts to capture all of the relevant information for your business processes.
  • Regularly review your data to identify any inaccuracies or inconsistencies. Use Salesforce reports and dashboards to help with this process.

Put in place procedures for correcting inaccurate data and preventing future problems.

By following these best practices, you can be sure that your Salesforce data is accurate and up-to-date.

CapStorm’s Solutions Will Ensure Proper Salesforce Data Quality

With CapStorm’s tools at your disposal, you can make informed business decisions while knowing your Salesforce data is accessible and verifiable. CapStorm technology facilitates seamless integration with near real-time data updates, keeping your data up-to-date as often as every five minutes. In addition, with the ability to analyze your data over any period you desire, you can access a much broader scope of Salesforce data than using Salesforce’s native tools. With CapStorm in your tech stack, it will be much easier for your data to remain complete, secure, and compliant. 

Ready for a risk-free way to take control of your Salesforce data? Try CapStorm free for 14 days.

Steven Welch

Steven Welch

Steven has over a decade of experience with content writing and design, and works to bring CapStorm's stories to a wider audience.

About CapStorm

CapStorm is the most technologically advanced Salesforce data management platform on the market. Billions of records per day flow through CapStorm software, and our solutions are used in every industry from credit cards, telecom providers, insurance agencies, global banks and energy providers.

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