Data Cleansing for Salesforce: Best Practices
- Taela Sigman
- Jan 29
- 3 min read
Salesforce, like many enterprise applications, can accumulate bad data over time, especially when users manually input data. Bad data in Salesforce can range from blank fields to complex duplicate records. Regardless of how many validation rules are in place, bad data inevitably finds its way into the system.
This article explores best practices your organization can adopt to effectively cleanse your Salesforce data.
Best Practices for Cleansing Salesforce Data
Identifying Data Issues Beyond Duplicate Records
Understanding the health of your Salesforce data is the essential first step in any data cleansing effort. While duplicate records are often the most obvious issue, many other problems can compromise data quality, including:
Missing data
Misplaced data
Formatting issues
Damaged data
Junk data
Incorrect data
These issues are often interconnected. For instance, the first step might be to identify fields with missing data and exclude them from being assessed for other data issues. There is no point in checking an empty field for incorrect formatting, junk data, etc. This is a waste of time and effort.
Additionally, identifying data problems can reveal their root causes, such as system integrations, data imports, or user errors. Addressing these root causes helps prevent future issues, ensuring long-term data quality.
Resolving Data Issues
Before diving into data cleansing, consider starting with a Data Quality Assessment (DQA) by ActivePrime. A DQA, available through ActivePrime or your Salesforce Account Executive provides valuable insights into your data’s health and offers tailored recommendations for resolving issues. For more details, see Data Quality Assessment for Salesforce: What’s Involved?
Data issue resolution can be as simple as identifying fields for missing data or as complex as enriching missing values in address fields. Other data resolutions include:
Standardizing data for consistency
Moving misplaced data to appropriate fields
Enriching records with additional values
Validating physical addresses and email addresses
The order in which data issues are resolved can play a key role in cleansing data effectively with less effort. For example, the first step might be to standardize and enrich fields used in matching criteria for duplicate records or other assessments. This ensures higher accuracy and confidence in identifying duplicate records. Higher accuracy and confidence mean automation can be enabled to resolve data issues with little or no manual intervention.
How data issues are resolved depends on your organization’s requirements. ActivePrime has over 20 years of experience helping organizations like yours with their Salesforce data quality journeys.
Preventing Data Issues
Preventing bad data from entering Salesforce is as important as cleansing existing data. A robust prevention strategy minimizes the effort required for ongoing maintenance. Here’s how your organization can prevent bad data at the source:
ActivePrime CleanData Search Before Create: This function alerts users during record creation that a similar record may already be in Salesforce. The user has the option to either use an existing record or create a new one.
ActivePrime CleanImport: Included with CleanData, check your incoming data against existing records to prevent duplicates. You can check against all data, or a very specific subset as required.
Validation Rules: These ensure data entry complies with business requirements. However, too many rules can frustrate users and inadvertently lead to poor data practices.
User Training: Educating users on data management best practices helps them understand the importance of clean data and how to input it correctly.
Clear Data Ownership: Assigning responsibility for data ownership ensures accountability and encourages users to keep data clean and accurate.
Continuous Data Quality Maintenance
Maintaining data quality is an ongoing process rather than a one-time task. It is a continuous cycle of identifying, resolving, and preventing data issues. That is why ActivePrime CleanData is an always-on data quality solution. CleanData continuously identifies, resolves, and prevents data issues for your organization with minimal to no manual intervention.
Archiving Old Records
Archiving unused records helps declutter Salesforce, improving both system performance and data storage efficiency. Regularly archiving expired data ensures the platform remains streamlined and effective.
Conclusion
Maintaining clean and accurate data in Salesforce requires a strategic approach that includes identifying and resolving existing issues, preventing new ones, and ensuring continuous maintenance. By implementing these best practices and leveraging tools like ActivePrime CleanData, your organization can unlock the full potential of Salesforce, improving operational efficiency and decision-making.