Top 5 Best Practices for Managing Data in Salesforce

Companies rely on Salesforce to help them make sense of all the data they collect, and if we take into account that Salesforce currently holds 23% of the global CRM market share, that makes it the dominant market leader. Having said this, it is not enough to simply collect data inside your Salesforce and hope that all of the features and functionality work as expected. There are certain data management best practices you need to keep in mind as you import data via spreadsheets, online forms, and other methods. In this article, we will take a look at the top five best practices you should start implementing today to get the most value out of your data and your Salesforce investment.

What is Salesforce Data Management?

Within the context of Salesforce, data management refers to the wide array of practices and tools you use to ensure the accuracy, completeness, security, and accessibility of your data. It encompasses the entire lifecycle of your data, from initial entry to ongoing maintenance and analysis. Effective data management is crucial for making informed business decisions, optimizing customer relationship management, and maintaining operational efficiency.

What are the Challenges of Managing your Data in Salesforce?

One of the main benefits of using Salesforce is all of the powerful business insight it can provide to improve your decision-making. However, this is only true if you have high-quality data, i.e., updated, accurate, and complete information. Having said this, a lot of companies are overwhelmed by the tidal wave of data that comes into Salesforce, which only continues to grow over time. The problems that can come from not properly managing all of this data include:

• Duplicate Data: Duplicate records can appear in many shapes, sizes and forms and usually as a result of manually creating new records or importing records from things like spreadsheets and online forms.
• Incomplete or Missing Data: Missing data can have a realy negative effect on your analyses, which can lead to missed opportunities and hinder your communication with customers.
• Inaccurate or Outdated Data: A lot of times, marketing and sales campaigns rely on information like emails and phone numbers and if this information is inaccurate or outdated, you could be wasting a lot of money.
• Data Fragmentation Across Systems: Your company is most likely using a lot of different tools and apps as part of yoru business processes and not all of this data may be properly aligning with Salesforce records.
• Invalid Data Validation Rules: Inaccurate or outdated validation rules may allow bad data to enter the system or prevent valid data from being entered. Weak validation mechanisms affect the integrity of data across the organization.

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Salesforce Data Management Best Practices to Overcome These and Other Issues

Implementing correct data management processes in Salesforce can help you overcome the issues we talked about earlier and many others as well. In order to help you get on the right track, we will now discuss practical steps you can take today to better manage your data and get the most value out of it.

1. Get a Grasp on Your Data Hygiene

Data hygiene refers to how much “dirty data” you have in your Salesforce, which includes things like duplicates, outdated or incorrect records, and many other issues. While this may not sound particularly important, consider the following statistic from Salesforce itself: poor-quality data can cost a business as much as $700 billion annually—or 30% of its average revenue. Why waste all of this money when you can put it to good use? There are a lot of data management apps on the AppExchange, and they give you an overview of the state of your data. For example, they will tell you how many duplicates you have, what data is incorrect, and many other issues that the application can help you identify.

Use this information as a baseline for understanding just how much work will need to go into cleaning up your data, what tools you will need and, after that, you can start your data cleansing efforts, which we will go over in the next section.

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2. Cleanse Your Data

Data cleansing involves removing all of the data issues you identified that can cause mistrust of the data, which hinders user adoption and further degrades data quality when users are not actively adding and updating records. It’s best to ‘nip it in the bud’ as soon as possible. As an example, let’s take data deduplication. Whether you decide to install an app or find yourself merging records, you should check your matching and duplication rules. It is worth pointing out that Salesforce, by itself, has very limited deduplication functionality. For example, there is no mass merge functionality. You will only be able to merge three duplicates at a time. There are many other deduplication limitations as well.

Consider running reports to find other issues. This is the meat and potatoes of the cleanup process, but it doesn’t have to be overwhelming. If you’re auditing your data regularly, you can run these processes pretty quickly, and making changes shouldn’t be overwhelming.

3. Use Automation to Manage Your Data

Let’s face it: maintaining good data hygiene is a time-consuming effort, so you want to automate it as much as possible. Using automation in Salesforce to manage data streamlines routine tasks, enhances data accuracy, and improves efficiency across teams. Automation tools like Flow can automatically update records, assign tasks, and send alerts based on specific criteria, reducing the likelihood of human error. Assignment Rules help ensure that leads and cases are consistently routed to the correct teams, while Scheduled Flows can regularly clean or update data. By leveraging automation, organizations can maintain high-quality data and optimize Salesforce performance with minimal manual intervention.

4. Prevent Bad Data From Coming Into Your Salesforce

Why wait for bad data to accumulate and snowball into big problems? It’s much better to be proactive and find as many data quality issues as you can before the data you import gets into Salesforce. There are applications on the AppExchange that will scan your data to find duplicates, which will eliminate a lot of hassles. Also, implementing data validation rules ensures that only accurate and complete information is accepted, enforcing required fields and proper formats.

Setting up picklists and standardized data entry options reduces the chance of inconsistent or incorrect inputs. Additionally, using Duplicate Management tools prevents the creation of duplicate records by automatically detecting and blocking them during entry. Training users on data entry best practices and establishing clear guidelines further helps to minimize errors. By proactively addressing these potential issues, organizations can significantly improve data quality from the outset.

5. Integrate Third-Party Applications With Salesforce

Give your sales team data and connections that they can use to cultivate great relationships with customers and target productive prospects. If you are looking to import data from other tools, there are a couple of popular options:

• Data Import Wizard: The Data Import Wizard is a web-based tool allowing users to import data sets into Salesforce objects, including accounts, contacts, leads, solutions, etc. This tool supports up to 50,000 records at once from common data sources like Excel, Outlook, and Gmail.
• Workbench: Workbench is totally free and can be used for data management activities. Workbench is an interface that gives Salesforce admins and developers a scaled-down, functional user experience to work with Salesforce data.

If you are exporting data out of your Salesforce, some of the popular options include:

• Data Export Wizard: A built-in Salesforce tool that allows users to manually or schedule regular exports of data in CSV format. It’s great for exporting large datasets across various objects.
• Report Export: Salesforce allows users to export report data into Excel or CSV format. This method is suitable for exporting data based on specific filters and criteria defined in reports.
• Third-Party Tools (e.g., Dataloader.io, Jitterbit): These external applications integrate with Salesforce and offer advanced options for data export, including automating exports and connecting with external systems for ongoing data synchronization.

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Ensure Long-Term Data Quality and Success in Salesforce

Effectively managing data in Salesforce is crucial for maintaining data integrity, improving operational efficiency, and driving better business outcomes. By following best practices such as enforcing data validation rules, regularly cleansing and updating records, leveraging automation tools, and preventing bad data from entering the system, organizations can ensure their Salesforce environment remains reliable and scalable. Consistent data management processes not only enhance the accuracy of customer information but also enable teams to make informed decisions and maximize the value of Salesforce as a powerful CRM platform. Implementing these strategies will help ensure long-term data health and business success.