Preserving Salesforce Data Integrity: 10 Steps to Success

Data is the heart of your CRM system: it informs your team about the customer needs, the current company trends, and the potential gaps in the service you provide. In Salesforce, where most decisions and functionality depend on it, data integrity becomes one of the central values. It determines how successful your workflows are and how you organize workplace procedures.

High-quality and reliable records contribute to evidence-based decision-making, which, in turn, affects how your customers see you. Companies with poor data quality can suffer from reduced ROI of their Salesforce usage.

This guide will answer what data integrity is, explain the challenges of maintaining Salesforce data integrity, show why this value is so high on our list, and provide simple and practical tips to ensure you’ve got clean and reliable records. We will further highlight several of the tools and real-world examples to serve as your focal point.

The Importance of Data Integrity in Salesforce Implementation

What is “data integrity,” and why is it necessary? The term itself is the principle that guarantees that data remains reliable, complete, and consistent throughout its lifecycle. Since Salesforce has its own data operation and storage rules, it’s more about the records. Every piece of data in the Salesforce system, including customer details, sales pipeline, or activity history, should be accurate.

Like any software, Salesforce is as reliable as the information you put into it. And so, the meaning of data integrity has grown to be associated with the team and its value.

Today, companies cannot afford to risk poor data quality — it can lead to painful legal, operational, and financial costs. It can cause:

• Operational inefficiencies. According to Gartner, the price of poor data quality for companies can reach an average of $12.9 million every year. This stems from poor decision-making and an increased ecosystem complexity. Teams that don’t have recent Salesforce data tend to struggle with collaboration and retrieving the relevant details. This also means many users repeat the same actions or don’t know the data they rely on. Over time, this will lead to deficiencies in the work environment. 
• Customer dissatisfaction. The worse you work, the less loyal your customers become. When Salesforce doesn’t have the relevant contact details or order information, the team will make mistakes, provide poor service, and harm customer relationships. For example, only 35% of CRM leaders today admit they have fully integrated their customer data into their tools.
• Regulatory non-compliance. Data security and preservation are highly sensitive topics today. A failure to comply and ensure trustworthy measures that each region has to protect this data can trigger legal ramifications. Companies should learn to implement best data security practices in Salesforce to prevent this from affecting their reputation and financial well-being. 

Key Benefits of Data Integrity

Data integrity brings several advantages to your business and Salesforce. Below are the main benefits of data integrity:

• Accurate reporting for data-driven decision-making. Leaders no longer choose their next steps in the dark. They rely on potential risks and gaps, which allows them to forecast sales and identify the critical customer churn risks. Operating without data is theoretical. With it, however, every choice becomes about action and practice.
• Improved customer satisfaction through reliable services. When all your teams have equally detailed access to your customer data, the quality of support and your product or service offering becomes much higher. Maintaining the integrity of Salesforce data is an advantage with multiple effects, including better customer relationships. Every customer wants to know that they matter; nothing does this better than knowing their history, preferences, and past purchases.
• Streamlined workflows with reduced errors. In 2023, Salesforce predicted its data to grow by 22%. This growth demonstrated the need for effective data management for better processes. Many processes in the Salesforce ecosystem require clean data that doesn’t need to be verified — this way, you can automate routine tasks, such as lead scoring or email campaigns. 

“Clean and reliable data is what makes Salesforce such a powerful tool. How you leverage all the findings and put them into practice is what defines you,” explains Anastasia Sapihora, Salesforce Architect at Synebo.

Common Challenges in Maintaining Data Integrity

Such complex systems as Salesforce can break down for multiple reasons, whether due to accidental error or inadequate in-team data management practices. Once this error penetrates the software and gets lost, figuring it out becomes much more difficult.

Maintaining Salesforce data is a continuous process that is easy to overlook when the team is overwhelmed and doesn’t have the proper tools to handle it. So, it’s best to identify and eliminate these errors as fast as possible. 

Data Migration Errors

Data migration isn’t as clear-cut as it might seem — all the systems have their own requirements for data, and triggering the process inattentively, without knowledge of this error, can accumulate low or even harmful data. CRM data integrity often depends on how well it’s transferred between the systems, and it can strongly affect the quality of your team’s performance and the customer service you provide. Up to 75% of service leaders face gaps in their data. 

• Missing fields. Sometimes, the data in your Salesforce system has more fields than the legacy system from which it migrates. For example, your original system may have only the phone number field, while Salesforce also requires the contact’s email.
• Mismatched formats. This minor issue can easily be missed, which is why it’s so dangerous. Even such a simple thing as date format can make data migration a more demanding process than it should be. To illustrate, dates formatted as MM/DD/YYYY might clash with systems using YYYY-MM-DD, and you might not notice it.
• Incomplete records. A lot of data gets lost or just remains incomplete during migration. When the team cannot maintain Salesforce data integrity, the records that lack address information or sales history can leave the entire segmentation or reporting ineffective. 
• Duplicate and merge issues. During data migration, duplicate records can often be created, especially if multiple systems contain overlapping customer information. Some records can merge and present conflicting information because of contradictory sources.

Lack of Data Governance Policies

This is when many companies start to reach out to Salesforce administration services to establish clear principles on which the team will rely in the future. This error, mostly stemming from a human factor, can leave the most unpleasant results — the lack of proper rules and guidelines on handling data and format-specific phrases/abbreviations/titles can make standardization and analytics impossible. 

• Inconsistent naming conventions. Reporting on how to name a particular field is difficult to track if there aren’t any policies for data governance. For example, one rep logs a company as “Acme Corp,” another as “Acme Corporation,” and a third as “ACME.” Finding each of them as part of one subject can become impossible.
• Duplicate records. Not only do users complicate records because they weren’t informed about proper guidelines, but even the issue above can contribute to it as well. The amount of logs for one client or issue can multiply without anyone knowing.
• No clear data ownership. Some companies don’t assign specific people to edit or create data. This causes a lack of accountability and makes data improvement difficult.

Integration Complexities

Salesforce rarely functions in a vacuum. It connects with marketing platforms, ERP systems, support tools, and other third-party programs. That’s why each integration point can become a potential vulnerability, whether it’s field mismatching or issues with data updates.

10 Simple Steps to Maintain Data Integrity

Once data quality and applicability become unacceptable, redoing the entire system integrity becomes more complicated. That’s why it’s always a good idea to focus on maintenance and prevention rather than addressing the crisis. These best practices for Salesforce data management are gradual and easier to implement.

Step 1: Audit Existing Data

Audits are crucial in Salesforce on a regular basis — three times a year is a golden standard. However, before you proceed with putting new information into your Salesforce system, make sure to audit what is already there. Your audit can look for:

• Redundant or duplicate entries
  
• Incomplete fields
  
• Outdated records (e.g., contacts who haven’t engaged in over 3 years).

You can use tools like Salesforce Data Loader or Excel pivot tables for a quick health check. By identifying the data issues in Salesforce and the quality of your records at the moment, you can understand where to move from here. Important: Have a specific inventory where you can check each field and data to make sure this system serves as a centralized info point. 

Step 2: Cleanse and Standardize Data

Now that you’ve reviewed all your records, you have a good understanding of your Salesforce data issues and procedures. You can cleanse your data and make sure all of it has a unified format. 

Delete record duplicates on your own or using tools to do so (it’s best to combine them to save time and ensure good results). Get rid of all irrelevant data, such as outdated records or client contacts. Then, correct errors in all the fields and reports, especially when paying attention to contact information that can be easily overlooked. 

Standardize your formats for key fields like dates and emails. Choose a universal format and make it your new norm for the entire organization and teams using Salesforce. 

Step 3: Define Data Governance Policies

As we already explained, Salesforce data governance helps you develop and maintain a golden standard for your company, which will ensure better efficiency in the long-term perspective. Define clear policies on such things as: 

• Field ownership. Assign responsibility to specific roles or departments for maintaining key datasets. This will create a system where each dataset is relatively independent but follows the same standards. 
• Access controls. With Salesforce profiles and roles, you can assign different permissions for creating, editing, and deleting records. This will ensure no extra interruptions or unauthorized access.
• Standard naming conventions. Establish that account and contact names follow a consistent pattern (for example, “Company Inc.” instead of “Company, Inc.”). Reinforce it everywhere, which will make it easier for users to perform manual input in Salesforce.

Step 4: Use Validation Rules in Salesforce

Your Salesforce has built–in validation rules that can help you enforce effective Salesforce data quality standards during entry. You can introduce mandatory email validation or add proper formatting rules (such as email having an @ and so on). Or you can simply forbid inputting factually impossible information — no more accidental records added by an unsuspecting user.

Step 5: Use Duplication rules

Salesforce duplication rules can help the team prevent the entry of redundant records by identifying and blocking or alerting users about potential duplicates. These rules work together with the matching rules, and this affects how Salesforce identifies the duplicates. This serves as an additional measure to prevent duplicate records.

Create the duplication rules for leads, contacts, accounts, and more — this will prevent your CRM system from overcluttering with overlapping entries. 

Step 6. Merge Duplicated Data

If some duplications have slipped through despite your efforts, you can always merge them. This means you’ll need to consolidate information from different entries into one that is easy to achieve — Salesforce already has the merge function. Review conflicts and choose which values to retain. Keeping this process regular prevents inflated numbers, fragmented customer histories, and workflow errors.

Step 7: Implement Data Mapping Strategies

Don’t migrate your data immediately because it can lead to mixed-up sections. This is easily solved with mapping your legacy data fields in advance. This, while taking an extra step to improve data quality in Salesforce, will lead to higher system accuracy. For example, provide matching field types or consolidate similar fields.

Again, before you proceed with data transfer, assess your fields and make sure no critical data is left behind. It’ll help you build a more reliable data migration strategy and prevent loss of crucial details. 

Step 8: Conduct Data Migration in Phases

While you shouldn’t delay your shift to Salesforce and maximize its benefits for your operations, it’s as dangerous to go full head-on into data migration. Not only can you get lost in the new interface, but you will also struggle with understanding which data went where, and verifying it would be exhausting.

Some of the best data migration practices suggest migrating your data in manageable phases, starting with non-critical objects. Don’t forget about the Salesforce sandbox environment to test data loads and validate your planned automation flows. This troubleshooting will be useful for assessing what works and, importantly, what will work in your Salesforce system once you finalize it, without the costs of errors in the business environment. 

Step 9: Test Data Post-Migration

After you’ve migrated your data, validate it. No matter how well you think you did, there’s always a chance that something went wrong and your Salesforce fields don’t have everything you need to run smoothly. Run test scenarios in the workflows and randomly sample objects to spot-check for accuracy. Plus, it’ll give you time to adjust to seeing your data in the new system, making readjustment easier. 

Step 10: Monitor and Maintain Data Quality

You have probably guessed that, just like every organism, your Salesforce (including data quality) will change and adapt to new inputs and updates, meaning it won’t stay the same. Monitoring will guarantee a more reliable process, and those standards you focused on in step 3 will be reinforced across all levels.

Monitor data quality using tools like Salesforce Einstein Analytics — a great option for real-time monitoring and keeping in touch without delays. Schedule regular data cleanups; perhaps you want to do them before regular Salesforce updates and pair this up with an audit. If you can, ensure regular maintenance as well.

Tools for Maintaining Data Integrity

Fortunately, there’s no need to maintain data integrity (only) manually — plenty of instruments can make it easier and more accessible, keeping the load of updates and checks manageable. 

Salesforce Data Loader

Salesforce Data Loader is a tool designed for bulk data import, export, and update. It simplifies data management by targeting large volumes of records, up to 5 million. It is particularly useful for the implementation and data migration stages. Salesforce Data Loader has drag-and-drop field mapping, support for all objects (including custom ones), success and error log files in CSV, and a built-in CSV file viewer. 

MuleSoft

MuleSoft is a platform that provides seamless integration between Salesforce and external systems, including ERP solutions and legacy databases. With it, teams address the data migration error issue in advance. MuleSoft reliably connects all the data in one platform, allowing it to flow freely in real time. Plus, this tool has API management and data transformation features that make formatting easier and enhance the exchange among the systems faster and without mix-ups. 

Duplicate Check

Duplicate Check is a Salesforce-native instrument that helps with identifying, merging, and deleting duplicates in the system. Some of its key features are real-time duplicate prevention during data entry, batch deduplication for cleaning up existing records, and cross-object duplicate scanning. It’s user-friendly and easy to apply and ensures that Salesforce users don’t log in objects and record duplicates by tracking them from record pages without using code.

Setting the Building Blocks of Data Integrity

Your Salesforce implementation isn’t complete until your data works for you, not against you. It’s what your team will rely on from starters. Planning, structure, and a team-based approach are key to maintaining data integrity in Salesforce. And even though it takes time and effort, the rewards are much more immense — a scalable CRM that works for your business.

Do you try to maintain your Salesforce data integrity and need help making it a long-term strategy? Our team can help you handle your data efficiently by developing a flexible solution with minimum manual effort and smooth integrations with other platforms. Contact us today.