6 best practices for Salesforce data management

With the influx of information that businesses collect from their customers, it’s no surprise that organizations rely on their customer relationship management (CRM) systems to help them parse that data. With 23% of the global CRM market, Salesforce is one of the industry leaders.

But even with Salesforce, you still need to manage that data correctly. That’s why Salesforce data management is a crucial facet of any business that uses Salesforce. 

What is data management?

Data management is the process of collecting, organizing, and using an organization’s data securely and efficiently. Data management aims to help organizations get the most out of their data.

For many organizations, a successful data management strategy wouldn’t be possible without using a CRM like Salesforce. With so much data available to organizations, Salesforce helps make the management and organization of data more efficient.  

Why it is important to manage your Salesforce data

Data management goes far beyond building organizational efficiency—although that is one of the main benefits of managing your Salesforce data. Effective data management is essential for the success of sales teams. 

When you invest time and resources into data management, you improve your data quality and better understand the deal lifecycle. High-quality data leads to better decision-making, increased CRM adoption, improved customer experience, and increased revenue. 

With a Salesforce data management process in place, you can ensure your data is updated, exhaustive, and error-free. This kind of clean data means sales teams can make informed decisions that support the organization’s business goals and close more deals faster.

Challenges in managing Salesforce data

Customer data is critical for sales teams to improve their decision-making process. But as we touched on above, this is only true when sellers are dealing with high-quality data that is up-to-date, accurate, and complete. 

Organizations process more information than ever, and it comes from multiple data sources. As the volume of complex data organizations manage continues to increase, the challenges teams face also have the potential to grow. These challenges include:

• Duplicate records. You can run into issues when data is entered into the Salesforce platform more than once. For example, suppose you have two entries for the same customer. In that case, they may receive automated emails twice, and any reports or dashboards you generate will be inaccurate because of the duplicate data.  

• Out-of-date data. Out-of-date data can lead to missed opportunities and customer dissatisfaction. If you’re contacting the wrong individual because your records are outdated, you may miss out on closing a deal.

• Loss of important records. When managing multiple databases across several spreadsheets or cloud locations, losing track of important information can be easy. You can streamline data collection when you manage your data in a single location, like a CRM. 

• Inconsistency in data entry. When there isn’t a clear process for inputting data, records can become inconsistent. For example, if you don’t have set fields for data collection, you may end up with the wrong information in the wrong field, causing reports and records to be inaccurate. Salesforce validation rules can help ensure data entered in records meets your requirements.

• Data privacy and security. Collecting customer data brings with it concerns surrounding privacy and security. You can mitigate these concerns with a sound data management policy in place that ensures all personal data is secure.  

With proper data management, you can avoid these and other challenges. To ensure you’re on the right track, implement organization-wide standards, policies, and workflows for data acquisition, assessment, cleaning, and storage. 

When everyone within your organization knows how to input, access, and process data through the Salesforce ecosystem, your data will be more reliable and good enough for data-driven decision-making.  

Salesforce data management best practices

Some best practices can help manage Salesforce data effectively, including:

• Identify the data you need
• Enhance the quality of your data
• Integrate your third-party data with Salesforce data
• Consider data privacy and governance concerns
• Make keeping your data clean a priority
• Get the most from automation

Let’s explore each best practice and how they can help you execute successful data management for your organization. 

1. Identify and collect necessary data in Salesforce

The kind of customer data you choose to collect can have a significant impact on your ability to close deals. You can use data to uncover warm introductions, guide your decision-making processes, and help prioritize customer accounts. 

Depending on your business processes and how you plan to use your information, there are four main data types to consider:

1. Identity data is unique to one customer or lead. This includes name, mailing information, telephone and email address, social media accounts, etc.
2. Descriptive data is contextual information that helps you learn more about a lead or customer. This includes job title, industry, education level, organizational size, etc.
3. Qualitative data encompasses things that aren’t easily measured by numbers, like behaviors, feelings, and motivations. Qualitative data helps to describe what a customer “thinks” or “feels” about your product, service, or business.
4. Quantitative data measures behaviors or feelings by looking at numerical data points. Quantitative datasets use numeric metrics, making this data perfect for reporting and analysis. This includes the number of times a customer clicks an email, visits your website, makes a purchase, etc.

Consider how you’ll use this information to drive more sales when determining what data you should collect. Typically, using a mix of all four data types will yield the best results for your business. 

You’ll need to use various tactics to collect this data. Some data, like name and job title, are easily found through online research. For quantitative data, you’ll need to look at the data you’ve collected as a business. And finally, qualitative data is captured via first-hand conversations, surveys, or questionnaires conducted by your company or a third party on your behalf.

2. Improve data quality

Having the highest quality data gives your sales team the best chance of closing deals and increasing revenue. Ideally, you’d start with a clean slate with high-quality data. However, businesses frequently adopt data management practices after already collecting customer data. 

These four tips can help you improve your data quality:

• Create a duplicate management process: Merge any duplicate records in Salesforce to ensure your database is clean and only has unique records.
• Eliminate silos through data integration: Often, different teams across an organization gather data separately, and that data often overlaps. This can cause duplicate data or records that mutually exclude each other. By eliminating silos, you can dramatically improve data quality.
• Share data: When everyone in your organization has access to all company data, it becomes a source of valuable insights. If you don’t share data across all teams, consider giving everyone access—it may lead to unexpected observations and decisions.
• Standardize data: Spend time auditing your current data to remove mistakes, correct mislabeled data, and archive unnecessary data. 

3. Establish a data governance model

Organizations cannot gather customer information without their consent. Across the globe, laws govern the collection and use of customer data—for example, GDPR in the EU, CCPA in California, and PIPEDA in Canada.

Salesforce’s consent data management model makes your customers’ privacy a primary concern and helps ensure you stay compliant. Salesforce allows you to manage consent at multiple levels, from global preferences to more specific use cases. This data governance model takes a long-term approach to consent and focuses on the customer’s entire experience instead of a single contact point.

4. Prioritize data hygiene

While your work to improve data quality should create a CRM full of high-quality data, it’s still important to prioritize data hygiene. 

Schedule and perform regular audits to ensure that your data is clean and up to your quality standards. Ensure you’ve set data quality standards in your management processes so that you know what does and doesn’t meet the mark. Consider setting benchmarks for: 

• Accuracy
• Uniqueness
• Accessibility
• Integrity 
• Timeliness
• Purpose
• Consistency

5. Integrate your third-party data with Salesforce data

Getting information into and out of Salesforce from other applications gives you flexibility and the ability to bring your data together in one place.

Import 

To import data into Salesforce from third-party applications, there are three options to consider:

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1. Data Import Wizard. A Salesforce application that allows you to manually import up to 50,000 objects—contacts, leads, accounts—from a CSV file, Excel spreadsheet, or Google Sheets.  
2. Data Loader. With the same functionality as Data Import Wizard, use this Salesforce application when your data type isn’t supported or you need to import more than 50,000 items. 
3. Affinity for Salesforce. Ditch the manual data import and automatically import inbox and calendar activity from across your company to create, update, and enrich Salesforce records.

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Export

It’s important to export your data from Salesforce so that you can maintain a backup of all your data. Salesforce provides you with two options for data export:

1. Data Export Service. A Salesforce solution that allows you to export data manually or automatically once in seven or 29 days—depending on the edition of Salesforce.
2. Data Loader. A convenient way to export your data, especially when you have many items. Data Loader supports up to 5 million records. 

6. Use automation to manage your data

Data management is a time-consuming process critical to your business’s success. Finding effective ways to automate some of the processes can save your organization time and money. 

Affinity for Salesforce analyzes emails and meetings to create and update contact records in Salesforce automatically. By automating CRM data entry and record enrichment, Affinity saves each seller up to 200 hours of manual data entry annually and helps keep your data clean, up-to-date, and accurate. 

With relationship insights automatically generated by Affinity for Salesforce from your data, sellers can prioritize the right opportunities and discover warm introductions that close deals up to 25% faster. 

Manage your data with Affinity for Salesforce

Try Affinity for Salesforce today and see how much more your sales team can do with clean, enriched Salesforce data. 

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Salesforce data management FAQs 

What is Salesforce data management?

Salesforce data management is the process of collecting, organizing, and storing data securely in your Salesforce org. 

What is the best tool to help manage your Salesforce data?

The best tool to use to help you manage your Salesforce data is Affinity for Salesforce. With automated activity capture, Affinity for Salesforce saves each team member 200+ hours of manual data entry per year. It integrates with your inbox and calendar to capture all engagement activities, automatically updates Salesforce records, and enriches them with the information you need to make data-driven decisions.

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