salesforce data cleansing

Messy Salesforce data is a major obstacle. 

Imagine trying to run a campaign with duplicate records, incomplete addresses & outdated information. These data issues cost your business money & erode trust.

In fact, according to Experian, organizations estimate that up to one-third of their CRM data might be inaccurate, while 55% of business leaders report a lack of trust in their data assets.

When your data is inaccurate, business activities become a risky gamble. Marketing campaigns miss their mark, sales teams chase the wrong leads, and customer satisfaction drops. Your sales and marketing managers are stressed about the numbers, while your tech and IT teams are too busy with other tasks to bother about clean CRM data

But there’s hope. 

This guide tackles these deep-seated issues with effective Salesforce data cleansing practices. We’ll explore common problems like inconsistent data, duplicates, and poor integration, and show you how to transform your CRM into a powerful tool for success.

Ready to simplify your data management, save resources & enhance your business outcomes with clean, reliable data? 

Let’s dig in.

What is Bad Salesforce Data?

Bad Salesforce Data

Bad Salesforce data includes duplicate records, incomplete addresses & outdated information. Duplicate records happen when the same person or company is entered into your system multiple times. 

This can lead to confusion, wasted time & missed opportunities as your team might contact the same lead multiple times or, worse, not at all. Incomplete addresses are another common issue. 

When you don’t have all the necessary information, like a full mailing address, it becomes challenging to reach out to your customers, send marketing materials, or even deliver products.

Outdated information is equally problematic. 

Imagine trying to connect with a customer using an email address they no longer use or calling a phone number that has been disconnected. These scenarios are not just annoying, they can lead to lost sales and damage your company’s reputation.

The common issues caused by bad data don’t stop there. They ripple through your entire business process, affecting marketing campaigns, sales strategies, and customer service efforts.

Understanding what constitutes bad Salesforce data is the first step in addressing these deep-seated issues. 

By recognizing the impact of duplicate records, incomplete addresses & outdated information, you can begin to see the importance of maintaining clean, accurate data.

This awareness sets the stage for implementing effective data cleansing practices that will transform your Salesforce into a powerful tool for success.

Your Salesforce data should be an asset, not a liability.

Data Quality Metrics

Data Quality Metrics

Ever wondered why your Salesforce data feels unreliable? Measuring data quality is crucial to maintaining an effective CRM system. Let’s explore the key metrics that ensure your data is trustworthy and how they impact your business decisions.

Completeness 

It means having all the necessary information for every record. Missing data, like an email address or phone number, can cripple your marketing and sales efforts. 

When critical data is absent, you can’t reach out to leads, nurture prospects, or close deals efficiently. Completeness ensures your data is whole and actionable.

Accuracy 

Accuracy means the data correctly represents reality. Incorrect details, such as wrong job titles or outdated contact information, lead to misinformed decisions. 

For example, sending a personalized email to a former employee rather than the current decision-maker can waste resources and harm your reputation. 

Consistency 

This ensures data is uniform across your system. Inconsistent data occurs when the same information is recorded differently in multiple places. 

For instance, one record might list a company as “ACME Corp.” while another says “ACME Corporation.” This inconsistency makes it hard to generate reliable reports and insights. 

Consistency guarantees that your data is harmonized and reliable.

Timeliness 

Keeping data up-to-date. Outdated information, such as an old address or an expired contract date, can lead to missed opportunities and poor customer service. 

Timely data helps you respond quickly to changes. This ensures your strategies are always based on the latest information.

Uniqueness

Uniqueness involves ensuring each record is unique, with no duplicates. Duplicate records can result in confusion and inefficiency. 

Imagine two sales reps unknowingly reaching out to the same lead. It’s not just embarrassing but also a waste of effort. 

Uniqueness maintains the integrity of your CRM data, ensuring each contact is singular and distinct.

These metrics directly affect your CRM’s effectiveness:

  • Business Decisions: Reliable data enables informed decisions, minimizing risks and maximizing opportunities.

 

  • Marketing Efficiency: Accurate and complete data ensures your campaigns reach the right audience.

 

  • Sales Productivity: Timely and unique data helps sales teams focus on real prospects, not chasing shadows.

 

  • Customer Satisfaction: Consistent and accurate data improves customer interactions, fostering trust and loyalty.

Tip: Regularly review & update your data entry guidelines. Even the smallest tweaks can make a huge difference in maintaining data quality.

Data Capture (for Completeness and Timeliness)

Capturing data accurately and completely is essential for Salesforce data cleansing. To achieve this, you need to follow best practices that ensure the data you collect is reliable and timely. Let’s explore these practices, the tools you can use & the importance of validation rules and automation.

Best Practices for Capturing Data Accurately and Completely

  • Standardize Data Entry Processes: Establish clear guidelines for how data should be entered. Consistent data entry rules reduce errors and ensure uniformity.

 

  • Mandatory Fields: Identify critical data points and make them mandatory. This ensures that essential information is always captured.

 

  • Training and Education: Regularly train your team on the importance of data accuracy and completeness. Educated users are more likely to enter data correctly.

Tools and Methods to Ensure Timely Data Entry

  • Automated Data Capture Tools: Use tools that automate data entry, such as web forms that feed directly into Salesforce. This reduces manual entry errors and speeds up the process.

 

  • RealTime Data Integration: Implement real-time data integration solutions that automatically update Salesforce with new information from other systems. This ensures that your data is always current.

 

  • Mobile Data Entry Solutions: Provide your team with mobile solutions to capture data on the go. This is especially useful for sales reps and field agents who need to update data immediately.

 

  • Salesforce Integration Feature: Use software that offers a connector for Salesforce, such as WinPure, which allows users to automatically load and select specific columns of Salesforce data they want to fix. This feature streamlines the data cleansing process by providing a seamless connection to Salesforce, ensuring that the correct data is consistently updated and maintained without manual intervention.

sandbox salesforce (1)

What Is A Sandbox & When Do You Need One?

WinPure enables users to use a Sandbox environment to develop, test, and treat their data without affecting their current database. For businesses that have years of complex datasets on Salesforce, a Sandbox environment allows them to conduct thorough testing using copies of the actual production data.

WinPure is the only DQM solution that allows a direct integration with Salesforce data and the ability to create a Sandbox environment with a single click. Once done, users simply need to select the columns they want to profile, clean, and dedupe. It’s as easy as 1,2,3!

Address Standardization

Address standardization involves formatting and validating postal addresses to match a standard format, which aligns with government databases. Key steps in address standardization include:

  • Parsing Address Data: Break down addresses into components like street name, city, and postal code.

 

  • Formatting: Ensure addresses follow a standardized format, such as using uppercase letters for postal codes.

 

  • Validation & Verification: Cross-refer addresses with government databases to confirm their validity and deliverability.

Importance of Validation Rules and Automation in Data Capture

  • Validation Rules: Set up validation rules in Salesforce to ensure data meets specific criteria before it is saved. For example, you can require email addresses to follow a standard format or phone numbers to be of a certain length.

 

  • Automation: Automate repetitive tasks such as data cleaning and deduplication. Automation tools can regularly check for and correct errors, ensuring your data remains accurate over time.

 

  • Scheduled Data Audits: Regularly schedule data audits to review and clean your data. This helps identify and correct issues before they become significant problems.

Deduplication (for Uniqueness)

Duplicate data often occurs when the same person or company is entered into your system multiple times, typically due to inconsistent data entry or system integration issues. This can create a false impression of your data, such as believing you have 10% more leads than you actually do.

Identifying and eliminating these duplicates is essential for maintaining a clean, efficient database. 

Let’s talk about methods, tools & benefits…

Methods to Identify & Eliminate Duplicate Records

The first step in deduplication is identifying where duplicates exist. This process can be complex, but it’s crucial for ensuring your data’s uniqueness. 

Start by examining common fields such as email addresses, phone numbers, and names. Look for patterns and inconsistencies. Advanced techniques like fuzzy matching can help identify duplicates that aren’t exact matches but are close enough to be problematic. This method compares records based on similarity, catching those tricky duplicates that slip through exact matching processes.

Once duplicates are identified, elimination involves merging or removing redundant records. It’s important to consolidate all relevant information into a single, accurate record. This might involve manual review or automated merging processes, depending on the complexity and volume of your data.

Tools and Techniques for Effective Deduplication

Salesforce offers built-in tools like Duplicate Management, which helps identify and merge duplicates based on predefined rules. 

You can customize these rules to match your specific needs, focusing on fields that are most prone to duplication.

Third-party tools also offer advanced deduplication capabilities. Solutions like WinPure, for example, provide sophisticated matching algorithms and user-friendly interfaces for managing duplicates. 

While Salesforce offers built-in duplicate management, third-party tools like WinPure provide enhanced capabilities that go beyond the basics. WinPure’s AI entity resolution is designed for scale, offering unmatched accuracy & speed. 

It can transform 1 million records in just 3 minutes, ensuring data consistency and reliability. In the same way, WinPure’s no-code solution is easy for both business & non-tech users.

WinPure data matching results
Fuzzy data match results window

Benefits of Maintaining Unique Records for CRM Performance

Maintaining unique records improves the accuracy of your data, ensuring that your marketing and sales teams have reliable information to work with. This leads to better-targeted campaigns and more effective sales strategies.

Unique records also enhance customer relationships. When your data is clean, you can provide a more personalized experience for each customer. This builds trust and loyalty, driving customer satisfaction and retention.

In the same way, unique records streamline your operations. With no duplicates cluttering your system, your team can work more efficiently, saving time and reducing frustration. 

Clean data also improves reporting and analytics, providing clearer insights and supporting better decision-making.

Pro Tip: Consider scheduling a ‘Duplicate-Free Friday’ where your team dedicates a bit of time to identifying & resolving duplicates. A little goes a long way!

8 Actions to Take Towards Better Salesforce Data Quality

Here are eight actions that will help you improve Salesforce data quality effectively.

  • Regular Data Audits

Conduct regular audits to identify and rectify errors as part of your data cleaning Salesforce strategy. Schedule these audits to catch issues early before they snowball into bigger problems. Regular checks help maintain data integrity and trustworthiness.

  • Implementing Validation Rules

Set up validation rules in Salesforce to ensure data is entered correctly. These rules act as gatekeepers, blocking incorrect or incomplete data from being saved. For example, requiring an email address to have the correct format prevents future communication issues.

  • Standardizing Data Entry Processes

Create and enforce standardized data entry procedures. Consistency in data entry minimizes errors and ensures uniformity across your records. Provide clear guidelines and templates to your team for entering data.

  • Using Automated Tools for Data Cleaning

Automated tools can handle tasks like removing duplicates, correcting typos, and updating outdated information. In the same way, choosing the right tool can make a significant difference. Make sure to know what you want from the tool. 

Whether it’s total data management or precise data matching to eliminate duplicates, having a clear goal helps in selecting the right tool for your needs.

  • Training Staff on Data Quality Importance

Educate your staff on the importance of data quality. Make sure they understand how their actions impact the overall health of your CRM data. Regular training sessions can reinforce best practices and keep everyone on the same page.

  • Monitoring Data Quality Continuously

Establish continuous monitoring of your data quality. Use dashboards and reports to track key metrics and identify trends. Continuous monitoring allows you to respond quickly to any issues that arise.

  • Integrating Data Sources Properly

Ensure all your data sources are properly integrated. This integration prevents fragmented data and ensures that all information flows seamlessly into Salesforce. Proper integration improves data accuracy and completeness.

  • Setting Up a Data Governance Framework

Develop a data governance framework to manage and protect your data. This framework should outline policies, procedures, and responsibilities related to data management. A solid governance framework helps maintain data quality and compliance over time.

Creative Insight: Give ‘Data Quality Hero’ badges to team members who keep high data standards. It’s a fun way to encourage good habits & recognize their efforts.

4 Salesforce Data Cleansing Best Practices & Data Quality Standards

Here are four essential practices to ensure your data remains accurate, complete, and reliable.

  • Regularly Scheduled Data Cleaning: One of the most effective ways to maintain data quality is by scheduling regular data cleaning sessions. 

Set a routine to review and clean your data periodically as part of your Salesforce data cleansing best practices. Whether it’s weekly, monthly, or quarterly, consistency is key. Regular cleaning helps identify and rectify issues before they become significant problems, ensuring that your data remains up-to-date and trustworthy.

clean and match
Data clean window with advanced profiling features

 

  • Using Custom Rules & Matrices: Customize your data cleaning rules to fit your specific needs. 

Generic rules might not cover all the nuances of your data, so developing custom matrices allows you to address unique challenges. For example, you can create rules to standardize names, formats, or specific fields unique to your industry.

  • Ensuring Data Consistency Across Platforms: Data consistency is vital for reliable CRM performance. Ensure that data is consistent across all integrated platforms. 

This involves standardizing fields and formats so that information matches wherever it is stored or used. Implement cross-platform validation rules to catch inconsistencies and correct them automatically. Consistent data improves reporting accuracy and enhances decision-making.

  • Advanced Tools for Continuous Improvement: Use advanced data cleansing tools to automate and enhance your cleaning processes. 

These tools offer features like real-time monitoring, automated cleaning & comprehensive reporting. Advanced tools not only make the data cleaning process more efficient but also provide insights into recurring issues, allowing for continuous improvement.

The Best Salesforce Data Cleansing Solution

When it comes to Salesforce data cleansing, having the right tool can make all the difference. WinPure handles all your data cleaning needs efficiently.

WinPure’s data cleansing tool simplifies & automates the data cleaning process. It provides a user-friendly interface that allows both business and technical users to manage data quality without the need for complex coding or manual intervention. 

The tool supports a wide range of data sources, ensuring that you can clean data from multiple platforms seamlessly.

Key Features and Benefits:

  • Automated Cleaning: WinPure automates the data cleaning process, reducing the time and effort required to maintain data quality.

 

  • Custom Rules: The tool allows you to create custom cleaning rules for your specific needs.

 

  • Address Parsing: WinPure includes advanced address parsing capabilities, breaking down complex address strings into standardized components.

 

  • Data Matching: The tool’s powerful data matching algorithms identify and eliminate duplicate records, ensuring that each entry is unique and reliable.

 

  • UserFriendly Interface: The intuitive interface makes it easy for users to set up and manage data cleaning processes without technical expertise.

Real-World Examples and Case Studies

WinPure has helped many organizations clean up their data. Here are three examples:

Centura Health

Centura Health had a lot of messy data from different sources. They needed to combine donor information into one clear view. Kevin Lee, their Data Manager, said they used to match data by hand, which took a lot of time and often missed important details.

Using WinPure, they automated the data matching and merging process. This saved a lot of time and made their donor records much more accurate, helping them run their operations smoothly.

Luton Borough Council

Luton Borough Council needed a tool to clean up their old housing data while moving to a new system. Alan Kirk from their Information Management Department said their data was messy because it was entered in free text, causing many errors.

With WinPure Clean & Match, they quickly matched and merged property data. The tool was fast and easy to use, helping them clean up their data and make better decisions.

England Hockey

England Hockey had a CRM with over 162,000 addresses entered in different formats. This caused many duplicates and data management problems.

Using WinPure Clean & Match with Address Verification, they standardized their addresses and merged duplicates. This reduced their mailing returns from 10% to under 1%, improving data quality and boosting staff confidence in their CRM.

The Bottom Line

Why gamble with dirty data when you can win with a clean Salesforce? Keeping your Salesforce data clean is like making sure your tools are sharp and ready. Messy data can lead to missed opportunities, wasted time & frustrated customers. 

Regular audits, using the right tools like WinPure & training your team can make a huge difference. Remember, clean data is the foundation of smart decisions, better marketing, and happier customers. So, invest the time to keep your data tidy and watch your business thrive.

Written by Faisal Khan

Faisal Khan is a human-centric Content Specialist who bridges the gap between technology companies and their audience by creating content that inspires and educates. He holds a degree in Software Engineering and has worked for companies in technology, healthcare, and E-commerce. At WinPure, he works with the tech, sales, and marketing team to create content that can help SMBs and enterprise organizations solve data quality challenges like data matching, entity resolution and master data management. Faisal is a night owl who enjoys writing tech content in the dead of the night 😉

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