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What Is CRM Data Cleansing?
CRM data cleansing is the process of identifying and correcting or removing inaccurate, incomplete, or irrelevant data within a Customer Relationship Management (CRM) system.
It involves steps such as validating data, removing duplicate data, correcting errors, and standardizing formats to ensure consistency. The goal is to maintain accurate and reliable customer information for effective CRM usage.
Now that you understand the basics, let’s check out why clean CRM data is crucial for your sales organization.
Why Is Clean CRM Data Important?
Based on our experience of working with clean CRM data, here are some of the key benefits we’ve observed:
- Accuracy and Reliability: Clean data ensures that the customer information is precise and trustworthy, providing a solid foundation for all CRM activities.
- Sales Efficiency and Forecasting: Working with high quality data increases sales efficiency by providing accurate data that helps in identifying and prioritizing leads and opportunities. It also enhances sales forecasting by delivering reliable insights for predicting future sales trends.
- Business Performance: Clean and accurate data enhances overall business performance and customer satisfaction by ensuring that each customer interaction is based on reliable, up-to-date information.
So, what kind of data should you tidy up?
7 Examples of CRM Data That Requires Cleaning
Maintaining a clean CRM database is vital for effective customer relationship management. To ensure your system remains efficient and reliable, we’ll take you through the common examples of bad data that require cleaning:
- Duplicate Records: Instances where the same customer or contact is entered multiple times, leading to redundancy and confusion.
- Incomplete Information: Missing information or records that lack essential details such as phone numbers, email addresses, or job titles — making them less useful for communication and analysis.
- Inaccurate Data: Bad data and incorrect information, such as misspelled names, wrong addresses, or outdated information (like contact details) that can lead to miscommunication.
- Data With Inconsistent Formatting: Variations in data entry formats, such as different date formats, inconsistent use of capitalization, or varying address formats, that hinder data analysis.
- Outdated Records: Information about customers or contacts that is no longer relevant, such as former employees or clients who have moved on, which can clutter the CRM system.
- Invalid Data: Entries that contain placeholder text (e.g., "N/A" or "123456") or invalid data, which can skew analytics and reporting.
- Unlinked Records: Customer data that is not properly associated with related records, such as transactions or interactions, can lead to an incomplete view of the customer's history and behavior. This makes it challenging to provide personalized service and accurately analyze customer activity.
By now, you should be able to easily spot dirty data in your CRM. And once that’s out of the way, the next step is to clean the data by following the appropriate steps and best practices.
10 Steps to Perform a Comprehensive CRM Data Cleansing
Cleaning your CRM data involves several key steps to ensure the data is accurate, complete, and up-to-date.
To simplify things for you, we’ll take you through the process we usually follow when cleaning CRM data:
- Step# 1: Data Audit
- Step# 2: Define Data Standards
- Step# 3: Data Deduplication
- Step# 4: Data Validation
- Step# 5: Data Enrichment
- Step# 6: Standardization
- Step# 7: Data Purging
- Step# 8: Link Related Records
- Step# 9: Continuous Monitoring and Automation
- Step# 10: Training and Best Practices
Step# 1: Data Audit
Conduct a thorough review of the existing data to identify inconsistencies, duplicate data, inaccuracies, and incomplete records. This initial step helps you understand the scope and nature of the data quality issues — allowing you to prioritize areas that need immediate attention.
Step# 2: Define Data Standards
Establish guidelines for data entry formats, required fields, and validation rules to ensure consistency and accuracy. This helps prevent future data quality problems by providing a uniform approach to data management across the organization.
Step# 3: Data Deduplication
Identify and merge duplicate records to eliminate redundancy and confusion. This step ensures that each customer or contact has a single, consolidated record.
Step# 4: Data Validation
Verify the accuracy of the data by cross-referencing with reliable sources and correcting any errors found. This helps maintain the integrity and reliability of the CRM data.
Step# 5: Data Enrichment
Supplement incomplete records with missing information from reliable external sources. Enriched data provides a more comprehensive view of each customer — enhancing your ability to personalize every customer interaction and improve customer satisfaction.
Step# 6: Standardization
Ensure consistent formatting across all records, such as standardized address formats, phone number formats, and capitalization. This makes the data easier to manage and analyze.
Step# 7: Data Purging
Remove outdated information, irrelevant data, or invalid records to keep the CRM system uncluttered and efficient. This process helps maintain the overall quality and relevance of the data.
Step# 8: Link Related Records
Ensure all customer data is properly associated with related records, such as transactions and interactions. This provides a complete view of each customer’s history and behavior.
Step# 9: Continuous Monitoring and Automation
Implement ongoing monitoring and maintenance processes to keep the data clean and up-to-date. Regular checks and updates prevent data degradation over time. Also, automating data entry and collection can further enhance data accuracy and consistency.
Step# 10: Training and Best Practices
Train staff on the importance of data hygiene and best practices for data entry and maintenance.
Educated staff can help sustain CRM data hygiene and prevent future issues by following standardized procedures and recognizing the value of clean data.
And that’s it — you now know the top secrets of CRM data cleaning. Now, if you’re serious about performing an accurate CRM data cleaning, you need to get your hands on the right tools.
Top 4 CRM Data Cleansing Tools in 2024
After testing out various data cleansing tools, we have identified the most effective ones that significantly improve the accuracy and reliability of a CRM database. Here are our top picks:
1. Scratchpad
Scratchpad is an AI-powered Salesforce add-on that improves CRM hygiene by making it easier for frontline sales reps to manage their pipelines while providing better visibility into that data for Ops and sales leaders.
It integrates directly into existing workflows — offering instant visibility and control over the sales process and CRM data management.
With Scratchpad, you’re able to identify gaps in open pipeline and understand changes in real-time, ensuring data remains accurate and up-to-date.
Here are the key benefits of using Scratchpad:
- Data Accuracy and Insight: Scratchpad helps you maintain high quality data in Salesforce, which in turn enables better analysis, segmentation, and targeting of prospects based on reliable information.
- AI Sales Assistant: The Scratchpad Sales AI Assistant monitors your virtual sales calls and autonomously updates Salesforce with crucial details (like MEDDIC, next steps, and more). It also generates easily shareable sales call summaries and transforms these conversations into valuable insights.
- Unified Sales Workspace: Scratchpad combines sales notes, tasks, Kanban boards, and more in one place — making it a centralized hub where the sales manager or sales rep can easily manage all sales activities.
- Zero Boards: Scratchpad provides daily to-do lists so that you never forget to follow up on leads and/or opportunities in the pipeline.
- Process Adherence: Scratchpad enhances process adherence by streamlining Salesforce interactions, ensuring every sales rep maintains essential processes efficiently. It offers intuitive views and workflow tiles — making it easier to manage and correct data in real-time.
Rating
- G2: 4.8/5 ⭐ (1,445+ Reviews)
- Capterra: 4.9/5 ⭐ (96+ Reviews)
Pricing
- Has a free plan
- Paid plans start at $19 per user/month
2. WinPure Clean & Match
WinPure Clean & Match is a powerful data scrubbing tool that improves the quality of business data and contact information by identifying and eliminating duplicates, correcting errors, and standardizing information, as well as addressing missing data.
Its intuitive interface and powerful algorithms allow users to efficiently clean and deduplicate data from multiple sources. This ensures consistency and accuracy across databases, thereby enhancing overall data quality management.
Rating
- G2: 4.7/5 ⭐ (73+ Reviews)
- Capterra: 5/5 ⭐ (2+ Reviews)
Pricing
- Offers custom pricing plans
3. Experian Aperture Data Studio
Experian Aperture Data Studio is a powerful tool that integrates data profiling, cleansing, and enrichment — offering a complete solution for managing complex data environments. This data cleansing tool enables organizations to gain deeper insights into their data quality, identify and rectify issues, and enhance data for improved analytics and reporting.
With its user-friendly interface and advanced features, Aperture Data Studio helps businesses maintain high data standards and drive better business outcomes.
Rating
- G2: 4.8/5 ⭐ (2+ Reviews)
- Capterra: N/A
Pricing
- Has a free trial
- Offers custom pricing plans
4. OpenRefine
OpenRefine, formerly known as Google Refine, is an open-source tool for cleaning and transforming CRM data and contact information.
This data cleansing tool allows you to explore large datasets, fix inconsistencies, and convert data from one format to another through a powerful, yet straightforward interface. It also addresses missing data effectively.
OpenRefine is highly regarded for its flexibility and capability to handle messy data — making it a favorite among data analysts and researchers who are focused on data quality management.
Rating
- G2: 4.6/5 ⭐ (12+ Reviews)
- Capterra: 4/5 ⭐ (1+ Reviews)
Pricing
- Free/open-source
Before we wrap up, let’s demystify some of the additional questions you might have.
2 FAQs About CRM Data Cleansing
To help you understand the CRM data cleanup process better, we've compiled answers to some frequently asked questions:
1. How Often Should You Clean Your CRM Data?
Dirty data in the CRM should be cleaned regularly to maintain its accuracy and reliability. A common recommendation is to perform a thorough data cleaning every 6 to 12 months.
However, the frequency can vary depending on the volume of data and the rate at which it changes. Additionally, implementing ongoing data maintenance practices, such as automated data validation and deduplication, can help keep the data clean continuously.
2. What Are the Challenges of CRM Data Cleaning?
Performing a CRM data cleanup is crucial but can be complex and challenging.
So, we’ll explore the common obstacles businesses face during the data cleanup process and tips on how to overcome them:
- Volume of Data: Managing and cleaning large volumes of data can be time-consuming and resource-intensive. To overcome this, use automated CRM cleansing tools that can efficiently process large datasets, such as data deduplication software and batch processing systems. Additionally, schedule regular data maintenance to ensure CRM data hygiene and keep the workload manageable.
- User Errors: Human errors in data mining and data entry can introduce inaccuracies and inconsistencies that need to be corrected. To tackle this, standardize data entry procedures and provide regular training for employees to minimize errors. Also, use data validation rules and automated error detection tools to identify and correct inaccuracies promptly.
- Cost: Investing in data scrubbing tools and processes can be expensive, especially for small and medium-sized businesses. To overcome this, start with affordable or open-source data cleansing tools and gradually scale up as your budget allows. Also, prioritize essential data cleansing tasks to maximize the impact of your investment.
Clean Your CRM Data Hassle-Free With Scratchpad
Effective CRM cleaning is crucial for maintaining accurate, reliable, and up-to-date customer information. By following the essential CRM data cleanup tips we’ve outlined, you can significantly improve CRM data hygiene and enhance sales efficiency.
The good news is that there are tons of data cleansing tools that can help you out. However, picking the right one for your needs might not be straightforward.
But if you’re looking for an easy-to-use, AI-powered tool that can help you clean your CRM data and streamline your sales process, look no further than Scratchpad.
Wondering why?
The tool integrates seamlessly with Salesforce to provide fast updates, easy pipeline management, and real-time visibility into your sales process. It ensures data accuracy and enhances overall sales efficiency by offering a unified workspace for managing all sales activities.
Want to explore if it’s the right CRM data cleansing and sales tool for your needs?
Try Scratchpad for free today!
