How to Dedupe CRM Data for Better Decision Making

Does your CRM have multiple records of a customer but they are all incomplete and messy? 

Time to clean up.

Let’s say you log into your CRM only to find five different records for the same customer, each with slightly different details. This messy, inaccurate data can derail your entire business strategy.

Duplicate data leads to flawed insights, wasted marketing efforts & poor customer experiences.

Effective CRM data deduplication is essential to avoid such issues. 

You’re not alone though, so before you panic, remember that de-duplication is a common challenge for many organizations.

For example, a business we worked with discovered nearly half of their 74,000 records were duplicated at the time of doing a CRM data cleanup. This caused a severe breach of trust between managers and C-level executives, causing internal conflicts and wasted time.

You don’t want this to happen to your business.

This guide is for marketers, CRM managers, and account managers who need to maintain high-quality CRM data for better decision-making.

Let’s get started on making your CRM data accurate and reliable for better business outcomes.

Deduplication Explained: An Introduction to Key Terms

Data deduplication is the process of identifying & removing duplicate records within your CRM. It’s about creating a single, accurate version of each record, ensuring you have a clear and reliable dataset.

Why Does Duplicate Data Exist?

Duplicate data often comes from multiple data entry points, human errors & system migrations. When a customer fills out a form twice or different departments enter the same data in slightly different ways, duplicates occur. 

These duplicates clutter your system and make it hard to get a true picture of your data. 

According to Experian, 94% of organizations believe their customer and prospect data might be inaccurate in some way.

Key Terms in Deduplication

• Master Record: The most accurate and complete version of a record after deduplication. This record is used as the single source of truth.
• Data Cleansing: The process of correcting or removing inaccurate, incomplete, or irrelevant data. This is a crucial step before deduplication.
• Data Matching: Comparing data from different sources to find duplicates. This can be done using algorithms that identify similar records based on predefined criteria.
• Survivorship Rules: These rules determine which data points are kept when duplicates are found. For example, you might choose to keep the most recent address or the most complete record.

The Impact of Effective Deduplication

Effective CRM deduplication reduces clutter, improves data quality & enhances your ability to make informed decisions.

How?

By removing duplicate records, you ensure data accuracy, which directly impacts analytics and strategy. Precise data allows for effective segmentation, targeted marketing, and personalized customer interactions. 

It also streamlines workflows, reducing manual corrections and boosting efficiency.

DMNews states that problems keeping data current cost businesses in the United States more than $600 billion per year, according to a report released by The Data Warehousing Institute.

High-quality data prevents compliance issues and mitigates risks associated with data breaches.

Why Picking the Right Master Record is Important for CRM Deduplication

Imagine you have multiple records for the same customer. One has the correct email but an old phone number. Another has the new phone number but a misspelled name. 

Choosing the right master record is crucial for maintaining accurate and reliable data.

Why is this so important? 

Because the master record becomes your single source of truth. It’s the record that holds the most accurate, up-to-date & complete information. 

When duplicates are found, merging them into the correct master record ensures that you aren’t working with outdated or incorrect data.

Incorrect master records can lead to serious problems. 

You might send marketing materials to the wrong address or fail to recognize a key customer. This not only wastes resources but also damages customer trust and skews your analytics.

Why Should You Remove Duplicate CRM Data?

Duplicate CRM data is more than just a nuisance, it’s a business risk.

Here’s why you need to take deduplication seriously and dedupe CRM data.

Customer Experience

What if a customer receives the same marketing email multiple times. They might feel spammed and undervalued. Duplicates in your CRM can cause this. Each duplicate means potential repetitive or conflicting communication, which can annoy customers and harm your brand’s reputation.

Accurate Analytics

Accurate data is the backbone of reliable analytics. When your CRM is cluttered with duplicates, your insights are skewed. Imagine making strategic decisions based on reports that overestimate your customer base by 20% due to duplicate entries. This can lead to misguided strategies and poor resource allocation.

Cost Efficiency

Duplicates are expensive. Consider the cost of sending multiple mailers to the same address or the time wasted by sales teams contacting the same lead twice. These inefficiencies add up, draining both time and money. By deduplicating your CRM, you streamline operations and reduce unnecessary expenditures.

Compliance and Risk Management

Data privacy laws like GDPR require accurate data management. Duplicate records can lead to compliance issues, putting your company at risk of hefty fines. Ensuring your CRM data is clean and accurate helps maintain compliance and protects your business from legal risks.

Team Efficiency

When teams have access to clean data, they work more efficiently. Sales, marketing, and customer service teams can rely on the CRM for accurate information, reducing time spent verifying details or correcting errors. This boosts productivity and enhances inter-departmental collaboration.

Better Customer Insights

Understanding your customers is key to tailoring your services and products to their needs. Duplicate data fragments the customer journey, making it hard to get a full view of their interactions with your company. Deducing your CRM data allows for a complete, accurate picture of each customer, enabling personalized marketing and improved customer service.

See how MGT Consulting dramatically reduced their data deduplication time from 1-2 weeks to just 15 minutes with WinPure.

Why Determining the Right Master Record Can Be Complicated

Determining the right master record is a critical yet complex task in CRM deduplication. Many businesses struggle with this because it’s not always clear which record holds the most accurate and comprehensive information. Here are some key challenges you might face:

• Inconsistent Data: Different departments might enter data in various formats. For instance, one team might list a customer as “John Doe,” while another records it as “Jonathan Doe.” These inconsistencies make it hard to identify which record is the most accurate.
• Incomplete Records: No single record might have all the necessary information. One entry might have a correct email address, another the right phone number. Merging these requires careful consideration to ensure nothing important is lost.
• Frequent Updates: Customer data frequently changes. Addresses, phone numbers, and emails can all become outdated. Keeping track of these changes and determining which record is the most current is challenging.
• Data Quality: Not all data is reliable. Some records might have been entered with errors or missing crucial information. Deciding which data to trust requires a careful evaluation of data quality.
• Manual Processes: Often, businesses rely on manual processes to select master records. This is time-consuming and prone to human error, leading to inconsistencies and mistakes.
• Conflicting Information: Different records might have conflicting information, such as two different addresses for the same customer. Resolving these conflicts requires a clear set of rules and careful judgment.

Understanding these challenges is the first step towards effective CRM deduplication.

Common Practices for Picking a Master Record

Let’s explore the common practices for selecting a master record effectively.

Learn how to define audit objectives & scope to effectively clean your CRM data

Here are practical methods that can help you avoid duplication and data inaccuracies:

Establish Clear Criteria

Defining clear criteria for what makes a record the master is crucial. This could include data completeness, accuracy, and relevance. 

Establish rules like:

• The most recent update date.
• The record with the most complete information.
• The highest quality source (e.g., verified customer data).

Use Automated Tools

Automated tools like WinPure can streamline the selection process. These tools can apply predefined rules & criteria consistently, reducing the risk of human error. 

They can also handle large datasets more efficiently than manual processes.

Data Profiling

Perform thorough data profiling to assess the quality and completeness of your records. This helps in identifying which records are most accurate and should be considered as masters.

Regular Updates

Set up regular data update schedules. Ensuring that your data is consistently updated helps maintain the accuracy of your master records. Regularly refreshing data sources prevents outdated information from becoming the master record.

Merge Rules

Define merge rules that specify how data should be combined. For instance:

• Always keep the latest address.
• Combine phone numbers and emails if they differ.
• Retain all unique information from duplicates.

Manual Review

Despite automation, a manual review can sometimes be necessary, especially for critical records. Having a data steward review the selected master records ensures that the automated process aligns with business requirements.

Centralized Data Governance

Implementing centralized data governance ensures that the master record selection criteria are consistent across the organization. This centralized approach helps in maintaining data integrity and reliability.

Regular Audits

Conduct regular audits of your CRM data. This helps in identifying any issues with master record selection and ensures ongoing data quality. Regular audits can catch discrepancies early and prevent them from causing larger problems.

Example Criteria for Master Record Selection:

• Date of Last Update: Prefer records with the most recent updates.
• Data Completeness: Select records with the most complete set of fields.
• Data Source: Choose records from the most reliable and verified sources.
• Frequency of Use: Prioritize records that are most frequently accessed or used by your team.

Customizing Merge Behavior with Multi-Step Master Selection Rules

This process involves setting up detailed rules to determine which records should be merged and how to choose the most accurate master record.

To start, you need to define criteria for selecting the master record. These criteria might include the date of the last update, the completeness of the record, or the source’s reliability. 

By setting these rules, you ensure that your data remains consistent and accurate.

Steps to Customize Merge Behavior:

1. Define Selection Criteria: Determine what makes a record the master. This could be based on the latest update, data completeness, or source reliability.
2. Set Up Multi–Step Rules: Create multiple rules to cover different scenarios. For example, one rule might prioritize the most recent data, while another focuses on the most complete data.
3. Implement Automated Tools: Use automated tools to apply these rules consistently across your dataset. Automation reduces human error and ensures uniform application of your criteria.
4. Review and Adjust: Regularly review your rules and adjust them as necessary to accommodate changes in your data sources or business requirements.

Recommended Best Practices for Effective Deduplication Process

Following best practices ensures that you handle duplicates efficiently and maintain data integrity.

Best Practices for Deduplication:

• Data Profiling: Begin with thorough data profiling to understand the quality and structure of your data. Identify common issues like formatting inconsistencies and missing values.
• Regular Data Cleansing: Implement regular data cleansing routines to keep your data free from errors. Use tools that offer one-click data cleansing to simplify the process.
• Automated Deduplication Tools: Use automated CRM deduplication software to handle large datasets efficiently. These tools apply complex algorithms to identify and eliminate duplicates without manual intervention.
• Consistent Update Schedules: Maintain a consistent schedule for updating your CRM data. Regular updates ensure that your deduplication efforts are current and relevant.
• Merge and Survivorship Rules: Define clear rules for merging records and deciding which data points to keep. This helps maintain data accuracy and ensures important information is not lost.
• Regular Audits: Conduct regular audits to review the effectiveness of your deduplication process. Audits help identify any issues and ensure ongoing data quality.

Flexible Master Record Selection Rules & CRM Deduplication

Different scenarios may require different rules, and having the ability to customize these rules ensures your data remains accurate and reliable.

Key Aspects of Flexible Master Record Selection:

• Dynamic Criteria: Use dynamic criteria that can be adjusted based on the context. For example, prioritizing the most recent data for certain records while choosing the most complete data for others.
• Scenario–Based Rules: Develop rules based on specific scenarios. For instance, for marketing data, you might prioritize email accuracy, while for billing data, address accuracy is more important.
• Automated Adjustments: Implement tools that allow for automated adjustments to your selection criteria. This ensures that your rules stay relevant as your data and business needs evolve.
• Cross–Department Collaboration: Ensure that rules are developed in collaboration with different departments. This helps create a comprehensive approach that considers various data needs and perspectives.
• Continuous Improvement: Regularly review and refine your master record selection rules. Continuous improvement ensures that your deduplication process adapts to new challenges and maintains high data quality.

Final Thoughts

Cleaning up duplicate data in your CRM is like organizing your room. When everything is in its place, you can find what you need quickly and easily. The same goes for CRM data: with just one accurate version of each record, your business runs smoother, and everyone has the right information when they need it.

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