Imagine one of your sales reps just found the perfect lead. Excited, they reach out, only to discover the contact information is outdated.
It’s not only disappointing; it's a missed opportunity that directly impacts your bottom line. Research from Gartner found that bad data costs businesses $15 million every year.
However, there’s a solution that can keep poor Salesforce data away from your revenue predictions. In this article, we'll help you turn the seemingly insurmountable challenge of Salesforce data cleansing into a manageable system.
What Is Salesforce Data Cleansing?
Salesforce data cleansing cleans up the information in your Salesforce database to make sure it’s accurate and useful. Typically, it eliminates duplicates, corrects errors and standardizes formats.
For example, suppose you have numerous leads in your Salesforce system, but some of them have incomplete or incorrect contact details. Data cleansing would involve going through those leads, updating or filling in the missing info and getting rid of any duplicates you find.
The long-term goal of Salesforce data cleansing is to make sure you're making the best decisions possible. If your data is messy, your team might waste time or miss out on qualified prospects. But if your data is clean and tidy, you can trust it to guide your sales strategy and focus on the highest-impact areas.
Why Salesforce Data Cleansing Matters
According to the research by Dun & Bradstreet, 91% of data in CRM systems becomes incomplete, stale or duplicated each year. If that’s not reason enough to invest in Salesforce data cleansing, then let’s consider the advantages you will feel on your revenue:
- Improved Data Accuracy: Cleansing processes eliminate errors so that you can make decisions based on the latest information. From sales forecasting to customer relationships, good data makes everything easier.
- Increased Efficiency: You no longer have to spend time (and resources) on rectifying data-related issues. Sales and marketing teams, for instance, can focus on talking to high-quality leads instead of hoping their emails don’t bounce.
- Stronger Customer Relationships: When your Salesforce data is clean, it’s much easier to understand how your customers behave and what you can do to intercept them at crucial stages like activation, engagement and lifetime growth.
- Lower Costs: If you don’t need to allocate resources to correcting data errors or avoiding the consequences of acting on incorrect data, there will be more room in your budget for the initiatives that proactively grow your revenue.
- Improved Compliance: In an era of stringent data protection regulations, Salesforce data cleansing keeps you compliant. Similarly, when you regularly cleanse your Salesforce data, it’ll be easier to spot and mitigate potential security breach points.
- Competitive Advantage: Finally, clean data gives you a competitive edge over the competitors who are still struggling with “dirty” data. You’ll have an easier time seeing what your customers need you to do next and where their businesses are going, so yours can adapt.
Common Issues: Why Isn’t Every Company Cleansing Salesforce Data?
With the benefits so immediately clear, it’s easy to wonder why companies aren’t already cleansing Salesforce data regularly. But speak to any of your peers and you’ll hear something similar to:
“It’s such a mess. We’ve integrated so many tools that, at this point, it’d be easier to deconstruct the whole architecture than try to clean it up. And besides, we need the budget for the pipeline.”
No, Salesforce data cleansing – when you’re straining under the weight of trillions of entries – is not easy. But the sooner you rip off the band-aid, the easier it will be to make the right calls.
How to Deal with Poor Data Quality During Salesforce Cleansing
Sometimes, the data in Salesforce is “dirty” on multiple fronts, making the cleanup efforts feel like untangling a giant knot. You've got duplicates, missing fields and outdated information, all leading to unreliable reporting, missed opportunities and unnecessary resource expenditure.
Solve poor data quality by using tools that automatically spot and fix duplicates or missing info in Salesforce.
For example, Findymail integrates with Salesforce to verify the accuracy of your B2B email address data.
Missing email addresses? Not a problem, either. Findymail finds more accurate and verified email addresses than any other B2B tool.
Instantly.ai founder, Nils Schneider, performed a test comparing Findymail with a different popular B2B contact info tool.
He inserted 517 agency domains into both tools. The other tool found 76 emails.
Findymail, in comparison, found 139 emails. Then, it performed the verification process to give Nils 106 emails he could reliably add to his database.
“Findymail is the most versatile email finder. I love how easy the API is to integrate into workflows and tools we already use. The data quality is unmatched!”
Data Integration Challenges
Getting all your different data management systems to work in sync with Salesforce can be a challenge. Unfortunately, if your data isn't flowing smoothly, it's hard to keep everything consistent.
Look for tools that simplify data syncs between Salesforce and other tools. For example, Zapier automates data transfers between Salesforce and tools that don’t have native integrations.
Does Your Team Know Their Actions Affect Salesforce Data?
Let’s go back to the salesperson’s daily struggle: the pressure to reach out to as many people as possible.
In order to meet the quotas, the sales professionals front-load Salesforce full of data from different tools (e.g., Sales Navigator, Apollo, etc.).
Over time, people change jobs, their details change and the companies no longer have (or they develop) a need for your offer. The data does not only pile up – it starts to rot.
As the team expands, it gets even worse – now, you have even more people uploading data into the CRM without checking for accuracy.
Fortunately, you can solve a lot with training and tools. Help your people understand how clean data aids everyone. Offer hands-on workshops or create videos that walk them through best practices for data entry and management.
Similarly, examine and document how data enters Salesforce (e.g., manual input, web forms or third-party integrations). Then, simplify your data entry process by customizing Salesforce fields to only include the essential information or consolidate your data enrichment stack.
Cleanup Complexities
Finally, data cleanup is not always a straightforward process. You have to understand which types of records need fixing, how to fix them without causing more problems and how to prevent the same issue from happening again in the future.
Break down the cleanup process into smaller, manageable tasks. Handle the most critical issues first, like removing duplicates or updating outdated records.
Then, schedule regular cleanup sessions and monitor progress.
Types of Bad Data in Salesforce
Typically, bad Salesforce data will fall into one of these categories:
- Duplicate Data: Multiple records of the same contact, account or lead that clutter the database and confuse users.
- Unstandardized Data: Data that lacks consistent formatting, leading to inaccuracies in reporting and sales analysis. This can include variations in naming conventions, addresses or any other fields that should be uniform across the database.
- Missing Data: Essential information that is not recorded in the database, leading to incomplete records.
- Incorrect Data: Errors in the data, such as wrong contact details, that result in email bounces and missed opportunities.
- Outdated Data: Information that is no longer accurate, such as old addresses or job titles, which can point your campaigns in the wrong direction.
How to Start the Salesforce Data Cleansing Process
Data cleansing isn’t a one-and-done process. It’s an ongoing system that needs to evolve alongside your business.
While the specifics will vary from company to company, these are the steps our team at Findymail always takes to begin effective Salesforce data cleansing:
Step 1. Data Auditing
Begin by thoroughly reviewing your Salesforce environment to understand the current state of your data and pinpoint the root causes of data decay:
- What are the most common sources of bad data?
- What types of bad data are you dealing with? (See section above)
- How widespread are the issues?
This will help you set a baseline for the cleansing process.
Step 2. Establish Goals for Salesforce Data Cleansing
Next, define clear targets. Even if you’re struggling with multiple issues, focus on the most pressing ones.
For example, suppose your current biggest problem is duplicate records. Whenever your team tries to find a customer's contact info in Salesforce, they end up with three different records, each with slightly different details. This issue will create a mess in the pipeline, forecasts and inboxes, so it takes priority.
Similarly, identify your mission-critical data types.
In addition to the essential contact information, are technographics crucial to your outreach? Is it intent data for account-based marketing?
Go in with a plan, so you can tailor your approach and see the Salesforce data cleansing ROI faster.
Step 3. Data Deduplication
Ensure each Salesforce contact is represented only once in the database, so you have a single source of truth.
You can use Salesforce’s built-in duplicate management tools to identify and merge duplicates. Additionally, you could also set up custom matching and duplicate rules.
Step 4. Data Validation and Verification
The real issue with Salesforce data hygiene isn’t what you can see, but what’s hidden under the surface.
It’s extremely hard to predict inaccurate data – you only really know it’s inaccurate when your team sends an email and they get a bounce-back.
The problem is that this can happen hundreds of times every day.
Your salespeople won’t be reaching the right decision-makers, decreasing their chances of building a robust pipeline and starting the right conversations.
Verify the accuracy of your data and create automated workflows. For example, verify email addresses with Findymail’s actionable B2B contact information tool.
Step 5. Standardize Your Salesforce Data
Finally, implement data entry and formatting standards, such as creating naming conventions, phone and address formats and other field-specific rules.
Step 6. Enrich Your Data the Right Way
The quality of your Salesforce data heavily depends on the reliability of your data sources. When you choose data enrichment partners, choose tools that re-verify information and replace the outdated with fresh data.
For example, Findymail works in your Salesforce setup to verify email addresses before your team sends their outreach. If the information is incorrect, it will be replaced with newer data.
If your data comes from multiple sources, establish a process that cleans and reconciles data discrepancies.
Step 7. Implement Salesforce Data Hygiene Practices
As mentioned, data hygiene isn’t a one-time task but an ongoing process. Establish regular data maintenance routines, including periodic audits, updates and deduplication efforts.
For significant improvement over time, train your team on the importance of data quality.
Discuss procedures for standard conundrums such as managing incorrect records. For example, should the team member flag it as incorrect, delete it or leave it as it is, potentially risking someone else utilizing the incorrect data?
Create guidelines for data entry and set standards for all your data partners.
What Are the Best Tools for Salesforce Data Cleansing?
Of course, you’re not in this alone. There are plenty of tools you can use to make Salesforce data hygiene less of a headache. However, not all tools are built equally and some can even exacerbate bad data in your CRM.
When choosing a tool, consider the following criteria:
- Integration Capabilities: Opt for tools that seamlessly integrate with Salesforce, ensuring a smooth data flow and minimizing the risk of data corruption.
- Real-Time Validation: Tools that offer real-time data validation prevent bad data at the entry point, so the incorrect information doesn’t reach your database.
- Customization and Flexibility: Every organization has unique data standards and requirements. The right tool should offer customization options that allow you to define what constitutes high-quality data in your book.
- User-Friendliness: Finally, the tool should be easy to use for users with different levels of technical expertise. Look for an intuitive interface and clear documentation.
With this in mind, these are our five favorite tools for pulling clean data into Salesforce:
- Findymail: Great for enriching Salesforce with accurate and actionable email data. It makes sure email addresses are verified, so your campaigns are more impactful.
- Gridbuddy: Great for data completeness and timeliness within Salesforce, Gridbuddy aggregates data from multiple sources into user-friendly, editable grids.
- DemandTools: This powerful suite is designed to ensure data uniqueness by deduplicating Salesforce records. It's an invaluable tool for data quality management and maintaining a clean and reliable database.
- PipeLaunch: This tool pulls data from over 20 different sources, including LinkedIn, for the most accurate and up-to-date info.
- ZoomInfo: Offers comprehensive business profiles that enrich Salesforce data, helping in your lead generation efforts.
However, keep in mind that tools that focus on multiple data types at the same time often lack specialist accuracy. For example, ZoomInfo is great for enrichment at large, but it may come with lower accuracy for specific data like email addresses.
Best Practices for Managing Your Salesforce Data
1. Create Validation and Formatting Rules
Create validation and formatting rules to make sure that records have the expected level of field data before they can be saved.
For example, let’s imagine you often see inconsistencies in phone numbers. A valid phone number should have 10 digits and start with the country code. But sometimes, your team members forget to include the country code or accidentally add extra characters.
The validation rules could automatically check if the number has 10 digits before the information is saved.
2. Create Dedicated Page Layouts
If all your teams have access to the same page layouts, things will get confusing. Your sales teams need one type of data, your marketers another, while your finance team needs a unique setup.
For the Sales team, you want to focus on essential fields related to leads, opportunities and customer interactions. So, you create a customized page layout that prominently displays fields like lead source, opportunity stage and contact information. You might also include related lists for activities or recent deals.
Marketing folks are more interested in campaign data, lead nurturing and engagement metrics. So, you design a page layout tailored to their needs, with fields for campaign status, lead scoring and campaign member details.
Over in Finance, they're all about the numbers—invoices, payments and financial data. Your page layout for Finance would include fields for invoice status, payment terms and billing information.
At the end of the day, you declutter the interface and present users with only the information they need to do their jobs effectively.
3. Data Management & Governance in Salesforce
With the volume of data increasing rapidly, you need a solid data management strategy.
Start by dividing your data into logical segments based on factors like customer type, purchase history or geographic location. For example, you might have segments for loyal customers, first-time buyers or customers from different regions.
Then, establish clear policies for data governance (data usage, access and security). Define who has access to what data, how data should be stored and protected and what procedures you will follow in case of data breaches.
Implement processes and tools to maintain data accuracy, completeness and consistency. For example, you can use automated tools to flag duplicate records, validate email addresses and standardize data formats.
Similarly, set up regular backups of your Salesforce data to prevent data loss in case it accidentally gets deleted, the system fails or a cyberattack takes place.
Clean Your Data, Sharpen Your Vision
Data cleansing might seem overwhelming, but it's an integral part of staying data-driven as you grow. If you follow this guide, you’ll quickly transform this daunting task into a manageable process.
Remember, the journey to maintain a clean database is continuous but vital. Don’t be like so many of your competitors, drowning in the sea of rotting data.
Instead, face these challenges head-on and think of them as opportunities to make your data work harder, so you can work smarter.
