Data Enrichment vs. Data Cleansing (+ How to Do Both with Apollo)

If your contact list isn't reliable, is it actually useable?

If your database of phone numbers and email addresses actually extensive if your best ones are listed twice?

Chances are your organization and databases suffer from some level of bad data quality. And according to Gartner, poor data quality is costing organizations an average of $15 million dollars per year.

Gartner Lead Researcher, Mei Yang Selvage says that not only are organizations taking a financial hit from poor data quality, but it is also undermining digital initiatives, weakening competitive standing, and decreasing customer trust.

"On the other hand," says Selvage, "innovative organizations like Airbnb and Amazon are using good quality data to allow them to know who their customers are, where they are and what they like. Good quality data empowers business insights and starts new business models in every industry. It allows enterprises to generate revenue by trading data as a valuable asset."

Good quality data and a trusted data provider make all the difference. But how can you transform all of your faulty and outdated information into something useful and actionable?

The answer: through data cleansing and enrichment practices and tools!

Keep reading to learn everything you need to know about data cleansing, data enrichment, and how you can use these processes to revamp your customer databases.

What is data cleansing?

Data cleansing is the process of identifying and resolving corrupt, outdated, and/or irrelevant data. It boosts the overall reliability and value of your company data by finding and fixing mistakes in your database.

Some of the most common inaccuracies found in databases include:

• Missing values
• Misplaced entries
• Typographical errors
• Duplicate information
• Outdated contact data
• Poor data governance

Marketing and sales professionals say that over 30% of their records have outdated attributes, and 42% of these professionals say that this data inaccuracy is the biggest barrier to multichannel marketing.

Data cleansing is an essential process for preparing data for further use.

Whether it's for revenue generation or downstream analysis, data cleansing practices boost SDR confidence in your organization's database and enable them to execute data-driven selling.

What is data enrichment?

Once your data is clean, data enrichment comes in to make it more powerful. Data enrichment is the process of enhancing your existing records by adding new, relevant information from a third-party source, like Apollo's B2B database.

The goal isn't just to have more data, but to have a more complete picture of your prospects and customers. This added context helps you understand who they are, what they need, and how to best approach them.

Common types of enrichment include:

• Demographic data: Information about a person, such as their job title, seniority level, or skills.
• Geographic data: Location-based information like city, state, or country, which helps with territory planning and localized campaigns.
• Firmographic data: Information about a company, like its industry, size, revenue, or the technologies it uses.

The key is to enrich your data with attributes that align with your business goals, so every new piece of information helps you target, segment, and personalize more effectively.

Data cleansing vs. data enrichment: Key differences

Now that we understand data cleansing, it's important to understand how and when data enrichment comes into play.

After you finish cleaning up your data, you'll have fresh customer data. The raw data will be accurate, but it might not be too useful outside of very specific situations.

Data enrichment contextualizes your customer data points. It is the process of appending additional information from a third-party source to give you deeper insight into who your customers are, so you can personalize messaging and target your ideal prospects more effectively.

Benefits of data cleansing

A clean database does more than just look good—it drives real business results. By focusing on data cleansing, you'll see immediate improvements in several key areas.

Better decision-making

When your sales team trusts the data in front of them, they can make faster, more confident decisions. No more second-guessing if a phone number is correct or if a contact still works at the company.

Higher engagement rates

Clean data means your emails actually land in the right inbox. This reduces bounce rates, protects your sender reputation, and ensures your carefully crafted messages get seen by the right people.

Increased efficiency

SDRs waste countless hours chasing down bad leads or correcting faulty information. Data cleansing gives that time back, allowing them to focus on what they do best: selling.

Benefits of data enrichment

Personalization

In a world that is constantly demanding the attention of consumers, personalization is king.

Consumers now expect companies to know them and constantly anticipate their needs. It's reported that 74% of American customers feel frustrated when messaging isn’t targeted to them.

Data cleansing eliminates the chance of incorrectly targeting customers, and data enrichment enhances the customer experience by providing you with unique, relevant information on the people you are prospecting.

When these two practices work in tandem, your business can deliver effective and personalized marketing campaigns that result in paying customers.

Improved engagement

Internal Crime Report found that businesses lost a total of $675 million in 2017 from having their emails marked as spam.

When your data is messy and outdated, it affects more than your efficiency—it can also damage your brand. The last thing you need is your marketing emails going straight to the spam folder.

When your data is clean and enriched, your conversion rates improve and your outbound engagement becomes more valuable.

Smarter personalization

With enriched data, you can tailor your outreach based on a prospect's industry, job title, or even the tech they use. This level of personalization shows you've done your homework and makes your message stand out.

Improved lead scoring and routing

More data points allow you to build more accurate lead scoring models. You can automatically identify your most valuable prospects and route them to the right sales rep instantly.

More effective segmentation

Enrichment lets you slice your audience into highly specific segments. You can create targeted campaigns for VPs of Sales in the SaaS industry or for companies that just received a new round of funding, leading to much higher conversion rates.

When to prioritize data cleansing vs. data enrichment

So, which comes first? It's a classic chicken-or-egg question, but in the world of data, the answer is clear: cleanse first, then enrich.

Think of it like this: enriching a dirty database is like putting a new coat of paint on a crumbling wall. It might look better briefly, but you haven't fixed the underlying problem. Adding accurate, new information to an incorrect contact record is a waste of resources.

Here's a simple way to think about it:

• If your bounce rates are high and your team complains about bad phone numbers, prioritize data cleansing. Your foundation is shaky and needs to be fixed.
• If your outreach feels generic and you're struggling to personalize, prioritize data enrichment. Your foundation is solid, and you're ready to build on it.

Ultimately, data cleansing and enrichment are two sides of the same coin. A truly effective data strategy requires both working in tandem to keep your database accurate and powerful.

Step-by-step data cleansing and data enrichment with Apollo.io

If you follow the right processes, you can be confident in the integrity and quality of your B2B data. But, even the best data managers won't be able to fully execute these processes without a data tool to help.

And with millions of users and hundreds of millions of verified contacts, there's a reason why Apollo is the best data tool for the job…

According to the 1-10-100 data rule, it is 100x more expensive to fix the impact of bad data on your business than it is to clean and verify your data from the beginning.

This means that you need to invest in the proper tools and processes to clean up your existing data before something breaks.

With all your existing data in Apollo, it's time to correct those inaccuracies among existing customers. This one might take some time, but Apollo helps you streamline this process.

When your CRM is synced, Apollo identifies inaccuracies and refreshes your CRM in real-time. For example, Apollo automatically notifies you if there is a probable duplicate. You can then merge the duplicates into one contact to clean up your contact list in seconds.

Apollo also offers Job Change alerts, integrations with your Google Calendar, and other data housekeeping features—all to ensure that the data you are using in your current workflow is helping (not hindering) you.

Collect data

Now that your data is squeaky clean, it's time to enrich it.

A well-functioning data enrichment process is essential for brands looking to keep up in an information-centric world.

Among all of its other functions, Apollo can serve as your data enrichment services provider, helping you source quality data from external sources and seamlessly add it to your database.

First, you'll want to download the Apollo Chrome Extension for easy data collection from LinkedIn and beyond!

The Apollo Chrome Extension allows you to prospect and collect accurate contact information during lead generation without ever leaving your LinkedIn screen. You can look at current activities in any account, the current data on a particular sales sequence, whether or not a contact is in your CRM, and even what other contacts within a single account are in your CRM.

Most importantly, saving prospects' information in your CRM and Apollo account only takes a click of a button.

You can also use the Chrome Extension beyond LinkedIn! Enable Apollo Everywhere to access Apollo insights across the web.

To use this feature, all you have to do is install the Apollo Chrome Extension, launch the Apollo Chrome Extension and toggle 'on' Apollo Everywhere.

Standardize the cleansing process

As we've learned, data cleansing isn't a one-and-done deal.

To have a consistently clean database, you need an ongoing and standardized data process that is transparent and accessible.

Keeping your team in the loop and giving them the tools they need to upkeep customer data will help your business develop and strengthen customer segmentation and send more targeted and personalized information to customers and prospects.

One way Apollo can help with this is Job Change Alerts.

When Apollo detects a prospect's job change, their new title and company will appear beneath their contact in your Apollo account. Now, you never have to worry about having the wrong data for a contact's employment status, and you can capitalize on the opportunity to sell to a fresh employee who is looking for new tools for the job.

A data manager can also utilize Apollo's Rules Engine. Rules Engine is a hub for automation and it can easily be used to keep your database clean and enriched.

Set up a series of "triggers" and actions for Apollo to automatically carry out. You can tell Apollo to remove a contact from a list if an email bounced, or assign Apollo to set a contact field after a contact is updated.

Now, that's working smarter, not harder!

Learn more about using Rules Engine to start standardizing your data processes with Apollo.

Review and optimize

Last but certainly not least, your data quality needs to be consistently revisited and optimized.

Gaining visibility into your data health can improve your data cleansing processes and give you the valuable insight you need to make data-based decisions.

Run data health checks with Apollo Analytics and Reports.

Analytics opens up a whole new world of actionable reporting. With customizable reports and dashboards, you can view an ever-growing list of data analytics. From bounced phone calls and emails, to open rates, reply rates, and sales success rates, you can answer every question you can imagine about your data performance.

Over 60% of organizations don't measure the cost of poor data quality. Failing to measure this impact results in reactive responses to data quality issues, missed business growth opportunities, increased risks, and lower ROI.

By implementing the proper data and enrichment tools, you'll never miss a business opportunity due to poor data hygiene.

So, what are you waiting for?! Try Apollo for free today and scrub your B2B data clean.

Transform your data quality with the right approach

Data cleansing and enrichment aren't just buzzwords; they're fundamental practices for any modern sales organization. Cleansing fixes the data you have, while enrichment adds the data you're missing. Together, they create a reliable, high-performance database that fuels predictable growth.

But you don't have to tackle it alone. With the right platform, you can automate both processes and turn your data into your biggest competitive advantage. Ready to build a database you can trust? Get started with Apollo for free and see how easy it is to clean and enrich your data in one place.

Frequently asked questions about data cleansing and enrichment

What's the difference between data cleaning and data cleansing?

There's no real difference. The terms 'data cleaning,' 'data cleansing,' and 'data scrubbing' are often used interchangeably to describe the same process: identifying and correcting errors in a dataset.

What exactly is enrichment data?

Enrichment data is any third-party information you append to your existing contact records. This could be firmographic data (like company size or revenue), demographic data (like a contact's job title), or even buying signals (like recent job changes).

What's the difference between data cleansing and data purging?

Data cleansing focuses on maximizing the accuracy of your data, which might involve correcting, updating, or deleting individual records. Data purging is typically a broader action focused on removing large volumes of old or irrelevant data to free up storage space, often without the same focus on accuracy.

Should I do data cleansing or enrichment first?

Always cleanse first. You need a solid foundation of accurate data before you start adding new information to it. Enriching an inaccurate database just leads to more complex data problems.

Can I do data cleansing and enrichment at the same time?

Yes, with the right platform. A tool like Apollo automates much of the process. For example, it can continuously cleanse your data by flagging job changes or verifying emails, while you simultaneously use it to enrich your records with over 65 data points for better targeting.