Data Enrichment: Boost Your B2B Sales With Our Tips and Tools

When it comes to making the most of the digital information at your fingertips, quality trumps quantity. That’s where B2B data enrichment comes in.

But we’re not here to throw buzzwords at you. We’re here to help you make the most out of your data so you can gain better insights into your customers and get a competitive leg-up.

In this article, we’ll give you a data enrichment definition to sink your teeth into, before diving into the concept in more detail. 

We’ll explore the benefits for your sales teams, share data enrichment methods you can implement, and look into some of the best data enrichment solutions on the market.  

Note: Want more data about your leads? Leadfeeder identifies companies that visit your website and provides data like the best contact, email address, company stats, and more. Sign up for a free 14-day trial.

What is data enrichment?

B2B data enrichment is the process of turning raw data into accurate, reliable data by adding new data points and verifying accuracy with third-party data sources.

Here's a visual of how data enrichment works:

You start off with your raw data. There's a ton of it, and it isn't really that valuable.

Using third-party databases and tools, you verify the accuracy, clean up repetitive data, and add new insights.

Voila—powerful data you can use to segment audiences, build account-based marketing campaigns, and more.

Data enrichment vs data cleansing

We’ve already looked briefly at the data enrichment meaning—it’s about enhancing the value of existing datasets by adding supplemental data from internal or external sources. Data cleansing is an important step in the data enrichment process, but it’s not the same thing.

Data cleansing is the process of cleaning up your existing datasets by removing anything that’s irrelevant, inaccurate, or out of date. It involves finding and correcting errors such as misspelled names, clearing up inconsistencies, and deleting duplicates.

Data cleansing happens before you integrate new information through data enrichment, but you also need to cleanse all your data on an ongoing basis.

Top types of data enrichment

Data enrichment can encompass various types of information, depending on your reasons for using it:

• Demographic: Socio-economic information is used for customer data enrichment, such as age, gender, income, cultural background, and education. It can also include contact details for potential clients.

• Geographic: This type of data enrichment pulls in location-based information, such as street address, city, state, country, or region.

• Behavioral: Behavioral data relates to customer interactions, including their engagement level, purchase history, and online activity.

• Firmographic: Often used in B2B, this adds organizational attributes like industry type, company size, revenue, and business performance.

• Technographic: These insights relate to how customers use technology—for instance, their device type, operating system, and app usage. You can also use this for product data enrichment.

• Psychographic: Lifestyle characteristics such as personality, interests, values, and opinions are useful for market research.

What are the benefits of data enrichment for B2B businesses?

Okay, so the benefits of updating contact information may seem pretty obvious.

But beyond the glaring benefit of having updated email addresses to send cold emails to, there may be some advantages you haven’t considered. 

And if you have any worries about the time it might take to enrich all of your data or invest in the tools to help you do so, let us quell your concerns.

Improves decision-making

Data enrichment helps organizations (and people in those organizations) make better decisions by providing access to more accurate data.

Think about your sales team—if they go into a sales call with inaccurate data, that sales call isn't going to go so well, is it? With enriched data, sales and marketing teams can easily access the data they need at the very moment they need it, allowing them to make the right decisions quickly, react to changing circumstances, and capitalize on new opportunities.

Enriched data can also be fed into analytical models. With the support of AI modelling and machine learning, companies can leverage more accurately predicted business trends, patterns, and insights.

Ensures data quality

Data enrichment doesn't just expand your data; it improves the quality of your data. That is because you don't just add to the data, you also verify its accuracy.

Verifying and improving data can highlight new opportunities you might have missed. For example, you might find one of the companies you were planning to target separated from its parent company—now you have two clients to target.

 Alternatively, you learned that a prospect was acquired by a current client, saving time you might have spent nurturing them.

Saves time and resources

Old, incomplete, or inaccurate data is pretty much useless. Your teams will waste time reaching out to companies that no longer exist, leads who have moved to different roles, or prospects who no longer have a need for your product.

And wasted time is wasted money.

Enriching data plugs the gaps so sales teams can prospect, pitch to, and convert leads more efficiently.

Increases engagement and conversion rates

Enriched data gives you more in-depth information about leads–information that’s high-quality and relevant.

That type of data is useful for everyone from sales to marketing to customer relationship managers.

Using this data, sales and marketing teams can create more personalized content that’s more likely to grab their attention. It also means communications will be more timely and relevant to a company’s relevant situation and needs. 

For example, if a start-up has entered its growth stage or had an injection of funds, you can strike while the iron’s hot.

Data enrichment examples: Putting it into practice

The term ‘data enrichment’ may sound complex in theory, but it’s actually quite simple in practice. Here are a few examples of ways you might enrich data in your company:

• Updating existing contacts: Let’s say you have a decent list of leads but each contact only contains a name and email address. That’s not much to go off if you want to conduct effective outreach. Data enrichment would see you enhance this with details about each contact, for example, their company name and industry, their role at the company, and perhaps their social media profiles. 

• Finding new leads: Data enrichment software automatically scouts out contact information for your target market, adding accurate, up-to-date information to your CRM for real-time visibility.

• Segmenting customers: Enriched data means better data. Using third-party data from enrichment software allows you to better categorize customers based on different data such as behavioral or intent data. This helps sales and marketing teams find the best prospects to approach and allows for more targeted messaging.

Understanding the data enrichment process

Here’s a guide to how data enrichment works—you’ll need to work through these steps no matter what industry you’re in or which data enrichment platform you use.

1) Data assessment

First, evaluate the current state of the data your company holds. Make a list of the data types and their sources, and look for any gaps that you could fill with additional information. This will help you to understand what kind of data you need to introduce.

2) Data source identification

Now that you know the type of extra data you need, you can identify suitable sources. These may include internal sources like your own databases or CRM or third-party data sources such as web scraping.

3) Data cleansing

It’s hugely important to check your data’s quality before you integrate new information. As we mentioned earlier, this includes correcting errors and duplications and standardizing formats within your dataset. This will make it easier to integrate the new data.

4) Data integration and validation

Now you can go ahead and merge the new data with your existing datasets. You’ll need to validate the enriched data to make sure it’s still accurate and implement quality assurance (QA) protocols to check its quality and usefulness.

5) Ongoing review

After the initial integration, it’s vital to continue monitoring the data over time and adjusting it when necessary. Data can quickly become obsolete or irrelevant as your business, customers, and market conditions evolve. 

Challenges of data enrichment

Like most processes, business data enrichment comes with a few challenges:

• Data quality: If your data is inaccurate to begin with, your enrichment process isn’t going to go smoothly. This can happen if you don’t cleanse your own data and if you fail to check and validate data from external sources. Poor data leads to poor decisions and wasted efforts.

• Data relevance: You have access to a ton of data, but not all of it is pertinent to your goals or business processes. If you try to use everything, it will detract from your objectives.

• Integration: When you’re handling data in different formats and systems, the enrichment process becomes more complex. It’s challenging to integrate the two sets of data without hampering quality.

• Scalability: As the volume of data keeps on growing, you’ll soon be overwhelmed unless your enrichment processes can evolve to match it. 

• Compliance: You want to make the most of your data, but you have to stay on the right side of the law. It can be tricky to keep up to date with the latest regulations around data privacy and security—and if you don’t, you could face fines or even legal action.

Get it right with data enrichment best practices

Having explored a few of the main challenges of data enrichment, here’s how to avoid them:

Set clear goals

Think carefully about the objectives of your data enrichment strategy, as this will guide you through the process and help you select suitable sources of new data. Make sure you set measurable goals and define the criteria by which you’ll track progress.

Ensure data quality

Make sure your baseline data is accurate, up to date, and in a standard format before you get started so that the supplementary information can integrate seamlessly. Conduct regular audits of all your data, and verify it against authoritative sources.

Choose relevant data sources

As we mentioned, not every piece of data is valuable—at least not to you. Pick your new data sources based on relevance as well as quality, and disregard anything that doesn’t fit in with your specific goals.

Integrate gradually

It’s best to introduce the new data in stages to minimize the risk of problems with the integration. Data governance policies and standards will help to avoid errors and duplications, but you should still check how enrichment is affecting your datasets at each stage before you add more information.

Always validate the data

Once the enrichment process is complete, make sure you validate the results to make sure everything is as it should be. Have any inconsistencies crept in? Remember that your data environment is always changing, so monitor and update your datasets regularly.

Use technology

Automated data enrichment will streamline the process for maximum efficiency, reducing the risk of human error. It will also enable you to perform the process at scale as you collect more data. Consider using machine learning models to predict the outcome.

Keep your data safe

As well as maintaining compliance with privacy regulations—which includes obtaining the necessary permissions for using data—you should implement robust security practices to avoid data breaches. Include risk management and crisis response in your enrichment strategy.

Data enrichment techniques to supercharge your sales and marketing

Now that you know what data enrichment is, let's talk about the how.

Here are six strategies you can use to enrich your lead data. Don't feel like you have to use them all!

Try one or two and see how it impacts metrics like conversion and response rates. As you get more comfortable with the process, add strategies that make sense for your organization.

Don’t look at your data sources in silo

B2B data can come from nearly anywhere. And while first-party data is great (more on this below), you should consider other sources, too, including third-party data providers. 

After all, the idea of data enrichment is to get your hands on data you need but don’t have.

Combining data from external sources with existing data in your CRM or other contact database will help fill in any gaps. 

These third-party tools can also give you additional insights into customer characteristics, behavior, and buyer intent.

Use longer forms to gather more information about leads

This might seem counterintuitive. There is definitely an opportunity cost to longer lead forms — asking for more info does result in fewer leads filling out your forms.

However.

It can also provide more information and result in higher-quality leads, which means sales spends less time on low-quality leads.

While this isn't as high-tech as other data enrichment strategies on this list, it is one of the simplest approaches to contact data enrichment.

For example, rather than just asking for an email address and first name, you can ask leads for information such as:

• Job title

• Company size (based on number of employees)

• Company revenue

• Location

• Type of clients they serve

• Whether they are looking for the solution you offer

If creating a 15-question lead gen form seems overkill, consider using a chatbot that asks these same questions. The format is less intrusive, but you're able to gather the same information.

Then compare the data you gather to data in your CRM or email marketing tool to ensure accuracy.

Send out customer/prospect surveys to better understand and segment them

There are a ton of data enrichment companies on the market (we've even shared a few of our favs below)

However, that data is accessible to everyone — which means your competition has access to the same data.

Gathering first-party data about your audience is a powerful way to ensure your data is accurate and actually useful for your organization.

Sending out customer surveys can provide crucial information you need to segment your audience, target them with upsells and provide better customer service.

This can also help with data enrichment — for example, you can verify the best point of contact, ask about their overall goals, and so forth.

It's more time-consuming but provides data you won't find anywhere else.

Automate the enrichment process to save valuable time

You don’t need us to tell you that automation saves time. Chances are you’re automating numerous other processes.

But, data enrichment is a particularly tedious, time-consuming process. Maybe you’ve even been putting it off because of the sheer size of your contact list.

Automating the process of cleansing, enriching and segmenting your data will go a long way in guaranteeing your team is contacting high-quality leads that won’t hang up on them.

You’ll have up-to-date details so outreach doesn’t fall at the first hurdle. You’ll have all relevant company information for targeting prospects with personalized messaging. And you’ll have clear customer segments for approaching the right companies at the right time.

The result? 

Conversion after conversion after conversion.

Maintain enriched data in the long-term

The nature of data is that it’s ever-evolving. Contacts are likely to switch job roles or companies. Target businesses will grow, which means bigger teams and bigger budgets. And new companies will come into the market.

If you don’t keep all of your data up-to-date to reflect these changes, you’ll be missing out on numerous opportunities.

So don’t think of data enrichment as a one-time process. You’ll need to regularly monitor your data and keep it maintained so that it stays accurate. 

This is a key step in data integrity and crucial for your teams to make the right decisions at the right time.

Six data enrichment tools to enhance your database 

This might all feel overwhelming — especially if you have a large database or get hundreds of leads every month.

The good news is, it doesn’t have to be complicated. And there are some really robust lead enrichment tools out there that will make it that much easier.

No one has time to manually sift through databases or search for contact information online. These tools automate the process of contact enrichment by bringing together everything, from email addresses to user intent.

Also known as sales intelligence, lead generation, or sales prospecting tools, these platforms will become a lifeline for sales teams.

Before you select one, make sure you understand what you need out of it — key features, data points, and so on — as well as your budget.

Let’s see what some of the top tools offer.

1) Leadfeeder

Leadfeeder is a lead generation and data science tool that identifies site visitors based on their IP address and domain (you can read more about how it works here), and then pairs that info with our contact database.

This lets you see not just the company, but also location, company size, and the best point of contact.

In addition to the company contact info, you get access to behavioral data about each lead. 

For example, you can see: 

• What pages they viewed

• How long they stayed on each page

• What page they exited on

• Acquisition source

• How many people from the same company visited your site

This data can help verify other database information, add new information to your current database — and even be imported into your CRM so you can see it all in one place. 

Pricing: Get started for free or gain access to unlimited data for €99 per month paid annually.

2. Crunchbase

You may already be familiar with Crunchbase, but did you know they offer a database enrichment tool as well?

This data can help you enrich current lead data, build reports, better understand your marketing effectiveness, and even research investment opportunities. It is a paid tool, but it's also pretty powerful.

For example, the searchable database means you can filter down to find your target company or key decision-maker at that company. Other useful features include automated lead recommendations based on your ideal customer profile (ICP) and flexible APIs for scalable insights and predictions.

For B2B companies, in particular, it's worth consideration.

Pricing: From $99 per user/per month; custom packages available.

3) Cognism

Cognism is arguably one of the best known sales intelligence platforms on the market, so it’s not surprising that its complementary Cognism Enrich feature is equally beneficial.

The tool’s primary goal is to help you enrich historical data and enter new, accurate data with access to GDPR and CCPA-compliant information.

You can do this by selecting the right enrichment layer for you – Instant, Scheduled, or CSV Upload.  Each layer will streamline the enrichment processes for you, helping to automatically cleanse data, ensure information is accurate, and update your CRM in real time.

It also integrates with various tools that are probably already in your tech stack, including SalesLoft, Salesforce, and HubSpot.

Pricing: Contact for custom packages

4) LinkedIn Sales Navigator

LinkedIn Sales Navigator is a B2B sales rep's best friend. It provides deep insights into people and companies.

For starters, sales teams can find target accounts by searching for companies by industry, location, and more.

But, it also connects with several different CRMs so you can verify data you already have about prospective leads.

By matching up data you have with LinkedIn, you can ensure you have the right contact information, job listing, etc.

As a result, your sales team can go into cold calls with more (and better) information about leads.

Even the basic plan provides real-time alerts on decision-makers, such as job changes, as well as account recommendations and a new Relationship Map feature that gives you visibility into key leads with up-to-date organizational maps.

Pricing: Sales Navigator Core plan starts at $79.99 per month paid annually, with a one-month free trial.

5) Clearbit

If your target market is early- or growth-stage start-ups, Clearbit is a great option.

The platform, which has joined forces with HubSpot, is powered by machine learning, which trawls countless data sources and converts unstructured data into precise data sets you can act on. 

With access to a wealth of B2B contacts from around the world, it’s best for data coverage, understanding corporate hierarchies, and comparing contacts against your ICP.

Pricing: Free account offers limited contact look-ups or upgrade to Business plan for custom volumes.

6) Dealfront Connect

Dealfront Connect enables you to shorten your prospecting time by using the built-in Chrome browser extension while browsing company data online.

What you can do with Dealfront Connect:

• Access deep company data and insights

• Discover up- and cross-selling opportunities

• Get alerts like company expansions

Features like trigger events, including financial statements and webpage changes, and seamless CRM integration, make contact enrichment easy and effortless. 

Pricing: Connect Browser Extension for free. Connect is part of Dealfront’s all-in-one sales intelligence solution, with flexible packages created on a business-by-business basis.

B2B data enrichment solutions for better insights

Data enrichment is all about improving the quality of your data so your organization can make better decisions.

When sales, marketing, and your business leaders have better data, they're able to target leads more accurately, build better campaigns, and make strategic decisions that help your business grow.

Note: Leadfeeder is a lead generation and data enrichment tool that helps B2B companies understand their leads better. Sign up for a free 14-day trial and see how we can help your business grow.

FAQs

What are the main types of B2B data?

The most significant types of business-to-business data include contact data (also known as people data), firmographic data, technographic data and intent data. 

What’s the difference between data enrichment and data cleansing?

Data enrichment equals adding. It’s the process of verifying and enhancing data with third-party databases. Data cleansing equal removing. It’s the process of ‘cleaning’ data by eliminating corrupt, inaccurate, or repetitive information.

How do you enrich lead data?

Third-party tools like Leadfeeder automate the process of B2B lead enrichment. Collecting real-time, accurate information about your site visitors, they give you access to behavioral data like online activity as well as demographics to help you more effectively target those leads.