One of the most frequently used terms in the RevOps world is data enrichment. But what is data enrichment, and why is it so critical to a company's sales and marketing success? You already know that data is your company's most valuable asset. It's the source of answers every company needs about who its customers are and where the ideal customer might be. But data also has an ethereal quality—it's constantly shape-shifting, changing, moving, and growing. Leads come in from multiple sources; companies merge, contacts change jobs, email addresses, and phone numbers. In that continual ebb and flow, crucial bits of information inevitably get lost, duplicated, or corrupted. The process of keeping all that changing data correct and up to date—that's data enrichment.
Data enrichment vs. data cleansing: what's the difference?
These two terms often get used interchangeably, but they describe two distinct steps. Data cleansing fixes what's wrong with data you already have — removing duplicates, correcting formatting errors, and updating records that have gone stale. Data enrichment adds what's missing — filling in fields your team never captured in the first place, like job function, company revenue, or technographic data. In practice, cleansing and enrichment work together: you clean before you enrich, so your enrichment vendors are matching against accurate records. But they're not the same thing, and conflating them leads to gaps in your data strategy. If you want to go deeper on cleansing, Openprise's data cleansing and standardization page covers how that process works. The rest of this post focuses on enrichment.
Where do enriched records come from?
For a record to become a part of your database, someone, at some time, had to put it there. It might have come from a list your company purchased or someone showing interest on your website or at an event. If a person filled out a web form, the chances are good that the record won't contain all the information RevOps needs to understand that person's business needs. You might have a company name but not a job title. The record may show an email address but not a first or last name. And what if you have a name, job title, and company but a personal email?
Customer data enrichment helps to place the proper context around each record so that RevOps teams know what they're working with—and avoid spending time and money trying to reach the wrong people. Perhaps your company acquired a smaller firm years ago and merged the records. Or maybe the spreadsheet from one company event had different fields, in a different order, than another spreadsheet from another event. How can the database parse that, and how can RevOps properly market to those people?
In a competitive B2B space, the best chance for success lies with your data. So how do you ingest the types of data you have access to? And how do you leverage it? The simple truth is this: If you don't go the extra mile to go deeper with your data, you're at a competitive disadvantage.
The main types of data enrichment
Data enrichment isn't a single thing — it covers several distinct categories, each of which answers a different question about a record. Most B2B RevOps teams use a combination of the following:
- Firmographic enrichment adds company-level information: industry, employee headcount, annual revenue, company type, and headquarters location. This is the foundation of ICP scoring and account-based segmentation. Without it, you can't reliably tell whether a lead belongs to a company you should be selling to.
- Technographic enrichment tells you what technology a company uses — their CRM, marketing automation platform, cloud infrastructure, and more. For technology vendors, this is often the most commercially valuable data type, since it reveals which competitors a prospect is using and whether their stack is compatible with your product.
- Contact and demographic enrichment fills in individual-level fields: job title, seniority level, job function, direct phone number, and LinkedIn profile. This is what makes personalization and lead routing work — you can't route a lead to the right rep or score it correctly if you don't know what role the person holds.
- Intent data enrichment layers in behavioral signals — which topics a prospect has been researching, which competitor sites they've visited, or which content categories they've been consuming. Intent data is a more advanced enrichment type, but it's increasingly important for identifying accounts that are actively in a buying cycle before they ever fill out a form.
- Geographic enrichment adds location specificity beyond what a company's headquarters address provides — regional office locations, territory assignments, or country-level data for global accounts. This matters most for teams with regional sales structures or complex territory models.
No single data vendor covers all of these categories equally well. That's the core reason why most mature RevOps teams end up working with multiple enrichment sources rather than a single provider.
Garbage in, garbage out: why data enrichment is so important
The standard old phrase "garbage in, garbage out" applies exceptionally well to data. If you don't have the correct data to begin with, there's no way you can get a good picture of who your potential customers or your TAB (total addressable base) could be. And that has enormous implications for the entire company. You need good data to be able to:
- Identify your ideal customers
- Do customer targeting or segmentation
- Understand which type of customers want to buy your product
- Spend appropriately for advertising, campaigns, and other outreach
- Retain sales and marketing team members
- Route leads to the correct salesperson in the right region
- Appropriately attribute leads and opportunities
- Price your products and services competitively
- Make your company attractive to investors
As you can see, everything stems from the quality and completeness of the data that you have as a company. Data quality affects everyone from entry-level SDRs to the C-suite and board level. As Openprise head of data enrichment Lem Lloyd pointed out, "if you don't know anything about your customers or your future customers, how do you create a product roadmap? How do you know what they want?"
And yet, B2B companies are, for the most part, still reluctant to spend appropriately for both the acquisition and management of data. It isn't unusual in the B2B world for an entire business record to contain only three to four field attributes. From the barest of information available, companies are making blind decisions — when better data enrichment could give them penetrating insight to help them anticipate and target the needs of lucrative accounts.
Why some companies hesitate to fully enrich data
It seems like a no-brainer: if companies are spending money to acquire leads and know the data they're getting might not be complete, why has there historically been little effort put into data enrichment?
Even companies that are willing to allocate budget to data enrichment may balk because of the time and complexity it takes. RevOps teams may not have the resources or existing knowledge to keep data updated, and because of this lack of confidence, they remain paralyzed to move ahead.
Some companies try to get as much information as possible at the lead form level, and still others may make a half-hearted attempt to enrich the data by drawing from one or two sources to fill in the blanks one time. But the truth is, you'll never find all the information you need from cursory, single-use enrichment. Why? Getting it right requires more.
- A lead might have come in from a different country or another segment
- The data might be of an undetermined age: the shelf life of data is notoriously short
- Better, more complete data enables you to derive intent data and read intent signals
Getting the complete picture from data enrichment requires access to multiple databases. Unless you have a service like Openprise multi-vendor enrichment, the amount of contracting and red tape involved with working with different data providers is costly, time-consuming, and more than a little daunting.
Finding hidden clues within the data
But customer data enrichment does much more than keep existing data fresh. As you add more information to both generic and specialty data, you can start to ferret additional material in other databases, making your data even more valuable.
Let's say there's a company you need to reach, but the contacts you have on file only have generic role-based email addresses, Lem explained. We can work with another data source to take what we already have and use automation to match it against additional records. And suddenly, we have direct contact information that matches the right people at that company. That's a game-changer for teams who've been looking for a way to get that information for a long time.
How often should companies enrich data?
Data enrichment is never a one-time job. You can't clean your house one time and call it clean forever, and the same goes for data. As we mentioned earlier, the continual movement of people and companies makes static content stale quickly—and that erodes the money you may have already spent for data. Enrichment is the best source of ongoing ROI from that data investment. Lem Lloyd tells Openprise customers that they should be enriching data every quarter, at the minimum. Ongoing data enrichment means that no one will have to wonder if the information they have is still valid, and no one should have to waste time calling on people who've moved on or on companies that don't fit the Ideal Customer Profile (ICP).
When data sparks no joy
We've compared the data cleansing and enrichment process to the Marie Kondo method of tidying before. Most people think of enrichment as only gaining data. Another benefit of data enrichment is the chance to get rid of data you no longer need. Lem cautioned that the idea of deleting data you may have paid for might be a hard sell. "Part of it is allowing you to discard things that you no longer need, that no longer sparks joy, right?" he said. "It lets you just focus on the good stuff," Lem said. "And when you focus on the good stuff, your revenue per rep will go up, and your pipeline will go up. You'll get more of the customers."
An insider's guide to multi-vendor data enrichment
Now that you understand what data enrichment is and why it matters, the natural next question is how to execute it well — especially once you realize one vendor isn't enough to cover your entire database.
Our insider's guide to multi-vendor data enrichment walks through 20 practical best practices for aligning your organization before you buy, evaluating and sourcing multiple vendors, and measuring ROI so you can negotiate contracts from a position of knowledge. It's written for the practitioner who's ready to move from understanding enrichment to building a real program around it.
Read: An insider's guide to multi-vendor data enrichment
Or if you'd like to see how Openprise handles enrichment across multiple vendors in a single platform, get a free data analysis with one of our data experts.
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