Waterfall enrichment fills data gaps quickly, while researched data focuses on accuracy and ICP fit. Explore how combining both approaches can build more reliable B2B target account lists.
Your enrichment workflow has just filled almost every empty field on your target account list.
Emails. Job titles. Employee counts. Technology stack. The spreadsheet finally looks finished.
But a filled field is not the same as a true field.
That gap sits at the heart of a choice many B2B marketing teams are now making. Waterfall enrichment promises coverage by running each record through a chain of data providers until one of them returns an answer. Researched data takes a different route. It checks the details that decide account fit against current sources before a record is accepted.
Both approaches have a place in a modern data stack. But if your goal is an accurate Ideal Customer Profile (ICP), they do not produce the same result.
This blog explains how each approach works, where each one falls short and how to decide which should shape the accounts you target.
Waterfall enrichment is a B2B data enrichment method that sends a record through several data providers in a set order.
If the first provider cannot find the missing field, the record moves to the second. If the second has nothing, it moves to the third. The process continues until a value is returned or every provider has been tried.
Picture a list of 10,000 target contacts with no email addresses. Provider A finds some of them. The records Provider A misses pass to Provider B. Whatever Provider B misses passes to Provider C. At the end, you have one enriched file assembled from whichever source answered first for each record.
The logic is simple. No single B2B database covers every company or every contact, so combining several increases the number of fields you can fill.
For tasks like filling in missing company domains, sizing a total addressable market or topping up contact fields at volume, those are real advantages.
Researched data is B2B company and contact data that has been built or validated against a defined brief, using current and relevant sources rather than accepted from a database as it stands.
Research can draw on company websites, professional profiles, company announcements, job listings, technology signals and your own CRM history. Tools support the work, but people check and interpret the information that decides whether a record is right for the campaign.
The starting question is different.
Waterfall enrichment asks: what is missing from this record, and can we find a value for it?
Researched data asks: is this account a genuine fit for our ICP, and is the information about it correct today?
That difference shapes everything that follows.
A waterfall is designed to stop when it finds an answer. That makes it efficient. It also means the first answer wins, not necessarily the best one.
Suppose Provider A holds an old job title for a contact who changed roles last year. The waterfall accepts that title and moves on. Provider B, which may hold the current role, is never checked for that field.
Now apply that to an ICP.
An ICP is a set of fit criteria: industry, company size, geography, business model, technology environment, buying structure and business context. Some of those are simple facts. Others need judgement.
A provider can tell you a company has 800 employees. It cannot easily tell you whether the company is an independent buyer or a subsidiary whose purchasing is controlled by a parent group. A tool can detect a platform on a website. It cannot tell you whether that platform is central to the business or a leftover from a project that ended two years ago.
Waterfall enrichment answers "Can we find a value?" Researched data answers "Is this value true, current and relevant to our ICP?"
Enrichment providers return the values they hold. A returned value shows that a provider has a record. It does not prove the record reflects the company or person as they are today.
When match rate becomes the main success measure, teams can end up celebrating coverage while accuracy quietly slips.
People change roles. Companies restructure, merge, rebrand and move into new markets. If the first provider in the sequence holds an outdated record, the waterfall has no built-in reason to question it.
The record looks complete, so it goes into the campaign.
Some of the most important ICP questions cannot be answered by a single field.
These are interpretation questions. They need someone to look at the evidence.
When different providers hold different values for the same company, a waterfall typically keeps the first and ignores the rest. The conflict itself, which is often a sign that something has changed, never gets surfaced.
This is not a small issue. Gartner names inconsistency in data across sources as one of the most challenging data quality problems organisations face, caused by data held in silos with overlaps, gaps or inconsistencies.
Every provider in a waterfall has its own collection and refresh practices. The more providers you chain together, the harder it becomes to say exactly where a given field came from and when it was last confirmed.
For teams marketing in the UK and Europe, that matters. The ICO's guidance on the UK GDPR accuracy principle says organisations must take reasonable steps to ensure personal data is accurate and make sure its source and status are clear. Knowing where each contact field came from is part of good practice, not an optional extra. This is general information rather than legal advice, so check your own obligations with your data protection team.
Researched data is not the answer to every data problem, and it is worth being honest about the trade-offs.
That is why the real question is not which approach wins overall. It is which approach suits each part of your ICP.
Researched data builds the more accurate ICP. Waterfall enrichment builds the more complete dataset.
If accuracy is the goal, research should decide which accounts qualify, especially for the criteria that need interpretation. Enrichment still earns its place for scale and basic gap filling.
Here is how the two approaches typically map to the layers of an ICP.
The pattern is clear. The closer a data point is to the question "Should we target this account?", the more it benefits from research.
Poor data is expensive. Gartner research from 2020 estimated that poor data quality costs organisations at least $12.9 million a year on average.
In B2B marketing, that cost rarely shows up as one big failure. It builds up quietly:
An inaccurate ICP does not stay in the strategy deck. It flows into every list, campaign and report that follows.
For most B2B marketing teams, the best results come from using each approach where it is strongest.
Start with your best existing customers. Identify the characteristics they share and separate the must-have criteria from the nice-to-have ones. Only the must-haves should decide whether an account enters your list.
Waterfall enrichment is useful for building a broad starting universe and completing simple fields such as company domain, headquarters location and approximate size.
Apply research to the criteria that need judgement: company structure, technology relevance, buying roles and business context. This is where false positives get removed.
When sources disagree, treat it as a signal. A different employee count or job title often means something has changed recently.
Note where each critical data point came from and when it was confirmed. This supports compliance, makes refreshes easier and lets you trust the data months later.
Compare validated accounts with CRM outcomes, won and lost deals and sales feedback. Your ICP should get sharper each quarter, not stay frozen in the version you wrote at the start of the year.
If most of your answers point to accuracy, context and trust, research should lead.
At Merit, we do not believe a static database should decide who belongs in your ICP.
We start with your brief. Our team researches accounts against your ICP, validates the information that matters and builds contact data around the specific audience you need to reach. Depending on your campaign, that can include company research, firmographic validation, contact research, technology information and business context.
Our database size is zero because we do not rely on a stock pool of contacts that already exists. We research to your requirements.
The result is data built around your ICP, your market and your campaign, not a generic list that simply has fewer blank cells.
Want an ICP your sales team can trust? Talk to Merit's marketing data team to build a researched target account list or validate the one you already have.
Waterfall enrichment is a data enrichment method that queries several B2B data providers in a set order. If one provider cannot fill a field, the record passes to the next until a value is found or all providers have been tried.
It improves coverage, but accuracy depends on the providers in the sequence and on any verification added afterwards. Because the waterfall usually accepts the first value it finds, an outdated record from an early provider can pass through unchecked.
Researched B2B data is company and contact data that has been built or validated against a specific brief using current sources, such as company websites, professional profiles, announcements and job listings, with people checking the details that decide fit.
Data enrichment is the broad practice of adding missing information to existing records. Waterfall enrichment is one way of doing it, where several providers are queried one after another instead of relying on a single source.
ABM depends on a small number of well-chosen accounts, so accuracy matters more than volume. Researched data is usually the better fit for ABM target account lists, with enrichment used to support contact details.
Yes. Many teams use enrichment to size the market and fill simple gaps, then apply research to the criteria that decide ICP fit, such as company structure, technology relevance and buying roles.
There is no universal schedule. Review it whenever your customer patterns, products or target markets change, and use CRM outcomes and sales feedback to spot when accounts or criteria have drifted.
