Data Quality Redefined: Beyond Merge/Purge and Hygiene

By Michael D. Fisher, CEO, Allant Group

For decades, the industry has operated under a limited and increasingly outdated definition of data quality. Merge/purge routines, NCOA updates, and basic file hygiene once served a purpose. But in a composable, real-time marketing environment, those practices are no longer sufficient. Marketers today need more than just “clean” data. They need complete, current, and decision-ready data. That’s why at Allant, we’ve redefined what data quality actually means and how it should serve the business.

The old model was built around suppression. The new model is built around activation. We need to reframe the conversation around data quality, from static suppression lists to dynamic identity orchestration.

It’s Time to Challenge Legacy Thinking

Let’s be honest: the process of defining data quality hasn’t changed much in 35 years. Most providers still treat a single compiled file as the “source of truth” and apply deterministic logic to identity based on that file’s construction rules. But here’s the problem: no one file is complete. Each data provider defines household structures, contact details, and identity markers differently. Relying on any single source of data means you’re accepting blind spots as truth.

At Allant, we see this every day. When we layer in a second, third, fourth, or fifth source, we consistently find incremental gains in accuracy, reach, and precision. That’s not just theory. It’s measurable. And it proves a critical point: if one source were truly sufficient, those gains wouldn’t exist.

So why has the industry clung to legacy methods? Because until now, no one has built a system capable of orchestrating across sources in real time. That’s where Allant is different. We’ve composed data ready for activation across some 16 sources and regularly pull in additional sources as needed, validating attributes at the element level, and constructing the most complete view possible of an individual and household.

Redefining What “Quality” Really Means

In today’s composable data environment, quality can’t be defined by formatting and suppression alone. It must be judged by fitness for purpose: Is this data accurate? Is it current? Is it aligned across sources? And most importantly, is it ready to drive business decisions?

With AMP+, Allant’s Audience Management Platform, we start at what I like to call “floor 25.” The first 24 floors, the cleansing, standardization, deduplication, enrichment, are already handled behind the scenes. That means your analytics, modeling, and activation efforts begin not from raw chaos, but from an already structured, prioritized dataset that’s ready to act.

AMP+ leverages real-time orchestration, comparing attributes across 16+ sources and validating them by fit, frequency, and fidelity. The result is a constantly evolving dataset that doesn’t just meet hygiene requirements. It anticipates analytical needs. We don’t shrink the file down to 270 million identities. We keep the full 5.5 billion IDs in play because there’s value in the long tail. Shrinking your universe to only the “knowns” limits your ability to find new audiences, test new hypotheses, or adapt to behavioral shifts. The truth is, data quality isn’t about what you remove. It’s about what you unlock.

Why Multi-Source Identity Resolution Is Non-Negotiable

The myth of the “single-source identity graph” continues to do damage. If your audience strategy is built on one view of the market, you are guaranteed to miss millions of people, especially those who don’t show up in traditional datasets. Think about affluent Gen Z consumers. Many of them bank digitally, avoid credit, ignore direct mail, and exist almost exclusively in behavioral and digital signals. Traditional compilers don’t even see them.

That’s why AMP+ uses a multi-source model. We compare and contrast attributes across providers in real-time. If source one and source two disagree, we validate using source three. If three out of five agree, we go with the majority. And if one source stands alone, we flag it. This isn’t a static data match. It’s active orchestration that continuously improves as more signals emerge.

And the persistent ID that underlies it all? It’s built once, then applied everywhere, from acquisition to loyalty, from marketing to customer service, and even into fraud and risk. This is what true enterprise-grade identity resolution looks like.

Beyond Marketing: A Business-Wide Advantage

While our roots are in marketing, the value of high-fidelity identity extends well beyond campaign execution. Underwriting teams use our data for real-time quoting. Risk managers use it for fraud detection. Customer service teams use it to personalize experiences. When every function in the enterprise works from the same identity spine, you eliminate duplication, accelerate resolution, and create consistent customer touchpoints.

And let’s not forget the brand risk of bad data. It only takes one poor service experience, one time where a customer says “you should’ve known me better”, to erode trust. In today’s environment, data isn’t just operational. It’s reputational.

Where the Industry Is Headed

The days of “I have a file, therefore I have the truth” are over. Brands are getting smarter. They know that accuracy requires breadth. They know that enrichment requires orchestration. And they know that activation begins with readiness.

What will become obsolete? The idea that you have to rip out your martech stack to evolve. You don’t. The tools you’ve chosen, email, SMS, DSPs, clean rooms, can all continue to operate. You just need better data feeding them. Composable. Cross-source. Current. And channel-ready.

That’s the future. And it’s already here.

Let’s Erase the Myths

There’s one myth I’d love to wipe from the industry’s collective memory: that data must be purged to be usable. That engineers should decide at ingestion what data matters. That raw is bad.

It’s not.

At Allant, we’ve built a data innovation factory in AMP+. We keep data raw. We keep it wide. We test, iterate, and refine. We introduce new sources (recently credit card transaction data) in weeks, not months. There’s no penalty for experimentation. And that’s where the biggest breakthroughs happen.

When brands are no longer constrained by single-source thinking, outdated processing logic, or rigid file structures, they can finally see their entire addressable audience. Not just those who opt in. Not just those who are easy to find. But those who matter.

Final Thought

The goal of modern marketing isn’t just precision or scale. It’s both. And it starts with data that’s composed for action.

So, the next time someone asks, “Is your data clean?”, I’d suggest a different question: “Is your data ready to move your business forward?”

At Allant, we’re not just redefining data quality. We’re enabling a smarter way to grow.

If you’re ready to activate your data and unlock its potential, let’s talk.