Marketers don't need more data—they need smarter data. When you unify your first-party customer data and layer it with predictive AI, you move from generic messaging to precise, revenue-driving actions. Whether it’s suppressing low-propensity audiences, expanding high-value segments, or optimizing media efficiency, organized data is the engine that powers real growth.

That’s a quote from Matt Greitzer and a sneak peek at today’s episode. Welcome to Revenue Boost: A Marketing Podcast—the show where growth-minded business leaders learn how to turn marketing into a measurable revenue engine. I’m your host, Kerry Curran: revenue growth–obsessed, go-to-market expert, and industry analyst. Each week, I sit down with the brightest minds in marketing, sales, and customer success to unpack the real-world strategies that drive sustainable growth.

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Today’s episode is all about the power—and the promise—of unified customer data. In From Siloed to Strategic: How Unified Customer Data Fuels Predictive Marketing, I’m joined by Matt Greitzer, CEO and co-founder of Actable. Together, we explore how smart brands are turning fragmented data into actionable intelligence using AI, clean cloud infrastructure, and strategic alignment across teams.

Whether you’re dealing with outdated systems or trying to scale predictive modeling, this episode walks through the foundations of better segmentation, smarter media targeting, and lifecycle personalization that drives real results.

Stay tuned until the end to hear Matt’s practical advice for data readiness—and what to do if your ESP is still your database. Let’s go!

Kerry Curran, RBMA (00:01.432):
So welcome, Matt. Please introduce yourself and share your background and expertise.

Matt Greitzer (00:06.898):
Sure. Hi, Kerry. Thanks for having me. My name is Matt Greitzer and I'm the co-founder and CEO of Actable. Actable is a company that works with enterprises to organize and enhance their first-party customer data to get them ready for AI-driven scoring and segmentation.

Kerry Curran, RBMA (00:30.016):
Excellent. You've been in the media space, media buying, and strategy. Talk a bit about your background before you got to Actable and how you identified the need for customer data.

Matt Greitzer (00:44.5):
Sure, yeah. That’s right. I spent 20 years in media, ad tech, and advertising. I started my career in the dial-up era at a company called Avenue A, which became Razorfish. I had a few different roles there, but the most formative one for me was running the search engine marketing practice, where I really got into the quantitative side of marketing.

I then started the programmatic media practice at Razorfish and eventually left to start a business with a former co-founder of mine called Accordant Media, one of the first programmatic trading desks in the space—again using quantitative information to make better media buying decisions.

We were acquired by Dentsu in 2016. Through that acquisition, we ended up running the programmatic practice at Dentsu. Dentsu had also acquired a much larger company called Merkle that same day. That’s where I first got exposed to first-party customer data. We worked very closely with a group at Merkle that used first-party customer data to build segmentation and use it for targeting in advertising.

From that experience, I realized that this would be the future—how marketers would create differentiation in the face of signal deprecation and increasing personalization needs. So I left Dentsu in 2019 and in 2020, co-founded Actable with Craig Shin, a long-time colleague. We worked together at Razorfish and Accordant.

Our thesis at Actable was that enterprises would create differentiation with their own customer data—but they’d need help organizing it coherently and bridging the gap between IT (who owns the tech) and marketing (who uses it). We’ve stayed true to that ever since.

Kerry Curran, RBMA (03:41.740):
Yeah, thank you. You've got such a rich background across both media buying and internal data challenges. I remember in the late 2000s, "big data" became the buzzword—brands and marketers suddenly had an influx of data. But now we’re seeing how much smarter we can actually get with it.

So talk about the business challenges you’re helping solve today and how the data connection applies at a strategic level.

Matt Greitzer (04:39.362):
Sure. The business challenges are the same ones most marketers and advertisers face: reducing customer acquisition cost, decreasing churn, and improving retention.

What we see is that companies have spent a lot on tech and data collection, but have suboptimally organized that data. So we come in and say: the problem isn’t the data itself—it’s how it's structured. Most enterprises don’t have a coherent infrastructure to activate customer data effectively.

Think of it like a car—you don’t buy it for the engine, but you can’t go anywhere without one. Similarly, if you don’t have a strong data foundation, you can’t activate it strategically. The whole promise of “data-driven marketing” has only partially been realized because foundational customer data is often disorganized.

Kerry Curran, RBMA (05:56.371):
Right. And it's not just for ad targeting. You’re helping unlock that holistic customer view. Talk about how that data powers broader business goals like predictive modeling or churn prevention.

Matt Greitzer (07:24.192):
Absolutely. We work with a top 10 grocer—doing $16–20B annually. If they lose a customer, that’s a massive revenue gap. We helped unify their in-store, web, and app data to identify signals of churn. That allowed them to proactively retain at-risk customers.

It’s a $60M+ opportunity annually for them. But without unified data, they’d never have seen the signal patterns to act on.

And this isn’t limited to grocers. Whether it’s increasing basket size or new customer acquisition, we focus on identifying signals that lead to the right interventions at the right time.

Kerry Curran, RBMA (09:15.404):
That’s so smart. I know you also help predict next purchases or propensity to buy, which helps brands prompt that next transaction. So what verticals are you most active in?

Matt Greitzer (09:44.418):
Retail is a big one—grocers, apparel, and big-box retailers. We also work with CPG brands (who are newer to customer data), publishing (especially subscription-based models), and financial services. We’re not vertically exclusive, but those four are where we’ve built the most depth.

Kerry Curran, RBMA (10:46.926):
Makes sense. Let’s talk tech—what kind of systems do you typically start with? How do you bring these data sets together?

Matt Greitzer (11:06.880):
The starting point is almost always a well-structured cloud-based customer data warehouse. You’d be surprised how many enterprises don’t have one. It’s foundational—and not that expensive or time-consuming to implement.

For us, Google is our primary partner. From there, we help unify web, transaction, offline, and media exposure data. Then we layer in customer data platforms (CDPs), which help with orchestration and identity resolution. But CDPs are just one part of the solution.

Beyond that, we’ve built our own AI capabilities for scoring and segmentation—so clients can identify high- and low-value customers automatically and activate those insights across channels.

Kerry Curran, RBMA (13:29.582):
Yes! So first it’s unified data, then segmentation, then AI. That’s how you’re enabling predictive modeling and smarter engagement.

Can you give another example?

Matt Greitzer (13:50.636):
Sure. We work with a large retailer that’s traditionally relied on catalogs. What we found is mailing catalogs to high-propensity buyers has minimal impact—they’d buy anyway. But mailing to low-propensity buyers had huge lift. That insight saved them tons in print costs and drove more incremental revenue. It was only possible with better segmentation.

Kerry Curran, RBMA (15:04.194):
So smart—and so much more effective. Suppressing low-propensity buyers from media targeting must also drive efficiency.

Matt Greitzer (15:38.630):
Exactly. Suppression is a great tactic—but you need the data structure to identify who to suppress. That’s why the foundation matters. Once you’ve got the “engine,” you can go places.

Kerry Curran, RBMA (15:58.380):
And once the data is unified, you can also personalize messaging and creative, right?

Matt Greitzer (16:48.514):
Absolutely. But the challenge is that CMOs often don’t own the data. IT or a CTO does. We’ve gotten good at aligning both sides by focusing on use cases and ROI.

Kerry Curran, RBMA (18:32.930):
That’s a huge value add—being the translator between IT and marketing. This is what’s needed for real company-wide revenue growth.

Matt Greitzer (19:40.450):
Exactly. Customer data is a powerful asset—but too few companies know how to unlock it. We step in and help them do just that.

Kerry Curran, RBMA (19:57.070):
So true. For anyone listening, what do they need to have in place before they’re ready to work with you?

Matt Greitzer (20:32.698):
Honestly, nothing. We meet clients wherever they are. Whether your ESP is still your customer database, or you’re more mature, we always start with use cases. That’s how we define success—and how to get there.

We also have a free Customer Data Readiness Assessment on our website. It’s a 5-minute quiz that helps teams benchmark where they are and what to do next.

Kerry Curran, RBMA (22:15.596):
Perfect. So how can people find you and learn more?

Matt Greitzer (22:23.394):
We’re at actable.com — that’s A-C-table.com — and I’m at [email protected]. Feel free to reach out!

Kerry Curran, RBMA (22:39.840):
Excellent. We’ll include that in the show notes. Thank you so much, Matt. This was such a smart and helpful conversation.

Matt Greitzer (23:09.228):
Thanks for having me, Kerry. I hope it was helpful to your listeners.

Kerry Curran, RBMA (23:14.478):
Absolutely. Take care!

Thanks for listening to Revenue Boost: A Marketing Podcast. If this episode gave you a new way to think about customer data, predictive modeling, or cross-functional alignment, send it to a teammate or your favorite data partner. Don’t forget to subscribe and leave us a review on your favorite podcast app—it helps other revenue leaders find us. And if you're ready to unlock smarter segmentation, cleaner data, and better results across your go-to-market strategy, visit revenuebasedmarketing.com.

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