#749: Data Axle CEO Andrew Frawley on using identity resolution for stronger customer relationships

Summary

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The Agile Brand with Greg Kihlström®

Episode #749: Data Axle CEO Andrew Frawley on Using Identity Resolution for Stronger Customer Relationships

Date: October 10, 2025
Host: Greg Kihlström
Guest: Andrew Frawley, CEO of Data Axle

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Episode Overview

In this episode, Greg Kihlström welcomes Andrew Frawley, CEO of Data Axle, to discuss the pivotal role of identity resolution in modern marketing technology and customer experience (CX). The conversation delves into how high-quality, ethically sourced data enables personalized, omnichannel customer engagement and builds deeper, trust-based relationships—all within an evolving landscape defined by data privacy and AI.

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Key Discussion Points & Insights

1. Defining Identity Resolution

[03:18]

• Three dimensions:
  • Terrestrial Identity: What most brands have—first-party data connecting customers to physical identities.
  • Connecting Terrestrial to Digital: Linking physical data to digital footprints (an area of widespread struggle).
  • Understanding the Whole Person: Integrating consumer and business personas for a full, holistic view.
• Quote:

  “You need to market to the whole person, whether they're the business persona plus consumer persona or vice versa. We think that's sort of a missing piece to identity in most brands today.”
  — Andrew Frawley [03:55]

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2. Identity Resolution’s Impact on Personalization & Omnichannel Success

[05:08]

• Context for Every Interaction: Accurate identity enables brands to personalize in real-time—the right message, in the right format, at the moment of truth.
• Powerful with Generative AI: The more holistic the identity, the more tailored and emotionally resonant experiences can be delivered.
• Atomic Moments of Truth:

  “You've got seconds or milliseconds to decide what's the appropriate message, offer, content, creative... Technology can do that now if we have the right data to inform the decision.”
  — Andrew Frawley [05:15]

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3. Why Data Axle’s Approach Is Unique

[06:23]

• Emphasis on Data Quality:

  “You won't find companies that have more high-quality data than Data Axle has.”
  — Andrew Frawley [06:24]

• Ethical Sourcing: Compliance remains foundational—rigorous practices ensure alignment with regulations.
• Profile Fuse Innovation: AI-driven technology matches and links business and consumer identities, achieving high confidence at scale (100M+ connections, 85% confidence).
  • Hard Problem Solved:

    “That's a hard problem to solve, to say that Andy Farley in Boston, Mass. is the same Andy Farley that runs Data Axle in Dallas, Texas.”
    — Andrew Frawley [07:26]

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4. Beyond Acquisition: Enabling Cross-Sell and Retention

[08:30]

• Unified View Unlocks New Value: Identifying existing customers across B2B and B2C divisions empowers cross-sell.
  • Example: Cable providers recognizing a consumer customer as a potential small business customer and vice versa.
• Contextual Targeting: Use passion points (e.g., golf) for targeted offers across media like connected TV.
  • Quote:

    “Those audiences will absolutely outperform better than anything else you're deploying.”
    — Andrew Frawley [08:47]

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5. Privacy, Compliance & Ethical Data Use

[09:39]

• Adapting to Global Regulation: Dedicated teams and leading external counsel stay ahead of evolving regulations (GDPR, CCPA, others).
  • Privacy is “at the table” for every new product.
• Transparency for Customers:

  “All of our AI is observable... We can show how we came to a prediction and what data elements were part of that prediction—and what we kept out.”
  — Andrew Frawley [11:20]

• Value Exchange: Consumers increasingly accept data sharing for tangible benefits.
  • Greg Kihlström:

    “Consumers are willing to share data when there’s a value exchange... when they know they're going to benefit from it.” [12:14]

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6. The Future: AI, True Omnichannel and Data Quality Over Quantity

[13:57]

• Step Change in AI + Identity: Brands can finally act on the full potential of one-to-one, omnichannel marketing—delivering contextually-aware experiences across every touchpoint.

  “… We’re at the point where that is a reality… create a new set of challenges around measurement, but that's where I see the next four or five years—refining that art of the possible.”
  — Andrew Frawley [14:40]

• Advice for Leaders: Shift from “more data” to “better data” for meaningful results.

  “The pendulum needs to swing back to: I need more high-quality data… You could ignore false signals before… now the game has to go back to quality.”
  — Andrew Frawley [16:10]

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7. Staying Agile as a Leader

[17:02]

• Client-Driven Learning:

  “Every time I talk to a client I learn something… Best practices across industries can apply to others… We try to be very good at synthesizing and curating that input into both our strategic plans and tactical products.”
  — Andrew Frawley [17:03]

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Notable Quotes

• Greg Kihlström:

  “Agility requires not just reacting to change, but anticipating it and even shaping it. It demands a deep understanding of your customer and the ability to adapt your strategies in real time.” [01:12]

• Andrew Frawley:

  “You need to market to the whole person, whether they're the business persona plus consumer persona or vice versa.” [03:55]
  “Technology can do that now if we have the right data to inform the decision.” [05:15]
  “You won't find companies that have more high-quality data than Data Axle has.” [06:24]
  “That's a hard problem to solve, to say that Andy Farley in Boston, Mass. is the same Andy Farley that runs Data Axle in Dallas, Texas.” [07:26]
  “All of our AI is observable... We can show how we came to a prediction and what data elements were part of that prediction—and what we kept out.” [11:20]
  “The pendulum needs to swing back to: I need more high-quality data… now the game has to go back to quality.” [16:10]

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Timestamps for Key Segments

• 03:18 — Defining Identity Resolution
• 05:08 — Personalization, Omnichannel, and the “Atomic Moment of Truth”
• 06:23 — Data Axle’s Unique Approach and Data Quality
• 08:30 — Real-World Use Cases Beyond Acquisition
• 09:39 — Privacy, Compliance, and Ethical Data Practices
• 12:14 — The Value Exchange and Consumer Trust
• 13:57 — The Future: AI, Omnichannel, and Measurement
• 16:10 — Data Quality vs. Data Quantity
• 17:02 — How Andrew Frawley Stays Agile as a Leader

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Summary

This episode provides marketing leaders with insightful, practical guidance on how advanced identity resolution, rooted in high-quality and ethically sourced data, is the new foundation for driving marketing ROI and customer loyalty in the digital age. Andrew Frawley’s perspective highlights why “more” data is no longer better, and why the fusion of holistic person-level identity with responsible AI unlocks the next era of brand agility and customer lifetime value.

Transcript

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the Agile Brand. Welcome to Season seven of the Agile Brand where we discuss the trends and topics marketing leaders need to know. Stay curious, stay agile and join the top enterprise brands and martech platforms as we explore marketing technology, AI, E commerce, and whatever's next for the Omnichannel customer experience. Together we'll discover what it takes to create an agile brand built for today and tomorrow and built for customers, employees and continued business growth. I'm your host Greg Kilstrom, advising Fortune 1000 brands on martech, AI and marketing operations. The Agile Brand podcast is brought to you by Tech Systems, an industry leader in full stack technology services, talent services and real world application. For more information, go to teksystems.com to make sure you always get the latest episodes, please hit subscribe on the app you listen to podcasts on and leave us a rating so others can find us as well. Now onto the show. Are you building a brand that's building customer relationships and the data behind them to last, or one that's just trying to keep up with today's Omnichannel? Consumer agility requires not just reacting to change, but anticipating it and even shaping it. It demands a deep understanding of your customer and the ability to adapt your strategies in real time. Today we're going to talk about the critical role of data reliability and identity resolution in building an agile brand. To help me discuss this topic, I'd like to welcome Andrew Frawley, CEO at dataaxle. Andrew, welcome to the show.

[B]

Thank you Greg. Great to be here.

[A]

Yeah. Looking forward to talking about this with you. Before we dive in though, why don't you give a little background on yourself and your role at Data? Axel Sure.

[B]

I've got over three decades of experience with data, customer engagement, analytics, AI, so I really enjoy helping brands. You know Drive outcomes by building better connections both functionally and emotionally with their clients.

[A]

Great, great. So, yeah, let's, let's dive in here and we're going to talk about a few things today, but I want to start with the role of identity resolution. And so for marketers less familiar with that term, what exactly do we mean when we say identity resolution? And what are some of the symptoms of an organization that needs it, whether they know it or not?

[B]

Sure, there's a couple different dimensions to identity resolution. There's sort of what most brands have already accomplished, which is sort of terrestrial data identity resolution where we know where our customers are and we've got first party data that describes our relationship with them. The next piece comes in connecting that with the digital world. So where a lot of brands struggle is to say, all right, how do I connect my terrestrial identity with a person's digital footprint? And that's not an exact science, certainly. And it involves things like cookies, which, you know, we all know have been up and down from a deprecation standpoint a little bit. But, you know, there, there are fragments of identity floating all over the place. You know, different identifies by channel, by business, by geography. And so, you know, being able to stitch that together into a identity spine or identity graph that then links back to the terrestrial world is critical. And then the third dynamic or dimension of it is really understanding the full person. And this is something that we feel strongly about a data axle. Historically, people have either marketed to people as consumers based on their consumer identity or Persona, or professionally based on their business Persona. We think you need to market to the whole person, whether they're, you know, the business Persona plus consumer Persona or vice versa. And we think that's sort of a missing piece to identity in most brands that we talk to today.

[A]

Yeah. And so building on that, how does this accurate and to your point, more holistic identity resolution really impact a brand's ability to personalize customer experiences, measure marketing effectiveness and do all of that across all of the touchpoint, you know, the omnichannel touch points, whether it's offline online, all the above.

[B]

Yeah, well, you know, again, it, it first gives context, every interaction. So if you think about, you know, when you're interacting with a brand, you've got, I use this phrase, atomic moment of truth, but you've got, you know, seconds or milliseconds to decide, you know, what's the appropriate message, offer content, creative, you know, all of those things. And, and the reality is the technology has come a long way and we can do that now if we have the right data to inform the decision. So that's sort of the key piece. And then second again is to the point I made earlier, it's sort of the breadth of how well do we really understand the person and then how can we use that to again, all the great sort of gen AI technologies that are out there today is how can we inform a message that's not just right sort of functionally. We want to offer you this product at this price, but in a way that also creates an emotional connection between a brand and a person.

[A]

Yeah. And so you've been cited as a rare data provider by forrester for both B2B and B2C markets. What exactly what does that mean? Can you explain how your approach is unique and where maybe some of the current providers are not hitting the mark?

[B]

Yeah. So our philosophy is to identify high quality data so you'll find companies that have more data than Data Axle has, but you won't find companies that have more high quality data than Data Axle has. And we're very focused on quality. We're very focused on ethically sourcing the data. So it's compliant with all the regulatory environments that we have to deal with now. But to your question specifically, so we have both a third party data set of all the consumers in the U.S. we also have a third party data set of all the businesses and contacts within those businesses in the US on the business side, we still do things like we make 30 or 40 million phone calls a year to validate businesses and are they open and are they still at the address and things like that. So we use AI to cure that data, but we're still using people to curate it as well. And then what we think is probably the most innovative thing is we've built a product called Profile Fuse which links that business and consumer identity together. And so that's a hard, you know, it's a hard problem to solve to say that Andy Farley in Boston, Mass. Is the same Andy Farley that runs Data Axle headquartered in Dallas, Texas.

[A]

Right.

[B]

And when I joined the company a year or so ago, a year and a half ago, I challenged our, our data science team to. So let's take a fresh look at that problem. And they built a set of matching AI based matching technology that has allowed us to create over 100 million of those connections now at a 85% confidence level. So very high efficacy, high scale. And you know, we think that's a, you can't have the marketing or identity conversation without a capability like that.

[A]

Yeah, yeah. And so a lot of this is, a lot of the use cases for this involve customer acquisition. You know, whether that's B2B or B2C. Beyond that though, you know, how can marketers leverage this, you know, high quality data to improve things like cross selling or retention? You know what, what are some examples that you've seen that, that work well?

[B]

Yeah, one very common one we're working with a bunch of, you know, big brands is they have, you know, part of businesses that focused on small businesses and they have a, you know, part of their business focus on consumers. You know, think about your cable television providers. Yeah. So, you know, it's a simple use case. It's if I come to a website, I figure out if I'm a current customer first, second, if I'm a, you know, consumer customer, cross sell me small business and vice versa. So, you know, simple use case, something most people can't do. You know, those audiences will absolutely outperform better than anything else you're deploying. So, you know, that's just sort of one example, you know, other examples. We're doing a lot of connected TV work these days. And so if you're trying to sell me, you know, I T products, but you know, I'm a golf enthusiast, maybe you ought to be doing, you know, CTV to me around golf events.

[A]

Yeah.

[B]

So again, it's a, it's understanding that full person and leveraging it to, you know, both give them the right functional targeting as well as emotional targeting.

[A]

You mentioned a little bit about some of the, the privacy and you know, certainly could third party cookies is part of that as well. But you know, with, with regulations like gdpr, CCPA and many others around the world, how do you look at, you know, ensuring this high quality data but also ensuring ethical sourcing of it?

[B]

Yeah, yeah. So we, we have an internal team that, you know, is monitoring the regulatory environment and you know, and in the US know, it's still done largely at the state level. So we have to deal with, you know, tweaks and, and specific things, whether it's, you know, how we manage the data ourselves, how, you know, brands manage their privacy policies, those sort of things. We also leverage outside counsel that's active in Washington, sort of, you know, in, you know, on the front edge of what is being contemplated and actually involved in lobbying and things like that. So it's a, it's an important part of a, the input for our product strategy. You know, privacy has a seat at the table on every new product we build Basically, yeah.

[A]

And so those, those sitting on the, on the brand side, then, you know, obviously they're, they're being careful about the platforms that they choose for, for, you know, to support the things that you just mentioned. What else should marketing leaders be doing to, you know, what steps should they take to build trust and transparency around their data practices, both internally as well as with their customers?

[B]

Yeah, well, I mean, there's obviously the basics of, you know, making sure you're compliant and, you know, and everything is opt in. You know, I think depending on the industry, you know, if it's a regulated industry, there's a different level of compliance that's necessary, you know, to give full transparency to, you know, how, you know, a credit model or, you know, likelihood to buy a credit production model might be built. You know, you have to build to make sure there's no discriminatory data that sits behind that. All of our AI is observable. So, you know, we can, you know, show how we, you know, came to a prediction and what data elements were part of that prediction. And, you know, what we, we kept out of the mix. And then, you know, I think, you know, ultimately the data tells a story itself. If it, if it's working and consumers are responding to, oh, here's an offer that I actually want in a channel that I don't find too intrusive, you know, that tells you something. And so there is a connection between marketing performance and, and sort of the value of the data and the quality of the data.

[A]

Yeah, and I mean, that's a great point because I think at least the studies that I've seen, you know, consumers are willing to share data when they, when there's a value exchange. Right. So, you know, when they know that, okay, I'm providing this piece of information, but it's actually, I'm gonna benefit from sharing that as opposed to a brand that asks something completely unrelated for some reason. Tbd. Right. So, I mean, is that, that's part, that's part of the, the, the value exchange. Right. Is, is just making, making it clear, you know, when I, When I, as a consumer give something, I'm gonna get something in return, right?

[B]

Yeah. No, I think consumers, you know, they generally want to see offers for things they're interested in or they want to know about the new products just came out. You know, use the golf example. I'll always, like, you know, take the email that says there's a new golf club in the marketplace, you know, because I have a sensational desire to spend money on golf. Probably don't make any difference to my game. So you know, what sits underneath all that is sort of a, you know, a listening and reacting mechanism. And yeah, those you know, vary by channel and, and sort of Martech ad tech stack and then you know, also a marketing measurement framework. So you know, we really can get to these communications driving, you know, incremental value and the communications really causing the, the value or would have happened more organically.

[A]

Yeah, yeah. So looking ahead, what are you, you know, what, what are you excited about? What, what are some of the most significant trends that you're seeing that are shaping data driven marketing, particularly in the areas of data reliability and identity resolution?

[B]

Yeah, well, I mean I think obviously AI is the answer to all questions these days, but I think we're at sort of a step function point where for 10 years we've been able to target people very directly. I mean that capability has been there. It was hindered by the ability to create custom content at an individual level and by not really having, you know, the identity capabilities to know who the people are across channels. And so I think as we see more, you know, traditional predictive analytics come together with gen AI, there's an opportunity to really, you know, take all the, you know, the promises of digital marketing one to one marketing, whatever, you know, sort of name you want to put on it. You know, we're actually doing that now and doing it in an omnichannel basis, not a multi channel basis where each touch has the context of the prior touch. And despite years of work and lots of technology and data solutions, most brands still have trouble doing that today. And so I think, you know, we're at the point where that is a reality, you know, create a new set of challenges around measurement and things like that. But yeah, that's where I see the next four or five years is really sort of refining that are the possible.

[A]

Yeah, I mean, I agree, I mean I think the, the, the promise of AI is, is great and yet I mean, you know, in my consulting work I work with a lot of Fortune 500 companies and see this time and time again of there's great ideas but the customer data, data in general, but like the customer data has some challenges to it. And so you know, things like data management, identity resolution, all this stuff, it hits home because it's, if you can crack that then it really unlocks all of these, all of these opportunities. What advice would you give to marketing executives that are, again, they know this and yet they're struggling to navigate some of those complexities and what advice would you have for them?

[B]

Yeah, well, I mean, you're right, AI is only as good as the data it's based on, right? Yeah. So I think, you know, there, there has been a tendency over the years for marketers to say I want more data, just give me a bigger audience. And I think now, you know, the, the sort of pendulum needs to swing back to, you know, I need more high quality data that having all this false signal in there, you could ignore it in the past because the cost per impression was not very high and you know, more was better than last. I think now when that data is not just delivering a targeted audience, it's actually delivering content, potentially offers, potentially the game has to go back to quality. And so that's always been data action strategy over 50 years of history. But we think it's going to become more popular.

[A]

Yeah. Love it. Well, thanks so much for joining today and sharing your ideas and insights. One last question for you. I like to ask everybody, what do you do to stay agile in your role and how do you find a way to do it consistently?

[B]

Yeah, so it's a great question. I talk to clients. Every time I talk to a client I learn something. The world is changing. You know, there's a lot of best practices across industries that you can apply to other industries and we're fortunate to work across a lot of different industries. Data Axle. So I think, you know, and we try to be very good at from a leadership standpoint, sort of synthesizing and curating all that importance input into both our strategic plans but also our more tactical products we're going to build tomorrow, how we're going to change our service delivery model.

[A]

Yeah, love it.

[B]

Great. Well, thank you for having me, Greg.

[A]

Thank you so much. Again, I'd like to thank Andrew Frawley, CEO at Data Axle for joining the show. You can learn more about Andrew and dataxl by following the links in the show notes. Thanks again for listening to the Agile brand brought to you by Tech Systems. If you enjoyed the show, please take a minute to subscribe and leave us a rating so that others can find the show as well. You can access more episodes of the [e-mail] that's theagile brand.com and contact me. If you're interested in consulting or advisory services or are looking for a speaker for your next event, go to www.greggkilstrom.com that's G R E G K I H L S t r o m.com the Agile brand is produced by Missing Link, a Latina owned, strategy driven, creatively fueled production co op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. Until next time, stay curious and stay agile. The agile brand.