AI Agents Will Take 50% of Your Traffic — Is Your Data Ready? | Jeff Lunsford, CEO of Tealium

20% of enterprise website traffic is already coming from AI agents rather than humans, and that traffic converts at 38% more revenue per session than human visits. Within a year, Jeff Lunsford expects that number to reach 50%. Jeff, CEO of Tealium, joins Craig Smith to explain what this shift actually means for every business with a digital presence, and why the companies that will win are the ones whose data layer speaks fluently to agents, not just human browsers. Tealium operates as a neutral, real-time collection and distribution layer that sits underneath all of a company's customer-facing systems, capturing every interaction as it happens and distributing enriched identity-resolved profiles to whichever downstream system needs them - from personalization engines to fraud models - without storing the data itself. The most important argument Lunsford makes is one that Craig sets up precisely: agents need current state, consented context on demand, and a data warehouse offering yesterday's picture doesn't just underperform, it actively produces bad recommendations that erode trust in the AI system. He uses the pilot analogy he's carried for fifteen years: you don't want to fly knowing your altitude from yesterday, and for the same reason you don't want your customer-facing agent making decisions on stale data. The episode also covers the pattern that governs every channel transition in business history, brick-and-mortar didn't disappear when phones arrived, the internet didn't disappear when mobile arrived, and human website traffic won't disappear when agents arrive. Total session volume goes up because agents make it easier to initiate interactions. The businesses that prepared for each transition early captured disproportionate value. The businesses preparing their data layer for agentic consumption now are doing the same thing. Subscribe to Eye on A. I. for weekly conversations with the people building and deploying the future of AI.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Craig S. Smith?

  We're still early days in agent adoption by enterprise, certainly.

• 0:05Speaker 01

  The future is going to be wild, but humans are not going to go away. Your traffic is going to grow, probably 50% of it by mid next year will be agentic. But it's not, that doesn't mean your human traffic got cut in half.

• 0:19Craig S. Smith?

  In agentic commerce, there's a gap right now because agents need current state consented contacts on them. And a warehouse can only offer yesterday's picture.

• 0:32Speaker 01

  This agentic traffic is converting at about 38% more revenue per session than the human traffic is. Our customers today, about 20% of their inbound traffic is inbound agents, not humans. Even before AI, 40% of their traffic was bots. What used to be human traffic is now agentic traffic. When you go to a website with your browser, there's a hidden layer of data that the human eye never sees. But that's right where the agent goes to do its cleaning.

• 1:04Craig S. Smith?

  First of all, describe Telem to listeners, where it is in the stack, what it does. I mean, the, the, the software that Telem's making.

• 1:13Speaker 01

  Sure. So Telem is a neutral data collection platform that runs underneath all of a company's customer experience systems. So web, mobile call center, point of sale, branch store, ATM kiosk. And above stack from the cloud data warehouses in the backend transactional system. So we're basically a listening and collection and enrichment and distribution layer. And we position the company neutrally across the industry. So we integrate with about 1,300 different vendors across martech, customer experience, data warehousing, transaction processing. And help our customers just listen to all this real time data, resolve it around identity, create enriched visitor profiles.

• 1:58Speaker 01

  And then federate those back out in real time to all these systems that can benefit from that real time view.

• 2:04Craig S. Smith?

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• 2:45Craig S. Smith?

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• 3:30Craig S. Smith?

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• 4:04Speaker 01

  It is an orchestration layer. It's data orchestration. And so, you know, and, and we can do customer journey orchestration through data orchestration. So as the visitor profile is enriched, you might fire off different experiences through different systems. And use this as a data orchestration layer. And we also though are a very open architecture. And sometimes we have companies that just use us for data collection, filtering and enrichment. Other times they use us for identity and visitor profiling and complete orchestration. And in all cases, we're sending data back out, you know, what we call activation of various customer experiences or to various data endpoints that can benefit.

• 4:48Speaker 01

  Which obviously the, the name of your podcast and the most obvious beneficiary of great data is AI. And so, you know, over the last three years, we've just seen a huge upswelling of customer use for AI use cases.

• 5:02Craig S. Smith?

  Yeah. Most of the people I've spoken to about orchestration layers or orchestration software are talking about managing agents. But this is broader than that. Is that right? Or do you also orchestrate agents within a workflow?

• 5:21Speaker 01

  So we do not grab a hold of an entire agent and orchestrate it. We just feed agents data and context and fresh real time context. So trusted context where you know the, you know, the, the consent status of the visitor. So what we are doing is collecting data, labeling data, filtering data, enriching data. And then feeding it into AI models. And sometimes that could be an agentic use case. Sometimes it's just a fraud algorithm. You know, sometimes it could be a next best action algorithm.

• 5:56Craig S. Smith?

  The, the term data orchestration itself is more as AI has taken over. What, what does it actually mean in the modern stack as an architecture and, and not, not as a buzzword?

• 6:10Speaker 01

  Yeah, sure. So if you think back, I don't know, 10 years ago, we, we really started building this actually at 2012. What data scientists were doing to get great data was they're running batch data pipelines. And, and they were just set up a series of batch backward looking data pipelines. They'd pull data together, they'd run an ETL process, and then they might send that new pipeline somewhere else. And that is a cascading backward looking expensive way. And suboptimal in our view, because what happens is you get Tuesday's data on Monday, right?

• 6:52Speaker 01

  And now roll the tape forward to an AI agent and you don't want to give that AI agent context. It's 24 hours stale, right? And so not only is it suboptimal, it's much more expensive. So when we invented Telem, we said, we, we looked at like Tibco, which was message bus in the mainframe era. WebLogic, which was a neutral app server in the internet era. And, you know, we said enterprises need a real time data orchestration layer where instead of doing pipelines from each of these, you know, the average company uses 200 different software packages. And I'd say at least 30 contribute to the customer experience.

• 7:31Speaker 01

  So instead of just running pipelines from all those 30 systems, let's just listen to the event level traffic created from each of those systems in real time. And then let's, it's basically real time ETL. So we take the event, we resolve it around identity, enrich a profile, and then send it on its way to wherever our customers want to send it. And that may be to, you know, an open AI conversion API or Google or Meta or Tik Tok or Reddit for advertising. It might be to an email system or for audiences. It could be, it could go anywhere. And back to the data warehouse for analytics.

• 8:09Speaker 01

  And so that orchestration of those real time events, I think the term orchestration really comes into play when you flip from batch to real time. Because you're literally catching events in real time, orchestrating where they go, what they look like, how they're labeled, and then sending them on their way. And that requires coordination. It requires a, a hardened enterprise system. Because many of these software companies in the internet itself.

• 8:37Speaker 01

  Are not natively and truly real time to the first byte. And so you have to harden it. So if, if we send an event in the, the other vendor doesn't catch it, then we need to know that so we can resend the event, right? So, um, otherwise it just drops on the floor and you have data loss. And so that's a lot of the orchestration is, think of it as trust, reliability and observability. Taking an event from point one and sending it to point two. And, um, that's part of the orchestration. And the other part is, is I said earlier, like you can enrich that, that event, that payload. And it goes from raw event data to a, a robust visitor profile.

• 9:21Speaker 01

  Whether they're a known visitor or unknown, now you can create some crazy experiences that are going to convert better for that, that visitor.

• 9:28Craig S. Smith?

  Can you give us some, a use case? I mean, walk us through, uh, you don't have to name a customer, but a, a typical customer and how they're using it.

• 9:39Speaker 01

  Certainly. So let's take a large retailer, global retailer that has, you know, multiple brands. And that retailer wants to capture customer activity and prospect activity across their website, across their store traffic, um, across their mobile app and across all four brands. And so they will configure Tealium as the data collection layer. They will, uh, listen to event level data from all those different properties, uh, digital and physical. They will enrich the visitor profiles in real time.

• 10:21Speaker 01

  And then they can enhance an experience. So if someone's looking at something on their mobile phone in the mall, and then they walk into a store and now these retailers have, you know, iPads for the store owners. I'm sorry, the store employees and says, oh, oh yeah, uh, Mr. Lunsford just walked in and he was just looking at, you know, men's 34 inch jeans or whatever. And so you can inform an in-store session with what just happened digitally. You can inform a call center session with what just happened digitally. You can put people and email people that let's say abandoned things in a shopping cart. You can put them in a retargeting campaign, whether it's retargeting of display ads

• 11:03Speaker 01

  or whether it's a follow-up, you know, reminder with a coupon offer via email. And then you can take these enriched profiles and you can also send them back to your cloud data warehouse where you might run big workloads and break them into audiences. And then, you know, take an entire audience and you would use a Tealium to extract that audience and go activate that. That audience might be again, for a digital media campaign. It might be for first, first page personalization. It might be part of a loyalty program. And so, uh, that particular customer uses us for basically everything I just, I just walked through.

• 11:40Craig S. Smith?

  I mean, this idea of real time, that, uh, a shop clerk could get an update, uh, while you're in the store, that's from your online activity, right?

• 11:54Speaker 01

  Yeah.

• 11:54Craig S. Smith?

  Um, that's pretty powerful. Can you talk about why real time? And that's an obvious example, but why real time is so important today?

• 12:03Speaker 01

  You know, it, real time experiences convert at 30 to 200% higher rates than delayed experiences. Um, another example is an airline, you know, when you're traveling in the middle of a trip and your airline is telling you what gate, what baggage claim, you know, all of that is in, in the moment, real time customer's engagement. And, you know, a sporting venue is an example. Uh, we were just at a sports league today in New York, uh, one of my team members. And, you know, so all, all, if you think about it, almost all digital experiences

• 12:46Speaker 01

  will be higher, more engaging and higher converting if you're using fresh context. Period, full stop, you know? And I think AI has just shined a, a light on that. We've had data since 2012 that, you know, if you send an email four minutes after they leave the website versus 24 hours after the open rate is like six X, you know, it's crazy. Um, and so it's intuitively obvious to us. And it's interesting, over the last decade, people would debate that you, you know, you don't need real time data. And, you know, I'm a pilot, so I'm always thinking, I do not want to fly my airplane knowing what my fuel status was. You guys, I want to know my altitude right now and what's in front of me.

• 13:30Speaker 01

  So it's kind of obvious to, to me.

• 13:33Craig S. Smith?

  In the case of someone doing a search, uh, for jeans on their phone and then walking into a store, uh, what's the data flow? I mean, if, if, is it, is it the, the, um, platform that you're look, looking at that then is captured, that data is captured by, um, I assume it's the, the, the store is the, the customer that's using Tealium. Uh, what are the different channels for them collecting data?

• 14:09Speaker 01

  The data flow is basically, we're always listening to all of the systems. If a customer has, have, has us fully deployed. And any interaction on any of those systems creates events. Those events stream into Tealium in real time. And then our customers and we help them, you know, create use cases of, you know, I want, if someone, an employee in the store pulls up the iPad, someone's profile, I want to populate it with the most up to the millisecond activity. And so that would be a pull from the store system out of this database. Or it might've been a push because our customers can also set up, uh, rules where they say anytime an event anywhere happens,

• 14:54Speaker 01

  send it to the in-store because those in-store experiences are so valuable and high converting. And we want them to have larger checkout volumes.

• 15:00Craig S. Smith?

  This is something that everyone asks. Uh, you know, we've all had that experience of talking about something, uh, and then getting served an ad for it. Uh, is that part of this real time data flow? Or, or do you have any insight into that?

• 15:18Speaker 01

  That, that definitely is. And so the listening capabilities would just be one of those customer experience systems that I talked about that we would be listening to real time events. And it would be up to our customers to map, you know, from that software or us to, if we didn't, if there's a vendor that sells that listening software, we would build a connector to that vendor and, um, receive those events. A lot of times that's kind of a, happening in a walled garden where perhaps the device owner, um, also who operates the OS here, you know, also might be interested in advertising to you. And so that, that knowledge might even just stay client side on the phone to be privacy compliant.

• 16:03Speaker 01

  Um, there are all sorts of wild things going on, um, out there in, in the digital space. But what that is, is just classic, uh, intent targeting. So I can divine your intent, whether it's listening to you verbally, listening to the click stream of your website behavior. You know, listening to the clicks on your mobile phone. I'm still listening, um, to that data and then I can infer intent. And then I can go try to engage with you at the point in time when you have the highest propensity to convert.

• 16:36Craig S. Smith?

  A, a question, you know, I've been back and forth with your team, uh, uh, talking about, uh, why the modern stack needs to support real time and event triggered activation at once. And, and they said, instead of forcing teams to pick one architecture, what does that mean? Instead of forcing teams to pick one architecture?

• 17:00Speaker 01

  Well, we will, we definitely handle batch delayed data because a lot of companies only have the data in batch format. Um, and we'll take the, as data as fresh as we can. And so we don't go in and say, you have to be real time. I'm going to say, you know, let's get the best data you have and resolve identity and profiles around the best data that you have. And we also are, um, there's a big kind of debate in the industry right now of, you know, should your audiences live in your cloud data warehouse? Should they live in your CDP? Should they live in your marketing cloud?

• 17:40Speaker 01

  And our view is we can operate any of those three ways, right? Um, in our, the highest and most valuable use of Tealium is not that we have to hold the audiences. It's that we glue together on a trusted fabric, all of these systems, you know? And we do it in a very, in a very trusted, privacy compliant way. And we do it with high performance around the globe and with effectively zero data loss, you know, enterprise grade reliability.

• 18:15Craig S. Smith?

  Yeah. And so how do you activate data that lives in Snowflake or Databricks or BigQuery, uh, Redshift? Or one of these, uh, in real time without, uh, creating a shadow copier or a second source of truth, right?

• 18:32Speaker 01

  Yeah. So, so we have, uh, a capability called Cloud Stream. And we'll go extract an audience out of the CDW and activate it in real time out to, you know, whatever activation point they want to go to. Um, and again, those rules of where does that audience get sent and for what campaigns are defined in our platform. But it's typically triggered off of some inbound event. If this inbound event happens, then go pull this audience and activate it out here.

• 19:05Craig S. Smith?

  Yeah. Is this primarily for, I mean, I would imagine it's not, but the use case you gave was a retailer. What are, what are some of the other enterprise use cases beyond retail?

• 19:19Speaker 01

  There, there are many. So, you know, we have like 10 of the largest banks in the world, used Tealium, six of the 10 largest telcos, three of the five largest airlines. So massive companies across all industries.

• 19:32Speaker 01

  You know, in the banking space, when, when someone is going to

• 19:38Speaker 01

  apply for a home equity loan or in the insurance space, when someone is going to, they purchased a new car and they need auto insurance. They're going to transact very quickly. It's a considered purchase, but there's only a window. And then auto dealerships, we have a lot of auto dealerships to use Tealium. You know, when I'm searching for that new car for my daughter who's coming home from college or used car or whatever, you know, I'm going to probably get that done that Saturday. Cause I've allocated the time to do it. And all industries benefit from real time. And it just, it kind of makes no sense to engage in a debate that, oh no, delayed data is better.

• 20:23Speaker 01

  It's slower, it's more expensive. It requires more storage space because you're storing it in a whole bunch of different places. You know, it just doesn't make sense in our, in our view.

• 20:34Craig S. Smith?

  Yeah. And so do you, do you see these systems all becoming real time? I mean, all data flows converting to real time, or I would guess there are use cases where real time is not important.

• 20:52Speaker 01

  You know, the irony is when I got out of the Navy in 94, I started working in bank technology. And as you know, banks, you know, process checks through these big reader orders every night. And then they run a batch process through their deposit system on the backend and that's a classic batch process. Well, in, I think 95 or 96, people started building real time core banking systems.

• 21:20Speaker 01

  But the industry never upgraded to, still today, you have batch processes with all these large banks. And so yes, you can get a real time transaction done today, but there's still batch processes behind the scenes. And, um, you know, I think there's inertia there. There's just, you know, this is a system that works. And so that's why we found ourselves, well, obviously accept batch files. We do a lot of file import into Tealium.

• 21:54Speaker 01

  But we also preach real time and everything we do is a complimentary layer. We don't really replace anything Craig, other than point to point integrations.

• 22:06Speaker 01

  So we work with all the big martech folks and we just complete the last mile of these real time use cases. And we make their systems better because they get better data. And we'll go in and replace any of them. We just replace the point to point integrations, which is expensive to maintain that as well.

• 22:26Craig S. Smith?

  Yeah. I mean, there are vendor imposed schemas, right? Why do those become bottlenecks as stocks modernize and what does it take to activate data?

• 22:43Speaker 01

  A, um, let's say an email vendor, you know, they, they create a schema and it's optimized for email. And you know, let's say a website, A B testing vendors optimize their, their schema for that purpose. And we built an open schema so that you could map all of the different elements or attributes into this open and flexible schema to create a superset of all the attributes you want to track. Or, you know, about your visitor's behavior. And, you know, Palantir calls this an ontology.

• 23:25Speaker 01

  And they're doing it kind of at the enterprise level, not just customer data, but all of your data. We specialize in, I don't want to just call it customer data because it's really visitor data, prospects and customers. But you basically create a comprehensive ontology about your visitor behavior. And then you map the attributes from all these different systems into that, so that you get this comprehensive view. And then all the systems can benefit from seeing what the others have seen, right?

• 23:55Craig S. Smith?

  Yeah. And I would imagine in, in financial data, this becomes critical because you, you want

• 24:05Craig S. Smith?

  otherwise you're going to end up with a, a gap between the data that's exposed to or displayed to a user and the actual data at that moment. Is that right?

• 24:20Speaker 01

  Yes. Now we're typically not doing like financial account balances. We're helping create an experience for let's say a loan application or an insurance application or something like that. You know, we're more top of funnel stuff. And then the backend transaction processing systems will populate balances.

• 24:42Speaker 01

  But basically anything behavioral is where Tealium operates. And that behavioral data can then help you with all sorts of things. Next, like I said, pricing, next best action, fraud, personalization, personalized content, you name it, all of which leads to higher conversion.

• 25:02Craig S. Smith?

  Yeah. I asked about agent orchestration at the beginning because the use of the term orchestration layer in most of my conversations is about orchestrating agents or, or switching between models, that sort of thing. But in, in agentic commerce, there's a gap right now because agents need current state consented context on demand. And a warehouse can only offer yesterday's picture.

• 25:44Craig S. Smith?

  So what does it look like when orchestration is done right?

• 25:51Craig S. Smith?

  Well, why don't you ask, answer that first?

• 25:54Speaker 01

  Yeah, sure. So our customers today, about 20% of their inbound traffic is inbound agents, not humans.

• 26:05Speaker 01

  Even before AI, 40% of their traffic was bots. And, and so the 20% is really 20% of their good traffic. What used to be human traffic is now agentic. And agents still come in through the website. So what, what we're explaining to customers is like, you know, agents aren't killing the web. If anything, you know, the, the website is more important because that's the front door through which the agents access you. But you want to be able to speak their language and, you know, whether it's A to A or MCP or A to C. What we help our customers do is prepare their data layer on the website for that inbound agentic traffic.

• 26:48Speaker 01

  So there's a hidden, uh, when you go to a website with your browser, there's a hidden layer of data that the human eye never sees, but that's right where the agent goes to do its thing. And, you know, we can pull data, we call this data layer enrichment. So we can pull data out of the backend where the visitor profiles are. And you have all these attributes about your visitors and we can pull it out of the C W. And we can put it in the data layer so that when the agent comes in, they have everything they need right there in the data layer. And then you'll get higher converting traffic.

• 27:26Speaker 01

  And this agentic traffic is converting at about 38% more revenue per session than the human traffic is. So this is really important traffic and we're just helping our customers optimize their data layer. Agents like to, like JSON, JSON dash L D, which is basically kind of a pre-configured definition of what data elements means, like pre-labeled data. And so that you can put that on your website and then the agents are going to like you. And you want to be one of those websites where agents can get accomplished what their users ask them to accomplish.

• 28:10Speaker 01

  That means they'll rate you higher and rank you higher the next time around.

• 28:15Craig S. Smith?

  Yeah. And you're talking about websites that agents contact or systems that agents, external agents contact. But you're also talking about companies running agents and feeding them real time data.

• 28:33Speaker 01

  Inside the enterprise, obviously you're going to have AI models. Sometimes they might be agents that are doing a specific task like fraud, you know, next best action. Whether you call that an agent or a model or a skill, that's up, that's up to you. And then, you know, that's part of the agentic enterprise. And then just the fact that your customers are going to be coming, asking their agents, they're going to, they're going to entitle their agents with their username, a certain budget to act, certain authorized activities to come do their bidding on your website.

• 29:11Speaker 01

  And you better be able to handle that. Otherwise that and the customer will pick and, and/or its agent will pick a different vendor where the agent can do their, their bidding.

• 29:22Craig S. Smith?

  Yeah, we're still early days in agent adoption by enterprise, certainly. And what did you say? Did you say 20% of of traffic is agentic now going into? How do you see that changing? And what does that mean for Tealium?

• 29:45Speaker 01

  Well, we think it'll be 50% a year from now. And you just look at the slope and the trend and how much, you know, how much more usable these agents are becoming. People are going to be just talking to their agents on their phone and saying, hey, go go look up this trip for me. Go book dinner for me.

• 30:06Speaker 01

  And the internet's going to disappear into the walls. So, you know, the the idea of a screen

• 30:16Speaker 01

  and being required to access the internet or information or transaction capability. It's always going to be present, but you're also going to be able to do it just through voice. And in that voice capability, it will probably access the same front door. Right? It just won't require HTML rendering. And yeah, we just see, you know, the the future is going to be wild, but humans are not going to go away. Right? Your your traffic is going to grow. Probably 50% of it by mid next year will be agentic.

• 30:58Speaker 01

  But it's not that doesn't mean your your human traffic got cut in half. It means there's just more activity because it's easier to do things now. It's easier to send your agent to go off and do work and search for things. And so we think, you know, net net overall sessions are going to go way up.

• 31:17Speaker 01

  Something like half of it will be agentic. You can't forget the human interface, though, because they still want personalization.

• 31:25Speaker 01

  Still have to track consent and all these things that you have to do today. So really, AI is and agents are just another delivery channel on top of all of your other existing channels. Like, they're not replacing anything. And this is what's been going on, you know, since the beginning, when, you know, first you had brick and mortar. Then you had phones to add to that. Then you had IVR, and then all of a sudden, the internet came along. Then all of a sudden, mobile came along, you know, just as one layer and none of these, if that brick and mortar is still there, right? And so these things are just layering on top of each other. And the best in class companies are going to engage their customers in each channel.

• 32:10Speaker 01

  Right? And they're going to give them a consistent experience across all of those channels. So that the channels speak with each other back at the data layer where Tealium exists and understand what has happened across all those channels.

• 32:22Craig S. Smith?

  Yeah, and and you mentioned something interesting that that you don't need the HTML rendering. Because agents are are talking directly to the systems. I had a fascinating conversation with a guy about

• 32:42Craig S. Smith?

  clinical trials on new drugs, which is, you know, it takes a lot of work. And you have to produce all of these documents and the trial plan. And you end up with with, I don't know how many pages and pages and pages of of documentation that you send to the FDA. And then the FDA just feeds it all into an AI. So so people are saying, well, pretty soon it's just going to be sending data to an AI to the FDA's. Your agents sending data to the FDA's agent.

• 33:24Craig S. Smith?

  And and a lot of that stuff will happen in real time. Do you do you see that happening in other areas? And, you know, where you don't need that? The the the papers, you don't need the PDFs, you don't need the HTML rendering.

• 33:43Speaker 01

  Well, yes, I think, you know, we've just seen increased digitization of everything over, you know, since I've been around here since whatever 32 years and you know, I remember sitting at overhead projectors writing with acetate. Right? And then came PowerPoint. But then you would print your PowerPoint slides up and you would print them out and put them on an overhead projector. Right? Then came, you know, projectors that could take connect to your laptop and you never print it out like so. Look, everything is getting digitized,

• 34:26Speaker 01

  including forms, hopefully for the FDA, so we can get more drugs faster and save lives, which AI, you know, I think the coolest thing about AI is it's going to cure a lot of diseases and

• 34:36Craig S. Smith?

  Yeah.

• 34:36Speaker 01

  create save a lot of lives. And

• 34:42Speaker 01

  in our world of digital marketing, you know, since Tealium's inception, I would say

• 34:50Speaker 01

  we're not replacing paper, but we are replacing batch processes. And we are replacing point to point integrations, which have to be maintained over the years by people. And if you if you remember math, this is what's called an in factorial problem, right? So if you have, you know, two systems on the front end, like it used to be your call center and your internet site, and then two systems on your back end, like maybe your transaction, your transaction processing system and your data warehouse. Well, then you need four connectors, right? And or and so the if you start going to where you have 10 across

• 35:34Speaker 01

  and eight across the back, and now you have 30 across the front and 12 across the back. You know, that that simply the number of permutations, the number of point to point connection you have becomes unsustainable. But that's how corporations were growing. And then they would have teams of consultants who would build these connectors, who would then go to a different company. And then they wouldn't have the corporate knowledge. And so that's the the most, you know, sort of the biggest transition from old to new, you know, is that we've said, gosh, let's just come in and replace all that with an elegant real time data layer.

• 36:14Speaker 01

  And your life will become so much easier. Your conversions will get better. Your support costs will be lower. Your processing costs will be lower. Your storage costs will be lower. Real time is a better way. And that's it's been fun, but that's really what what we've been doing.

• 36:30Craig S. Smith?

  Yeah. Is there a domain or industrial vertical that you're

• 36:38Craig S. Smith?

  that you're most involved in?

• 36:40Speaker 01

  It's financial services, healthcare, automotive, retail, telecom, technology.

• 36:50Speaker 01

  Really both B to C and B to B businesses. You know, every I used to joke, everybody but oil field services needs a real time data layer, you know, and

• 37:03Speaker 01

  I I think that pretty much holds true. Travel and entertainment, we've got a bunch of travel customers. So really across all industries, pharma, healthcare, insurance, you name it. We've got great customers across all of them.

• 37:17Craig S. Smith?

  Yeah. And are are where does the the Tealium layer sit? Is it? Is it? Is this a SaaS platform that people are hitting by API?

• 37:28Speaker 01

  Yeah, we're cloud based, software as a service, and we do have customers who will run it. They will host the software in their domain. But largely, we run and process the data in the cloud. And most of the data that we help collect originates from outside the firewalls to begin with, right? So we're like a stopping point on the way back into the enterprise, four walls. And with all the security and auditability and trust we have, it's it's the right way to do it. Because then we can get the economies of scale processing, you know, 20 billion events a day in real time around the world on behalf of all of our customers. And

• 38:15Speaker 01

  operated that way.

• 38:17Craig S. Smith?

  Well, that's also an interesting question. The you're not your your user base is is global. It's not simply

• 38:28Speaker 01

  Half of Tealium's business comes from Europe and Asia and about half from from North America. So very global. And, you know, like I said, these big telcos and airlines and banks and, you know, entertainment companies, retailers, they're all global that we work with. So they they really like having a partner that can collect data. And there are a lot of data residency requirements around the world so that we can keep sovereign data local when when required by law.

• 39:02Craig S. Smith?

  Yeah, yeah. And you're agnostic as to what operating system or or, you know, what what the architecture is around.

• 39:13Speaker 01

  They all run. Every one of our customers has a different stat. None of them have exactly the same mix of vendors or geographies or platforms on which they run. And so we connect to all of it.

• 39:31Craig S. Smith?

  Yeah.

• 39:34Craig S. Smith?

  With Snowflake of.

• 39:38Craig S. Smith?

  When you say activate Snowflake data in real time without a shadow copy, what would actually moves? I mean, something has to leave the warehouse.

• 39:49Speaker 01

  Yeah. So you you would take a profile out of Snowflake and send it to, let's say Reddit, you know, for an audience activation or something like that. And that you might take an entire audience, or you might just take a profile.

• 40:06Speaker 01

  And depending on what the request was and what the rule is that you've defined in the platform.

• 40:13Craig S. Smith?

  Yeah. When an AI agent shops on a customer's behalf, who who is the customer in your identity? Graph that you've built? Is it the person or the agent?

• 40:30Speaker 01

  Um, yeah, it's interesting. There was just a lawsuit today where that topic came up and that the.

• 40:36Craig S. Smith?

  Oh, is that right?

• 40:37Speaker 01

  Yeah, the court ruled that the agent really was the person, the person was responsible for the agent.

• 40:46Speaker 01

  So for for Tealium, it would be a way to create a new attribute at it at the human visitor level. And then you would. Say, do they have an agent or not? And then that agent, this would be their agent, you might have an agent agentic identifier. And, you know, we're working on all this in real time with our customers. How would they like to see it? Right? Because we also could give the agent their own identifier. And you can set rules up for how all that happens in the platform.

• 41:15Craig S. Smith?

  Yeah.

• 41:18Craig S. Smith?

  Yeah, but give give the agent that that's something that would happen at the. Agentic, the the. Vendors. Side. It's not something a shopper is going to set up, right?

• 41:33Speaker 01

  Correct. Now, the the vendor would decide, you know, there's a concept of householding is is an example. And, you know, or in B two B businesses of associating. A person with a business. And so the same idea, I think, would apply where you would associate an agent with a human. Potentially as part of a household, but you would you'd probably clearly know they were an agent.

• 41:56Craig S. Smith?

  Yeah, you know, OpenAI has this thing called instant checkout that compresses. The funnel to almost nothing. If if agents are doing the browsing. What happens to the personalization industry that's built on browsing behavior?

• 42:15Speaker 01

  The. That's where you go back to optimizing your data layer for that agentic. Checkout, right? Or that agentic experience? And. Yes, if you have all right data. Surface for that agent already. Through the API and the protocol. That you'd like to support. That agent will be able to come in, transact. And leave faster than a human. And what is the point of a website other than to get conversions? And, you know, sometimes it's to educate. Typically, it's to get some type of conversion, like a loan application done, or.

• 42:58Speaker 01

  You know, there's a lot of big pharma companies, they're trying to educate people about their new medications to different audiences. And. You know, so. I think the instant checkout is just part of the future. The human traffic won't go away. You will get inbound agentic traffic that might want to use instant checkout. And if you have an optimized data layer for them. Then you'll get higher conversions out of them than if you make it difficult for them. I would not fight. The trend. Of agentic instant checkout if I was a company. Because you would then end up losing an entire generation, you know, my 20 year old, young adult kids.

• 43:43Speaker 01

  They would just wouldn't use you, right? If their agent can't do it, then they're not going to use you. They'll just go somewhere else where where their agent can do it for them. Yeah, the AI natives are. I'm gonna demand that kind of service.

• 43:59Craig S. Smith?

  Yeah, that's right. I have I have adult children too in their twenties. They're. They're very impatient. Tealium started as a tag management. Company for the browsers. Is that right? Can you describe what that is?

• 44:18Speaker 01

  Yeah, so. Yeah, for sure. When we started the company, think of around 2011 and. What had happened is ad tech had kind of really. Gone through this Cambrian explosion of different things like SSPs, DSPs, banner network, so on and so forth, personalized content, A B testing. And so companies were, you know, putting during Internet 1.0, you might have one or two. Pixels on your website that use JavaScript to read the data layer, and that's called a tag. And when we started Tealium, we wanted to solve the whole omni-channel data fragmentation problem, but we had to pick somewhere to start.

• 44:58Speaker 01

  And we decided to start on a website because we knew it well. We were former web analytics team. And. We built a platform. Our customers had gone from an average of two tags to 15 tags. And so then their. Their ad tech and martech teams are having to support all of these JavaScript tags on their website, which became a big management problem. And keeping a current problem. And so we just abstracted that to one common data layer. We manage all the tags. They could do that inside our platform. And that's how we started out on the website. And then we added, obviously, server side for mobile. We added audience capabilities. You know, over the years, we've just added zero party data collection, just added more and more to it.

• 45:44Craig S. Smith?

  Yeah, is is there? You know, people hear a lot about warehouses, a lot about orchestration. Is there a clean? Line between them or do they overlap? I mean.

• 45:59Craig S. Smith?

  Yeah.

• 46:00Speaker 01

  I would say.

• 46:04Speaker 01

  The warehouses are building more and more capability. And. You know, when we think about a warehouse. That's for running analytics and running AI models and all that fun stuff, you know, we want to do the data collection part. Stream data into that data warehouse. And then we want to help them do the activation part like they don't want to go build 1300 connectors and maintain them the way we do. And so we can help them with with the activation capabilities. And. You know, I think the orchestration layer. Is. It the most. Architecturally.

• 46:44Speaker 01

  Efficient place to put it is in between the back end and the front end, where, you know, you go back to that in factorial problem I talked about, because. There is not just one back end. There never will be. Right? And there will never be one front end. You know, and so they're always going to be, you know. 20 to 30 out the front end and, you know, five to 10 on the back end. And so. This orchestration capability should sit in the middle, in our view.

• 47:12Craig S. Smith?

  You ship M C P server in June. What? What are customers doing with it?

• 47:18Speaker 01

  Uh, that's great. You know, our customers can use Claude or Codex or. Grok, whatever, you know, to actually. Do anything in Tealium that they used to have to log in. And, you know, create rules, create attributes, create campaigns, create audiences. They can literally just talk natural language now to their agent and it can latch on to Tealium with their with the M C P via the. M C P server and do it all for them. And it's the biggest unlock of the power of our platform I've I've ever. I could have ever dreamed of because. Because we built a very powerful platform.

• 47:59Speaker 01

  You know, it took a lot of training to get people up to speed on how do I do this with Tealium? Oh, wow. Once I once they figured it out, it was great. Now they don't even have that have to go through that ramp up in that training because. The agent can just figure it out and she's M C P to latch on and make things happen.

• 48:18Craig S. Smith?

  Yeah, I mean, I asked about

• 48:22Craig S. Smith?

  use cases, but can you describe a deployment? You talked about the lift in conversion that this creates, the real time creates. Can, can you describe a deployment where this, this really clicked? Again, you don't have to name the, the customer, but and, and what did the before and after look like?

• 48:45Speaker 01

  Sure. So I mean, we have just so many of those out on our website, you know, we've got ROI use cases galore and we have customer conferences, three or four a year around the globe where our customers literally stand on stage and talk about, you know, their ROI. And, you know, I, I think what I would say, rather than giving a specific example, so there's a couple of areas where there's just obviously low hanging fruit. One is the conversion APIs that exist in ad tech. So like the, the Google Meta, LinkedIn, Reddit, Pinterest, Snapchat, Tik Tok, they have conversion APIs.

• 49:28Speaker 01

  And when our customers send data, they connect to those conversion APIs via Tealium.

• 49:35Speaker 01

  Their conversion rates and their return on ad spend go up on average 25%. And that sounds like a small number, but then you realize that how much they're spending on digital ad spend, which is typically at least 10x what they're spending on, you know, their tech stack, usually 20x. These are big dollars and when you can optimize your campaign spend by 25%, you get, you get great lift. We talked about the conversions and, you know, we see in the travel industry, you know, 30, 40% conversion improvement when we go from day old data to real time data.

• 50:14Speaker 01

  We just see it everywhere and it's, the other thing is the value of, of pulling together multiple channels of data. So one auto dealership, you know, an auto dealer has leads that come in through digital and marketing. And the average auto dealer across the US converts about 10% of those leads to a completed sale. Well, you have one dealership that was kind of the lead, thought leader that embraced Tealium early, probably three years ago, and they optimized their data, cleaned up their data sources, created this clean data layer and their conversion rate went to 30%.

• 50:58Speaker 01

  So they tripled from 10% to 30%. And now the automotive industry is a zero sum in that, let's say in that county, only so many cars are going to sell. So what that means is this forward thinking, digitally savvy dealership is taking share from the other dealers in their community.

• 51:15Craig S. Smith?

  Yeah.

• 51:16Speaker 01

  Not. And 10 to 30, just think about that. This is a considered purchase, you know, 30,000 on average, 40,000, you know, dollar purchase on average. And so that emboldened this dealership to go out and acquire other dealers because they knew they could underwrite the M and A. Uh, once they could convert, you know, um, their 10% conversion rate to 30, or let's say 20 on average that, you know, they would be able to get great value out of that acquisition.

• 51:48Craig S. Smith?

  Yeah. How, how do you guys charge? Is this, uh, you know, everyone's going to sort of metered.

• 51:56Speaker 01

  Yeah, we, we charge by volume and, you know, with our customers, we'll assess what their volumes are going to be, we'll, we'll create an annual budget and they'll commit to that budget and their like usage tiers if they go over that. But typically our customers come in within that budget. We don't like for there to be surprises.

• 52:15Speaker 01

  That allows them to budget and get the ROI they thought they were going to get.

• 52:19Craig S. Smith?

  Yeah. And on, on ROI, are you talking about revenue specifically or, or I would imagine the benefits are also in speed and engineering time and, and things beyond.

• 52:34Speaker 01

  Yeah, it's, it's all of it. It's, it's definitely efficiency and speed and agility, the ability to try new things. Once you have that neutral data layer in there, you can try new vendors, swap them in and out and use who you like. An open architecture stack. And then there is, you know, higher conversion rate is higher incremental revenue, greater ad efficiency, greater targeting efficiency is you can, you know, either plow your savings into more growth, or you could plow them to the bottom line for more earnings, either way.

• 53:06Craig S. Smith?

  Yeah. And you, you've been doing this, what did you say since 2013? Is that what you said?

• 53:12Speaker 01

  Tealium, um, we gave Tealium, we funded it, uh, in 2011. Um, in 2009, they started as, as a two person consulting company. And then we really started building the software company in 2011.

• 53:26Craig S. Smith?

  Okay. What's the biggest thing that's turned out differently than you expected? I mean, certainly, as you said, you started out in tag management and moved up to the data layer, but, but in in the, I mean, obviously a lot has changed, but is there something that, that turned out differently than you, than you expected?

• 53:53Speaker 01

  I think the, the biggest surprise was the 150 other companies that wanted to copy us. Once we showed, you know, uh, 12 years ago, what a big need there was here. And there were literally 150 other companies coming out of the woodwork saying, oh, I, I do what Tealium does. And so it's like, wow. Um, man, the Zerp era was crazy with overfunding for VCs, but that is now pretty much subsided and we're sitting here as the largest independent provider of what we do. That, you know, delivering that trusted neutral data layer to the enterprise. And so with AI coming over the horizon and the great need for

• 54:34Speaker 01

  collect, you know, clear consented data, you know, I think our, our future is bright and we'd love to talk to anybody that's interested.

• 54:42Craig S. Smith?

  Yeah. Uh, and what are you working on now? I mean, what is, you know, you, I would guess that your market is your addressable market, you, you know, you can spend the next 10 years addressing that market, but uh, where is this going? I mean, what do you see on the horizon for? I mean, are you guys going to eventually merge with the warehouse? Uh, so that you're doing the warehouse.

• 55:08Speaker 01

  We're just building AI into our platform and allowing our customers to be able to talk to their data and listen to data and do everything agentically. And that is, uh, being very well received right now. And then we're just building all the connectors for the AI ecosystem that, that our customers want, you know, like the OpenAI connectors, Google, Amazon, Bedrock, Google Vertex, all those. Uh, so that our customers can get, get active and, um, really, uh, really embrace the wave here.

• 55:39Craig S. Smith?

  Yeah. Uh, and in two years, if we talk again, I hope we do. What do you think will have changed about how enterprises handle customer data?

• 55:50Speaker 01

  It's going to be wildly more agentic traffic, um, and, uh, very much omnichannel, a lot of voice interfaces. Um, and the smart companies that embrace it will have higher converting, thriving businesses. So it's going to be fun.