Chris Strom:
Hey everyone, we're back with a new episode of the RevOps Hero Podcast. For today's episode, I have on George Samaras, and we're going to dig into the juicy and contentious topic of attribution, not just in the marketing department, but attribution across the marketing team, the sales team, partnerships team, three very different teams, and a lot of places where there can be a lot of areas where it's difficult to align or even contentiousness. So we're going to talk through all this with George here. So George, thanks for joining us on the show here. Tell us briefly about your background, how you got into this area.
George Samaras:
Thanks, Chris. Thank you for having me on. Yeah, I'll talk a little bit about my experience. I currently lead the marketing operations at Ataccama. I've been with the company for just over a year now. Prior to that, I was at Coveo for just over five years, leading marketing operations there as well. Really kind of grew my chops on the attribution side of the house. At my previous role at Coveo, that was where I was really, I was brought in more of a leadership role where we're really just trying to develop how we could capture the attribution journey and really scientifically measure and empirically measure how marketing is performing relative to pipeline influence and creating pipeline, sourcing pipeline, moving pipeline lawn and things like that.
But it's been a few years since then, so I've definitely fine-tuned my approach to it from things I've gone through experience and just doing things, getting them wrong, and eventually getting them right. So yeah, happy to share a little bit about my journey and how I look at attribution today.
Chris Strom:
Cool. So first we can start off with framing the problem and the challenge of attribution at companies in general.
George Samaras:
Yeah, so I like to use this analogy when we were initially discussing this episode. One thing that popped into my head was I kind of see attribution a little bit like, I don't want to say it's biased perspective here, but a bit of like a Formula One team. For anyone that watches Formula One, you'll notice that you'll always hear the drivers. Their biggest competitor is not someone else on another team or the other champion. It's actually their own teammate. And attribution I feel operates a lot the same way. A lot of the companies, every company I've joined to, it's almost as though the initial attribution framework that's set up, if there is one, pits people against each other. And so your biggest competitor is your own teammate, your own people within the organization itself. And so it's rarely ever an actual measurement problem. It's more of a behavioral and political one.
The math is really not the difficult part. It's how the system is set up and whether or not you're fighting for the same slice of pie or if you're going for something, going for different numbers and targets.
Chris Strom:
Yeah, a lot of times it's people look at it, they just see that they're looking at the numbers and they see it as a systems problem or a data problem, but that's just the symptom. The disease is the people problem.
George Samaras:
Yeah. Yeah, it is. I'm not going to underplay it. There can be a systems problem. A lot of organizations, if they don't have basic campaign member tracking from a marketing perspective, yeah, you've got a system problem there too. But I mean, most organizations I've either worked with directly or consulted with, the basics are set up to at least get a V1 of a proper multi-touch attribution or an attribution system for different teams. And especially now in the age of AI, we're able to use Claude Code to plug into these systems and make changes pretty quickly. It's a lot easier to get this set up now. So really the political piece and the piece that was obviously made at the higher levels of leadership is really the only major obstacle that still exists today and I find exists in a lot of organizations facing this problem.
Chris Strom:
Let's talk about some examples of the types of challenges or conflicts that can occur in attribution.
George Samaras:
Yeah, for sure. So I always use a common one. I most recently experienced this just about a year ago when I first joined Ataccama where we have biweekly pipeline generation calls where we have all the go-to-market teams getting together on a bridge for one hour. And we basically just discuss, "Hey, how is everyone's number doing? How is our pipeline progressing? Who's bringing in what pipeline? What pipeline's moving? What pipeline's stuck?" Et cetera, et cetera. And within a couple calls, I realized it was kind of like, who's the ticking time bomb today? It was one of those things where you're going in the call a little nervous and you never want to go into those pipe gen calls nervous unless you're not hitting your number. But if you're hitting a number and it's a matter of who gets credit for what, that's where it gets a little bit toxic, for lack of a better term.
So when I came in, marketing BD and partners, which are big go-to-market farmers, were the ones being measured on the exact same measurement, which was opportunity source. That's all we're looking at. What was the opportunity source? And what was the dollar value tied for that? And if the opportunity source was marketing, it went to marketing. If it was BD, it went to BD. If it was partners, it went to partners. The problem there seems pretty cut and dry and simple, was oftentimes it's not just something in one lane. It's usually, "Hey, someone requested contact," there are forms to a basic one like that. Came in from, let's say, a Google organic search, comes in, no problem. The contact us request/the MQL goes to the BDR. BDR sets up the discovery call. But right now, all of a sudden now the BDR is under opportunity source.
The marketing is getting all the credit, the BDR is getting nothing despite being the one setting up the discovery call, running the discovery call, getting the BANT information in order to progress that pipeline through to the next stage. So that's a very one-on-one example. But for us, what we noticed sometimes was like, "Hey, we saw someone come in through a contact us request, but we found out they were engaging with a partner via Slack on a Slack channel we don't have access to because it was coming in from a partner account that we're working with."
So things like that where it gets really muddy created a lot of friction. And then we just found ourselves double-clicking into opportunities on these pipe gen calls. I'm like, "Hey, we got the CRO, the CFP of finance, VP of RevOps, a bunch of people on these call, a bunch of leaders on these calls. This is a very expensive call. Is this a really good use of our time going line by line, opportunity by opportunity arguing of, hey, here's a screenshot from a partner Slack showing that the partner was actually working this before the person requested contact."
So we had a lot of just bad behavior, for lack of a better term. And it's not in a bad way, I'm not calling anyone out. It was just one of the things everyone was working in their own interests, rightfully so, because they were set up from an infrastructure perspective to only look after their own interests and not the organization as a whole. And so that was one of the things that my first few months in, I was like, "Hey, we got to fix this. Otherwise, we're going to be going into 2026 and it's going to be a mess. We're going to be fighting with each other. There's going to be a lot of infightings. There'll be a lot of bad behavior, a lot of sandbagging of opportunities and things like that. We have to come up with a better system where we're actually working towards the same goal. We're rowing in the same direction together, not in separate directions.
Chris Strom:
Yeah, especially when it's set up a zero-sum like that. Like, oh, here's an opportunity and I choose market. If I choose marketing, then sales doesn't get it. And if I choose partner, then marketing doesn't get it. And then out of the three of them, only one gets credit and the other two are going to be upset.
George Samaras:
Exactly that. That was the big challenge we had was it was almost throwing a bit of a blind spot on some of the work that other teams were working on, even if they weren't the first one to touch it. We had a system where when we set up the opportunity source, it was basically the first touch within 180 days of the opportunity being created regardless of channel. So we would notice things where sometimes someone would come in through a marketing campaign, say we met them at an event that would clearly be marketing sourced. Say the opportunity didn't go anywhere. The BDR would literally wait till the 181st day to action it, turn something in, and then from there it would become BDR source.
So we saw behavior like that and I'm like, "This can't be right." And they're set up that way. It's no one's fault, no one's strained, there's no mal intent. It's just like, "Hey, they have a number to hit. Their compensation's tied to that number. They got to do what's in their interest." So we really had to just get everyone on the same page.
Chris Strom:
So those are some examples of the challenges or conflicts that can occur. Let's go into what you typically end up doing to overcome those challenges.
George Samaras:
Yeah, great question. So towards the end of last year, we sat down at an offsite. Our CMO who's now our CRO had just joined the organization the week before we all met together in London. And we brainstormed how we can set up this new attribution system basically where we can measure each team respectively, allow overlap, but make sure there's a pipeline goal tied to them so they're still tied to the number. I was very afraid because I've worked in previous organizations where marketing, it gets disconnected from a pipeline number. And they're like, "Oh, marketing is measured on MQLs and SQLs," things like that. Levers, definitions that can be, for lack of a better term, they can be manipulated. An MQL, I can easily change that what an MQL is in HubSpot, not a problem. Anyone can.
Chris Strom:
Just change the definition of what you call an MQL.
George Samaras:
Exactly, exactly. I can just make a couple changes in a workflow or if you're using numeric scoring, a couple changes there and voila, now you have more MQLs. So we wanted to keep everyone tied to a pipeline number. So we used historic data. So what I did, one thing I really brought to Ataccama, when I joined Ataccama, there was no basic campaign tracking in place. There was some, for example, if someone registered and attended a webinar, there'd be a campaign. It was called webinar. And every webinar we ran was tied to this one webinar campaign. So we started actually creating proper campaign responses, putting UTM tracking to the campaigns. The good thing with running it with HubSpot was HubSpot keeps the data pretty much in perpetuity on the form. So I was able to do a lot of backfills of the data, so I didn't lose anything.
And so with this new system, we had campaign responses. We tied them to campaigns, we included the UTM information in these campaigns. And then from there, I was able to leverage contact roles on the opportunity. And I was able to go and see, hey, looking back, going to the past year, so let's say for 2025 in retrospect, we noticed, let's say 45% of opportunities had some sort of marketing touchpoint. We're going to set that as the baseline because 45%, and we'll take that whatever that revenue number is, and we slice that as a whole of the pie. I'm making numbers up here, but say our quarterly target is $1 billion, for example. We would say, well, we need to influence 45% of that, so $450 million.
Chris Strom:
Like marketing influence specifically?
George Samaras:
Marketing influence. Yeah. And so that would require to have a campaign touchpoint. It'd need to be a response. So it can't just be like, "Hey, person opened or clicked an email." We don't track that in Salesforce. But it would have to be something like, "Hey, person met with us at an event. Person requested contact, person attended a webinar," things like that. And so it was good because A, this gave us a system where marketing can act as an overlay for the other teams. But B, it also shows us now what specific tactics, channels, and strategies marketing is using that actually work. If I were to go and look at these opportunities and I'm looking back at what's the overlay that's occurring, what am I seeing the most of? Am I seeing a lot of webinar attendees? What channel it is, where they're coming from? What's really working for us?
We're trying to define the customer journey from a marketing perspective, find our secret sauce, and then see if we can repeat it for others. I'll say this because there's probably people who are watching this right now and are like, "Well, it's so difficult to do this or I feel like we do something like this and we can't find our secret sauce." And I'll be transparent. I always say this, I'm like, every customer journey is unique. There's patterns, but you can't apply the same playbook to everyone. Everyone has their own journey. But we do notice some things. And for us, it really helps us eliminate channels, for example, that might be costly and not effective. Content syndication's always a contentious channel. I always hear marketers double down on content syndication. The BDRs get the leads and they're like, "What's up with these leads?" That was our first finding out of the bat.
I'm just like, "Hey, this vendor in particular seems a little sketchy with the leads they're sending us." I sought to say, "Hey, content syndication doesn't work," but it allows us to get a little more thorough with which vendors are sending us data, what data is good, and the vendors that are sending us bad data, we need to rectify that with them.
Chris Strom:
So they're sending you lists of leads that they had generated for you, but then when you looked at to see if any actual opportunities in the pipeline were there, it was very, very, very low?
George Samaras:
Yeah, or none.
Chris Strom:
Or none or zero? Okay.
George Samaras:
Yeah, for some vendors. And you always bring it back to them. I always show them, and that's one thing. One nice piece of having a infrastructure like this is you have evidence. It's not just like, "Hey, the BDR said this person's not good." It's like, "Hey, here's what the data shows us. What's going on?" If you have empirical evidence to have a more meaningful conversation with the vendor. I know we're getting a little off-topic there from an attribution side, but from a marketing perspective, it really allows you to lean into the channels that work, cut off the channels that maybe are not as working or might be a little expensive, and really allow you to fine-tune your model. And it's always something that's always a work in progress. I feel like no one's ever really fully figured it out, and things are obviously changing with AEO and things like that as well.
Chris Strom:
You're mentioning some specific parts of the setup of it here. You're mentioning HubSpot forms and Salesforce campaigns. And can you tell us a little bit about how you typically set up the infrastructure for the components and the campaigns for this, and then the reporting?
George Samaras:
Yeah. So for us, I'll go very tactical here. So we have universal forms on our website, so the URL you're submitting is a hidden field. This allows us to keep our forms. We have control because we only have a handful, literally I can count on one hand public-facing forms on our website. But we'll have a single resource form, and that'll be for all of our content. And then from there, we have workflows that pick up the URL someone submitted and tie them to a Salesforce campaign. We have hidden fields that capture UTMs, which HubSpot does out of the box. And then we write those to Salesforce campaign member. We have a workflow in Salesforce that writes it to Salesforce campaign members. So the nice thing is at the campaign member level, I can not only say, "Hey, Chris came by and attended our webinar, but I saw that Chris actually clicked a paid Google Ad to attend our webinar." And I can see, "Hey, Chris then later on downloaded a white paper and he found that through Google Organic," and things like that.
So you really got really good fidelity of what someone did, when they did it, and from where they did it.
Chris Strom:
Are you looking at a lot of that off of the contact activity timeline and the HubSpot record, or is that all from the different Salesforce campaigns you're associating them to?
George Samaras:
It's the HubSpot form to the Salesforce campaign. We have this data obviously in HubSpot, but the reason I'm over-rotating on Salesforce is because Salesforce is our source of truth for a large part of the organization. If I give someone a HubSpot report that's on the partnerships team or the sales team, they'll be like, "Oh, okay, it's fine, whatever." But they want to see things in Salesforce. We operate in Salesforce, so my objective is to just make sure it's one-to-one with HubSpot.
Chris Strom:
And then when you're doing the campaigns, do you get into parent-child campaigns, like a master parent webinar campaign, and then sub-campaigns for the individual specific webinar and things like that?
George Samaras:
Yeah, we do that. We have overarching umbrella campaigns. So we'll say Q3 webinars and all our webinars that occurred in Q3. We'll tie it there. We have campaign themes, and it's really specific subject areas that we focus on. We're a data technology SaaS company, so we'll look for campaigns that focus on data quality or data governance or master data management, things like that. And we have campaigns tagged that way. But yeah, we do use parent and child campaigns quite extensively.
Chris Strom:
And then how do you approach building out the reporting from there?
George Samaras:
Great question. So actually, this is something pretty recent I've done. So we have a standardized report. For marketing, I've built a pipeline pacing tracker. I'll be transparent with something they built initially and I kind of supercharged it. So it's a Google Sheet. I plug Salesforce into the Google Sheet and it refreshes every couple of hours. And it's just basically a bunch of array formulas that put everything together so marketing can pretty much see in real time how they're pacing. I have a quad scheduled run that runs every day and basically just gives in plain English update like, "Hey, you had X amount of MQLs, this is how you're pacing towards the target. You've had Y amount of SQLs, this is how you're pacing towards the target." Things like that. Here's what we noticed in the past couple days. We noticed that a lot of our MQLs are coming from this, a lot of our opportunities are coming from that, et cetera.
So we use that for the reporting side. We do have Salesforce dashboards. A lot of our marketers use the dashboards. I'm very much now in the Claude artifact world because they look so pretty compared to the Salesforce dashboards, and you can overlay different data sources. My biggest challenge I always have with Salesforce is just limitations in terms of crossed object references. I don't have that problem when I go into Claude. But the reporting, really, we try to keep the standard of truth with that pipeline pacing tracker. We have a Tableau dashboard, and there's a couple of artifacts that only RevOps publishes that the team can use as the official source of truth.
Chris Strom:
So quite a variety of different approaches there. Some Salesforce dashboards, some Tableau dashboards, Google Spreadsheet with a lot of custom formulas in it. Now you're using Claude Artifacts as well.
George Samaras:
We're very data heavy here. Every company's going to say that, but I can say this now. I've been doing this for over 12 years. It's by far the most data. Do everything with precision here. We're very follow the data, which I love. It's a big reason why I joined the organization. But it's a challenge I think a lot of operators are having is right now everyone's now become a data scientist with Claude. So we're standardizing a few things where it's pretty much reports that are only shared to leadership or should be referenced are reports that are either built by the BI team or the RevOps team or have been signed off by other teams.
So even though everyone's kind of building their own artifacts, we have standardized ones that the teams use and they know which ones to use. And people can go and do their own thing, do their own analysis within their own Claude. But I'd be like, "Hey, if you're not fully in tune with the data to the level of a BI person or a RevOps person, just run it by us real quick. We'll double check everything, make sure nothing's missed, and then provide it back to you."
Chris Strom:
I was just talking with someone else about how with AI tools especially, if you're not giving it the context that it needs, you're not going to get the correct answers.
George Samaras:
Correct, correct. And when people are building artifacts, I know I got a pretty intimate knowledge of our database and our Salesforce instance, all the fields, what we do have, what we don't have, what we could derive, things like that. Our marketers are pretty tech-savvy here, but at times I'll look at a report and I'm like, "Something doesn't pass my sniff test." And then I take a look, I'm like, "Oh, this field was missed as a filter," and things like that. The most common one's always a new logo versus cross-sell. Marketing's really focused on new logo here. And then someone pulls a pipeline influence report and marketing's doing terrible. And I'm like, "Yeah, because you included a cross-sell," which we're not measured against right now.
Chris Strom:
That's the sort of context that, that's one little checkbox on the report builder, but it'll give you wildly inaccurate information if you miss that one checkbox.
George Samaras:
Yeah, it's crazy. It's so small and minuscule, and it's easy for anyone to gloss over. Yet we've all done it. We're all operators. How many reports have we built? And we're like, "Number doesn't line up." And then you realize, "Oh, oops," and things like that. So yeah, very common, but that's why we always have someone from our team or the BI team sign off on things, but we're in a pretty good spot. I try to keep the reports as flexible as possible. So we have a marketing metrics Tableau dashboard that we use, and there's different filters you can use to cut the data a million different ways. So for whatever use case you have for the data, we're always trying to build something out for our stakeholders. And like I said, the big challenge right now with us is we just want to make sure we're standardizing the reporting structure.
It's a big thing I've been talking to my colleagues in the industry where my whole career, Tableau or Power BI or wherever the company uses is always the source of truth. But I'm like now with Claude and people being able to integrate through CLI or MCPs, what is the source of truth? Do we have to rein it in, because everyone's kind of creating their own little source of truth. SQL queries being gatekept by people who are good with SQL queries are no longer a thing. Now anyone can pull data and be their own data scientist.
Chris Strom:
Oh, yeah. Well, they might think they're a data scientist.
George Samaras:
Yeah, and it's true. And that's where the experience comes from. But I will say this, the tools are powerful. They've been a disruptive force there. And I say in a good way from an operator's perspective, it's allowed me to pull reports, more complex reports I could ever imagine a year or two ago.
Chris Strom:
Yeah, I've had that same experience as well. One thing we were talking about attribution in general is, especially once you start going across teams, you had mentioned that you really need executive sponsorship.
George Samaras:
Yes.
Chris Strom:
So I'd love to hear why executive sponsorship is so important.
George Samaras:
Yeah, great one. So executive sponsor, I'll just say this full stop. Any project you work on, it doesn't have to be attribution, it can be anything. If your executive sponsor is not bought in or is not willing to sponsor your idea, just stop. I'd say almost give it up. And the reason I would say is I've learned the hard way from previous careers where I've made mistakes where I haven't launched these very complex projects and then C-level was not... My VP who I reported to was totally bought in, but the C-level was not. I would say though, so I would reframe this. This is going to sound like counterintuitive, but if things are not broken, don't fix them. And what do I mean by that? I don't mean like, hey, you found a problem and the exec's not aware of it, but you got to look at what the executive's need is.
My previous company, I built the attribution model that we're actually using here at Ataccama that I was able to deploy in a couple months here of joining my last company, it took me years to sell it internally. And it wasn't because no one didn't like it or no one trusted it, but it was because the existing model they were using wasn't broken. So they're like, "Well, why do I want to introduce this new variable to something that's already working?" If it's working, keep the status quo as is. For us, because we're more heavy on the data side, we're a lot closer with the data here at Ataccama. The execs are all bought in. They're following the numbers very closely. And so that's when we had that conflict. It was like the execs would realize like, "Hey, we're on these pipe gen calls. There's a lot of infighting. I recognize a problem. The CMO recognized the problem. The CRO recognizes the problem or CFO recognized the problem. Let's fix it."
And right there you got three stakeholders that if you give them a good proposal, they're bought in. And that was the big thing I did was before I lifted a finger in terms of building anything out, I did the analysis, I gave my proposal and I'm like, "What do you think?" And they loved it and we went through with it. Good thing is we launched this January 1st, 2026. We're about to wrap up the second quarter and it's going strong. Lot reduced infighting. I feel like we're finally working and rowing in the same direction like a unified team.
Chris Strom:
Oh, that's fantastic to hear.
George Samaras:
Yeah, I was relieved because at my previous org, like I said, I was really... Oversharing a little bit here, but it was something I really was passionate about and never got to really... I built the system, but never really got executive buy-in. And so it kind of made me question, is this the right thing? Even though I was talking to colleagues in the space, they were doing similar things and a lot of the thought leaders in our space were doing the similar thing. But I realized after joining here, I'm like, okay, this was a thing. It worked nicely. And obviously you got to fine-tune it to the org you're at. But yeah, so I'll reiterate, executive buy-in is key. And I'm not saying you need executive buy-in for every little project, but you don't need executive buy-in to build a campaign or something like that. But for big projects like this, especially projects that span and affect multiple teams, and more importantly, affect people's compensation, definitely need executive buy-in.
Chris Strom:
Yeah, I agree. Well, another thing that we had talked about a little bit before this was when planning out an attribution project like this, it can be very easy to go into a rabbit hole of complexity. And you had talked about how it's really important to have a system that's granular enough to get what you need without being overly complex. So can you tell us what is that right combination?
George Samaras:
And this is in the frame of attribution, right?
Chris Strom:
Yeah.
George Samaras:
I would say so here at Ataccama, on the marketing side, we look at campaign influence. So we rely on the contact role and campaign association. Our campaign association's pretty much at 100%. It's very reliable. Our contact roles, I think every RevOps person has this challenge with contact roles. We're getting better at it.
Chris Strom:
Whether they're accurate or not, or even up-to-date?
George Samaras:
Yeah, the sellers you can put anyone on.
Chris Strom:
Oh yeah.
George Samaras:
We have those challenges too. Hopefully no one watches this and pigeony flack.
Chris Strom:
Every team has that.
George Samaras:
Yeah, everyone has it. It's a known thing. I'm not calling anyone out. It's one of those things where every org I worked at has had this. For over 12 years, I've seen every company I've worked at. And we have different tools now, and especially with Claude now, we have better ways to automate some of this through Salesforce. We're finding different ways to expand the contact role through automation. So we do have some methods to get a better contact role, but we use the marketing overlay there. On the BDR side, we measure the BDRs in two ways. We look at how many discovery calls they actually have, which is very simple. We have a discovery call date and whether or not it was completed, it's a checkbox. And then we look at how much of that discovery call makes it to pipe.
So for us at our organization, a discovery call doesn't mean it's in pipeline. If we create an opportunity, it's almost like a pre-opportunity, but it's basically a placeholder where they have a discovery call. The objective of the discovery call is to capture BANT. And if the BANT is sufficient enough, we progress it to pipeline. So that's the objective. So the BDR's job, if they want to get comped and get their max comp, their job is to have lots of discovery calls and have good ones that get BANT, then move to pipeline, which is I think the best way to incentivize them to get good quality discovery calls. And on the partner side, we have them overlaying through partner influence. So it's more of a manual process where they'll let us know if a partner source a deal. We have a whole internal process where partners can refer projects to us and we tag accounts and opportunities accordingly.
But the nice thing is what I just explained is nothing complex, but it all overlays. So we're all rowing in the same motion. So it's not uncommon to see marketing bring someone in at an event, the BDR follow up and set up that discovery call, and then a partner go and refer that same opportunity because they're working with one of our partners. And so right there now, a year ago, that would've been World War III on the pipeline call, is now becoming something where it's like, "Hey, we're all getting credit and we're all rowing in the same direction. And in fact, we think this is going to move quicker because all three of us are hitting it."
Chris Strom:
And probably especially one team getting credit doesn't mean the other team does not get credit.
George Samaras:
Exactly. Exactly. We still make sure, we're making sure that we have good quality going on there. I'm constantly auditing the marketing touch points to make sure they're good marketing touch points. Same with the BDRs. I'm always making sure I have, as part of our biweekly pipe chain call, I'm also looking at the conversion rate to opportunity. So I'm like, for every call you have, how many of those calls are making it to build value? So I want to make sure you're not just getting your comp for calls and if nothing's entering pipe. We want to make sure you're having calls with the right people and they're meaningful calls.
Chris Strom:
Yeah. And then one of the last questions we'll talk about here is a really common one in the marketing ops world. And that is, can I or should I just buy a tool for attribution and that'll take care of it?
George Samaras:
Oof, that's a good one. This one is one where I don't have a good answer. I'll tell you why though. So should I buy a tool? If you asked me this maybe five years ago, I'd say no. I'm not going to name the vendor, but we got burnt pretty bad from an attribution vendor at my last company. So I did not have a positive experience. I did not believe in attribution tools after that, but that was largely because it was not a good tool. So that being said now, there are some vendors in the space. There's vendors like HockeyStack's the first one that comes to mind. DreamData, those are the two big attribution vendors I can think of. Vasco does something like that as well. They're a Canadian company, and they have some really good products. I personally have, I mean, I've demoed each one of them. I've never actually used them as a customer, so they do have some good products.
I know I have colleagues in the space who have used their products and speak very highly of them. So I'll say that. But it really depends on the complexity, maturity of your work, if you have budget and things like that. Ultimately say this, things will change. With AI, it's not as difficult to map out the attribution journey like it was prior to having Quad plug into your systems. But that being said though, these vendors are smart. They are rolling with the punches. I'm pretty sure it's HockeyStack has a built-in AI where not only is it showing you all the touch points, but you can actually have a conversation with them. They have a built in a conversational AI in their product where you can ask it about things, have them make recommendations, be proactive with you. A lot of vendors are doing that.
Even 6sense, I know they're not an attribution vendor, they're more of an ABM vendor, but they have RevvyAI, which I think is, I don't know if it's exited OpenBeta yet, but we've had it for a couple months now in OpenBeta and same thing, you can start asking it for recommendations and it gives it to you. So the good thing is even though AI can be disruptive, these companies are moving along with AI. But going back to your question, if you want to buy it, it's really specific to the org. It's specific to your budget. It's specific to you. Do you have a RevOps team in place? Do you not? Things like that. I can't give you a yes or no answer on that, I'm being honest.
Chris Strom:
Yeah, I was looking at some of our show notes here, and one of the things you had written was that tools don't resolve the disagreements, they encode them.
George Samaras:
Yeah. There's some good tools that will give insights. I will say that. But once again, it's up to you. If you guys aren't aligned, you don't have that executive sponsorship, you can go buy a tool and it might end up just collecting dust. So we got to be mindful of that as well. Like I said, these vendors are good vendors. Depending on the org you're working at, if I was in an operator's shoes and I just joined a new organization, I'd probably try to build something in-house, hit a wall, and then go to these vendors.
But once again, it really depends on the complexity, the executive sponsorship, how bad the issue is, et cetera. But I'm always a big fan of try to build yourself before you go buy. But a lot of times when you go buy, you have that tool backing a lot of the data you're sharing. You get more executive sponsorship for it. And they're very flexible tools now. They've been rolling with the punches, with powering their products, with LLMs to get real-time insights.
Chris Strom:
All right, that was most of the questions I had here. Was there anything you wanted to make sure we get to while we're talking here as well?
George Samaras:
No, I'd say one thing to be mindful of is make sure you approach attribution so it's not zero sum. You want to use obviously multiple parallel metrics. That's the key thing I'd say is the teams should be measured in parallel, not against each other. If you have teams fighting for the same number, regardless of what team it is, there will be conflict. There's no way around that. Full stop. Go back to that Formula One analogy I had at the beginning of this episode, but you don't want your biggest enemy to be your own teammate. You know what I mean? And that's where I feel like a lot of companies get it wrong is they have a lot of infighting and especially in today's market where selling is harder than ever, marketing is harder than ever, you really need to be able to be on the same page.
Infighting just adds a setback and a layer of complexity that organizations just don't need today. That's really not helpful.
Chris Strom:
Well, cool. This has been a fantastic conversation here on a very meaty and as a topic that everyone wants to do, but is very contentious and very difficult to do. So this has been a great conversation to go into the complexities of it, but also some ideas on how to manage it and how to align as a whole team around it.
George Samaras:
Thank you, Chris. I appreciate it. And I really appreciate you having me on. I'm happy to chat more about attribution anytime. People always reach out to me directly if they have any questions and always happy to do another episode on this topic.
Chris Strom:
All right, thanks again, George.
George Samaras:
Thank you, Chris.
