Scott Desgrosseilliers on AI Rewriting Attribution: Are Marketers Ready? (#021)

AI is changing how customers discover brands - and making marketing attribution far more complex.

In this episode of The Super CMO Show, Swami speaks with Scott Desgrosseilliers, Founder and CEO of @wickedreports about the rise of the AI dark funnel, the shift from SEO to GEO, and why marketers need to make their websites AI-ready.

They explore how brands can earn visibility in AI-led conversations, use structured content and proprietary expertise, rethink first-touch attribution, and make better budget decisions when clicks no longer tell the full story.

⭐ 5 Key Takeaways

1. AI is creating a new “dark funnel.”More customer research is happening inside AI chats, making early discovery and first-touch attribution harder to see and measure.

2. SEO is evolving into GEO.Brands need to make their websites AI-ready with clear structure, specific intent, FAQs, how-to content, and original research that AI systems can understand and reference.

3. Proprietary expertise is the new visibility advantage.Generic content will not be enough. Brands that translate their distinctive knowledge, data, and point of view into AI-friendly formats can earn more meaningful recommendations.

4. Marketers must look beyond platform-reported ROAS.Google, Meta, email, and SMS platforms can all claim credit for the same conversion. Independent, deterministic attribution helps reveal what actually drove new-customer growth.

5. Brand and first-party data are becoming even more valuable.As AI puts more distance between brands and the customer click, building a trusted brand, capturing owned audiences, and continuously testing new signals will be critical to growth.

⏱️ Timestamps

00:00 Introduction
01:56 AI Will Approximate or Guess Things
04:11 Your Search Traffic Is Going Down
08:59 AI Will Understand the Intent of the Page
26:10 It’s All About the Profitable Outcome
35:44 All the Ad Platforms Are Grading Their Own Homework
39:50 The Best Thing I’ve Seen Isn’t Accurate Enough to Count On
45:13 Keep Modifying Your Tags and Your Content
47:10 The Importance of Building a Brand4
9:01 ChatGPT Already Has a Conversion API
50:09 From Reports to AI-Powered Marketing Decisions

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Transcript

SPEAKER_03 0:03

We can go way back in time, if need be, to say, hey, what started this journey for this customer? Because the hardest click to earn is the first one. And so we're always trying to be like, hey, what got them first interested in your brand? And we find enough of those reverse-engineered journeys, that's where you want to spend most of your budget. Because what you'll find is once all the retargeting and all those other things, that's valuable, but you need to spend more than half of your budget on trying to find new people to first become aware. That first click or two. And usually before the click, there's viewing and there's AI chatter happening before. And so we're trying to always figure out. So our strategic edge is one, you don't overspend on bottom of the funnel somewhere, but two, where do you spend your top of the funnel dollars that lead to your overall business goal, which is usually new customers? You want new people. And so we measure new versus repeat, whereas the platforms blend it all in together because it looks way better when half of the conversions they claim are probably repeat buyers that are already buying off email. Well then, like Meta or Google says, hey, look, I sold another thing for you, and they did. It was your email that did it.

SPEAKER_01 1:16

So everyone, welcome to another edition of the Super CMO ContraMinds Podcast. In this episode, I'm talking again with Scott Desgrosilius, CEO and founder of Wicket Reports, a leading attribution platform based out of the US. The last time I spoke to Scott, we really had a lot of fun talking about attribution, the challenges marketers face with big tech platforms in terms of attribution and how to optimize their marketing spends. Since the last time we spoke, AI has disrupted attribution algorithms as dark funnel AI and visual AI referral signals are increasingly difficult to track and measure. Scott spoke to me about the new platform that they are releasing and publishing as a part of the AI-led transformation that Bitcoin puts is making and he really then broke down his experience of how attribution is changing with AI. He specifically spoke to me about why websites must be AI ready and how they must be attacked for research-driven conversations. He also mentioned the fact that increasingly with AI, brands will become more and more important as you are three or four steps away from a click in the AI world. Therefore, he said marketers must be conversant with using attribution as not just reports that they look at, but having a conversation with AI platforms. So as a marketer, he mentioned that it is important to ask the right questions because the answers will be embedded in attribution platforms. So if you are a marketer, asking the right questions to manage your spend and understanding of how to build your attribution will become increasingly important. So you need to know the context before you ask your question, and that is going to be your biggest competitive differentiator and the expertise that you need to build. Let's go in and dive into my conversation with Scott Desgrosilius. Scott, I wanted to uh you know kick off this conversation with uh the impact of AI, right? Uh and that has been absolutely uh you know earth-shattering in the way uh attribution is going to change, right? Because uh the AI dark funnel as we call it, okay, yeah, is really, really uh you know getting up to speed. And uh uh literally the AI referral signals uh are increasingly difficult to capture, right? Because the conversation happens pretty much inside the uh you know the AI uh chats, and therefore typically your ability to do attribution is becoming far more difficult. So can you talk to me about what's changing since the advent of AI in the attribution uh you know market?

SPEAKER_03 5:15

Sure. There's a couple phases to that. Um there's tracking, did AI refer? And then there's tracking, did those referrals, you know, first are you getting traffic from AI? Then there's is that traffic amounting to anything? And now there's AI advertising. I've been experimenting with uh open AI chat GPT ads. I can talk about those. And then the the biggest one that we have been grappling with is that everyone's bolting AI on top of their data, either chatting, uploading a CSV, using an MCP server, or chatting within. But no one's really asking the question, at least I've seen, is that is the data you're pointing your A at AI at true? Because AI will take the data and then use what's called generative AI, which is amazing, it's awesome, but it's probabilistic, which without getting too nerdy, it means that it'll approximate or guess things or fill the gaps in. And when it's writing something for you, then it does a fantastic job. You're like, oh, that's great. But with data analysis, it's quite risky because you need something that's what's called deterministic, which has rules and has if-then-else and has don't do this, if that. And you need those rules, which is based on a lot of you know expertise and you know, measurements of unique uh fields, just like anyone, any unique niche. And without that expertise, you get steered the wrong way or you miss a lot of opportunity. So I've been grappling with all of those. So which one do you want to dive into first? I want to I'd like to talk about all of them with you though. Yeah.

SPEAKER_01 6:59

So uh first, talk to me about uh how is AI uh changing this whole uh you know method and the algorithm of attribution. Maybe you can talk about that first because uh many of our uh marketers who are listening to this conversation, I'm sure are grappling with uh you know how do you really build attribution uh given how AI is changing search, right? So, therefore, that's something that I would want you to talk about, and then we will deep dive into many of the points that you just mentioned.

SPEAKER_03 7:33

Okay. So, yeah, what you're gonna find uh even with any attribution tool, you should find is that your search traffic is going down. Uh because AI is taking, you know, Google has been the foundation of a lot of people's businesses, and now most of the real estate is a it starts as a chat and now it's changing to where you can chat back and forth with it. So those if you're not on the first page, it's gonna be a very desperate searcher, which you know, if you do get those clicks, they're probably quite valuable because someone's willing to sift through, but everyone's getting more impatient and used to a chat result that they're not really gonna do that research unless it's a real pain point. I found it with a number of things recently where I had very niche things I needed to, like I had a wait dumbbell set of my sons that wasn't working right, and the AI kept giving me the wrong answer for the wrong product, and finally I had to scroll through. But it was only because I had exhausted the easy button. And so that's happening uh everywhere. And so your attribution tool, anything that's accurate, should show less traffic coming from search. That's a pretty much gonna happen across the board, unfortunately. Um, but then how to change that is uh, you know, there's a number of there's a couple different ways of talking about it, but it's that you need to get more content that AI likes. So that starts with marking up your website AI friendly. And then, you know, you can talk to AI to get all the specifics. So I won't go into all of them, but you can there's specific ways that AI likes to read your site, and then they it needs unique information from you that it's not generic resourced from elsewhere. So we're gonna start publishing unique research that I talk about. We're gonna start posting our unique research in an AI marked up format consistently. Then there's also you can, well, this isn't for everyone, but if you have an MCP server, which is a way of uh connecting your system to AI, you can give it um instructions that help the AI learn more about your product or offering. And this isn't just for data. I saw someone that did uh a really good job of it for hiking trails.

SPEAKER_01 9:50

Okay.

SPEAKER_03 9:50

And they created an info source where it just pulled in some of its hiking trail data. So if you said, hey, I want to go on a hike and I have a nine-year-old child, it would then tell you which hikes in your area were best, which was a really unique way to do it. But also then AI starts referencing your product more, then that spreads through its brain, basically, and then it becomes more well known. So there's some unique things that are very early adopter type things that can get you a big leg up, and I think that's one not a lot of people have done because you think MCP server and it sounds like, oh, I have a big complicated software. I mean, we have one coming. But it could be for any business niche where you could post and just post some basic stuff up there that's going to help people chat with your expertise better. And then you can so that's one that I would highly recommend people start looking into because it doesn't the the technical hurdles aren't great. I've been deep into AI and it's not insurmountable to create these things. You just need to have unique knowledge translated in a way AI likes, and so that's where the work is. But it's uh it's a it's a one two-month project, not a year-long one.

SPEAKER_01 11:09

So uh how do I uh convert my website into uh AI-friendly research content? Because uh sometimes what I really read uh uh from whatever I've kind of uh learned is uh uh you know it's almost like you will start giving it a direct attribution when actually uh you know AI has actually influenced your visit to the website and things like that. So therefore, your ability to kind of at build attribution which is influenced versus direct itself is actually changing given that you are doing uh most of the stuff through AA search, right?

SPEAKER_03 11:50

The first thing you should do, and anyone on this can do this very fast with AI, AI will help you help yourself. So uh the tagging is not elaborate, it it's basically uh so tagging for those that I don't know what normally a CMO level will understand this, but HTML is a way of tagging so that your browser understands what the display. And then behind the scenes, there's tags that don't display that used to be called meta tags, which would tell search engines about it. Very similar, there's certain tagging so that AI will understand the intent of the page, what it's about. To take it to the next level though, AI likes uh it it's a computer type brain, so it likes like uh FAQs and how-to guides. So you'll want those on the page, maybe at the bottom, or if it doesn't fit the page, you can put them in just it's not going to show on your maybe on your page because you like the layout, but behind the scenes you have a how-to or explanation for AI in the page. And you can do this by uploading your page to AI and saying, hey, I need to be better more discoverable on AI. Here's my website, here's my page. The intent of the page is this for this. So you want to be specific, not like it's about marketing is a great way to have no one reference it. Like we ours would be like for a particular page, this is about marketing attribution for people using Shopify and spending at least $20,000 a month and struggling because Google Analytics 4 doesn't give them what they need. So the longer the prompt that's more informative, the better, and that's generally true with AI in general, the more detailed it will give you exactly what to copy and paste into your website editor. And it'll be just this tagging where you'll go to like the code version of your website and you'll paste it in at the top or at the bottom. Or if you already have a script area that might, like with like HubSpot for our website, there's a little area where we put the meta tags for a search. Well, we'll add them for the um AI as well. And then you just you pay you paste it in whatever the tags are that it gives, or you have to might have to create some content and put in there. You paste it in, you hit save, and then you recheck your website, and it shouldn't show anything new unless you edited the WYSIWYG, the what you see, what you get area. But behind the scenes, AI will now know this stuff. You'll then go back to your chat and say, Hey, I just updated, can you confirm what would AI now interpret the page to be about? And so you do that. So that's the mechanics per page, but at a higher level strategy, uh, real quickly, you would want to say what say I need to get more visible to AI, and then you would say who who you are and what you what target market you have. Uh so for us, you know, marketing attribution for e-commerce brands, five to fifty million in revenue, they're spending at least 20 grand a month. I want to be more visible for them. And then it will spit out all the questions that they're asking AI, which is valuable because AI will tell you, here's what people are asking, which then is the type of content you should be creating. So that's a big that helps you anyway with your strategy. But then, based on those questions, it looks at your website and will surface probably some areas you didn't think that you needed, or other pages how you might need to repurpose, or some that you just want to text. Be some laundry list of action items, and you just go off and then it's just work. You got the you get the, you know, make someone. But it's not technically difficult work, is what I want to explain. It's just um Perfect. It's more you gotta have the expertise in your niche, which you should have you don't have a business. Hopefully. Perfect.

SPEAKER_01 15:32

So therefore, uh the first thing uh in the attribution uh in the post-AI era is about making your website AI ready, right? That's the first step that you're talking about. Uh, how is this connected with your uh MCP server? And can you just explain uh you know, with an example? On if I were a brand, uh, you know, say e-commerce brand, uh, looking at say beauty and cosmetics, uh, how should I be looking at uh you know using what you just said, which is an MCP server? How do I connect my content? And just if you can explain it uh with some analogy and uh you know, example, that would actually really excite the listeners.

SPEAKER_03 16:16

Yeah, actually, that beauty and health, it's a great example. So everyone's chatting with AI now, getting excited. Everyone likes new shiny stuff. So an MCP server, it technically sounds daunting, but it's not. What it means is I'm gonna install something in my AI for me that's gonna connect with my user uh credentials to some system and then pull out either the data that I have in that system or the this is where it gets interesting, or the unique skills or knowledge of that brand. And that's where I want to take it for the beauty and the and the makeup. So beauty and makeup, let's contrast it with what we're doing, because ours is more a logical step. So we have proprietary data and we have proprietary ways of analyzing things that we want, we want our point of view in the AI with our data that's different than other data sources they're going to reference. So there's a way we need to instruct the AI. Hey, this is why we're different. Here's how to use our data, how to compare. We have to give it instructions because then the AI takes the data in, uses our instructions to help get the user to the outcome they're trying to get to, whatever question they're asking. Now, with a beauty, uh, let's just say you're trying to make your, I don't know, your eyelashes look thicker. I have a couple daughters. So I'm trying to get my eyelashes look thicker for the prom or whatever. So, what a beauty brand can do is have an MCP server. It has to be very easy to install. But basically, they have a unique way they'll be able to capture leads this way. They can say, hey, use our, but you market it, use our AI tool to help look better for the prompt or whatever. And so people, you're also gonna go, oh great, I want to do that. So they click a few buttons and then they're in with their chat GPT on their phone or Claude, and probably ChatGPT, although Claude's more for the engineer types. And then when they've connected it, it means that whatever you've put into that MCP server, which we'll get into in a second, is now the AI is going to use whenever there are beauty questions asked. So when they say, and then you're going to, and then so behind the scenes, the beauty brand is going to be it's basically it's text files, and you're typing up your expertise. Like what makes lashes more thick is you know something to do with the brush that they use. I don't even know the terms. The brush that they use on their eyes, and the you know, all the gobbledygoop marketing that goes into your lashes are thicker. Well, they put all that knowledge in there called a skill. And so then they tell the AI, hey, when people are looking to make their eyebrows thicker or eyelashes, use our eyelash thickener skill. And it's a list of their expertise. And then separately they'll have one that says, Here are the products we recommend if they're trying to do that, which is of course what they really want. But you got to lead with advice first. So then you're in there chatting away, you get a helpful tip, and then naturally you want products. You know, we constantly have Sephora come into the house, it's like mind-blowing how much money we spend on this. And so then it's going to naturally start recommending you, and then it will learn locally on that person, but it can spread then if it's successful. And so it's a real cutting-edge thing where you can get your expertise and point of view in there. And uh, if you do it right and it's not all sales pitchy, then it can spread. And furthermore, then you know how I mean how my daughters and all her friends talk all the time. Obviously, they're like one hive connected mind themselves. That spreads, they're gonna say, hey, look, I've got this cool AI tool that helped me with my makeup or whatever, and then other people will go download it, and you've got a lead magnet that's very unique, and then you always have your uh you're getting your best chance in front of your customers of so uh I'm trying to uh you know get this right.

SPEAKER_01 20:13

So this AI tool sits in your website, or does it sit uh you know, uh independently in a uh you know, chat GPT or in a uh cloud uh uh chat? Where does this sit? And therefore, if I wear say Body Shop, okay, or if I wear Sephora, uh, you know, are you talking about the AI tool sitting in my website, or are you really talking about this AI tool uh being there uh in my uh uh you know, because I have cloud, I have chat GPT and I'm chatting with it. So where is my brand really coming in into in the conversation and how is it connecting with the expertise skill-based MCP server?

SPEAKER_03 21:00

So you have you or you hire someone that creates the MCP server, which is it just lines of code. It doesn't actually have to sit anywhere as a server, it's just code in the form of different text files that know how to talk to each other. And then it's in a format that people can install it into their AI. No different than when you install a browser add-on. Shoppers install like Chrome extensions for coupons. Very common thing to do. Commonplace now, hundreds of millions of people use them. When it first started, it was kind of like, huh, what? I got to install some in the browser. It's gonna be very commonplace soon. So this is like cutting edge to do this. But it's installing something in the AI so that your brand's instructions are in the AI. And so it's a very new space. So people can't uh you can't just go in and say, hey, Claude, always make people buy my eyelash stuff. Like it won't do that. This supposedly safeguards. But you can put your expertise of makeup or beauty in there and then recommend your stuff as an adjunct thing. What I like about it is that your point of view can get in there. Your actual expertise, it's not just uh you know generic stuff. Um, and then because if people are responding well to it, then Claude will continue to use it more.

SPEAKER_00 22:25

ContraMinds is a podcast dedicated to decoding people, minds, strategy, and culture. We interview and learn from high performers so that you can apply these lessons on your journey to becoming the knowledge worker athlete you are meant to be. The Contraminds Podcast is available on all leading podcast players, and if you are interested in revisiting past episodes or taking a look at our show notes from this episode, please visit us at www.contraminds.com. And now back to the show.

SPEAKER_01 22:58

How are you transitioning wicked reports as a platform, right? Uh, if you can break it down into three or four steps, how you are changing it, that'll be very uh valuable in terms of how you are transforming it, and therefore what outcome and impact will it have on brands.

SPEAKER_03 23:16

Well, that sentence is is where we're focused. Like now we have all this data, we're not building more reports. It's all about what's the profitable outcome from all this analysis. Like, I have playbooks upon playbooks of doing this for 11, 12 years, step-by-step checklists, in-app walkthroughs, all these things. And it still involved people had to think. Attribution has a lot of complexity. It'd be like flying a plane. You have all these different gauges, and certain gauges you only need because it's nose diving to the ground, or certain ones you need because you're crossing the water, you're in a fog. Other times, like you can see the airport and you just are gonna guide it in and you don't need a lot of guidance. Attribution in the same way. There's a lot of complexity in it, and what I'm most excited about is AI is allowing us to realize all the potential in the data we've had. So we now have uh what we have coming, it's about three to five weeks away, depending on how the testing goes, is that the outcomes are on a literally served on a platter, like a buffet at a restaurant. You pick, like, oh, I want meat today, and then we have all the meat entrees. This could be the customer LTV, or you're focused on new customer acquisition, and we have a menu list of all the outcomes we can give you. And you click on it, and then it pops up with the answer, and then you can chat with the answer to get further insight if you want, or you've already got the answer. You don't even need to go, you can go look at reports. I love to look at them, but you don't actually have to ever look at a report again only because you care to validate what we're telling you. And what came this came about, this was always my goal with Wicked Reports, is to realize the potential that we have in the data so that you always know what your next best customer is trying to tell you. Because they're out there, they're looking, you hopefully have the answers for them. How do you get them? How do you get to them? And so all these different playbooks are revealed, and it's because we we didn't know this at the time, but we built a very deterministic AI which was very rule-based. I remember my product manager was very stressed. He's like, There's not enough AI. It's still like what we know. And I was like, Yeah, but no one's not enough people are doing what we know already. Let's just get that in their hands. And now what we have is a hybrid where we start deterministic, which means we start from our expertise. So let's give an example. I want to improve my new customer acquisition. Where should I spend my budget? That means a lot of things in attribution. You gotta pick the right model, you gotta pick the right time frame, you've got to look at the right segment of traffic, and then you gotta compare it against how you normally do versus what you actually did versus what you're forecasted to do. That's all these different steps that we all have, and we get all excited, we demo them, the prospect, oh my god, this is gonna be amazing. Then they get in there and they're busy. I don't have time to do it, maybe. And now all of that power is harnessed, and we just start with giving them the answer. Go put your spend here. Why? And then we can say, well, and then we can unleash all the reasons why the data supports it, but it's data because it's deterministic, it's actual facts of attribution, backed with us doing this for 12 years, backed with what's most important, which is the foundation of the data has to be in a way that accurately attributes new customers correctly. So if you have the you need the right foundation, otherwise the the first you need the right data foundation, which we have, then you need to get to the answer, and then you need to back it up. And so we have all that now on a platter where each uh each click is a prompt to our MCP server, a prompt that's like 600 lines long, but it's hidden with all this expertise, all these agents below, these little mini agents that are experts in their little fields of expertise, and they all inject in if they need to. We have this orchestration agent that looks and says, okay, you're trying to answer this. I need these particular global skills, and I need to call these two workers, and they're going to work together with these skills to give you the answer, which is all based on our 11 years of work, 12 years actually. And then if you want to chat back and forth, it becomes generative, where now we have a correct foundation of the data and the expertise built into that chat window. So that now we know if you freestyle and start asking other things, we're comfortable that the generative AI, which is amazing, is going to have the right foundation. So it has the guardrails, it's not going to go off and start talking about taking uh taking a cruise on a boat when you're looking to stay in a hotel room, for example. So that's like I'm really like proud, but also like it's it's our end game because now we're giving and now it's just a matter of are the outdo you understand the outcomes, do you trust the data? And if not, we can dig into that with the people and customize it. But we're pretty sure we're accurate. That's what we built the business on.

SPEAKER_01 28:26

So uh let me uh dive a little uh deeper into what you are saying. Uh all this data that you have is uh the learnings that you've had on multiple categories, uh, multiple uh spend levels, multiple geographies. Uh, you know, I'm just giving an example, uh, you know, uh multiple uh uh customer segments, multiple uh price points of products, okay, and uh you had some amount of uh learnings out of that, which is anonymized, and uh that is something that you carry in, you know, if I were to call it uh you know the wicked report.ai is really something that you have, and you then start asking questions uh to say, Hey, we uh I am Wicked Reports uh attribution advisor. Now tell me where should I you know spend my money if I'm a beauty and a health brand. Okay, and you basically give out answers which will then allow you to really uh optimize your current marketing spend, then throw that data back into your Wicked Reports platform, and then further optimize it based on the results, and therefore it's a kind of a feedback loop that you're building as a part of your AI platform. Is that the way to kind of understand it?

SPEAKER_03 29:49

That's a great summary of it. You know, I said I had new talking points, so I'm a little uh boisterous with some of them. Not I'm not as concise. That's a better way to say it. I appreciate that. Yeah, because we have this thing, this this very taxing thing for people to mentally get, and when they do, they become very they really enjoy Wick reports, and until they get it, they don't. And this and it's leads take clicks take time to buy. You don't you do get last click sales, but they've generally had some upfunnel influence. And now we have that built into all the analysis, so you don't have to go off and cross-reference cohort values and past convert. We call it the lag curve, conversion lag curve. So we factor that in. So if you're looking at your new, you're trying to buy new customers, and we have all your historical conversion data, and we know it takes two weeks for them to buy, and it's been four days, and the performance doesn't look good. Well, we have your historical data that we've learned on, and yes, other brands in your niche and your AOV and your LTV. And so we can forecast out now, which is new, we for have the forecasted amount you should be at, but where we're forecasting it's gonna go based on your other new customer acquisition activities. So we can be much more confident and say, hey, we got 85% likely you don't have to panic, even though the ROAS looks bad. And so that's the type of stuff that we didn't have access to, where it was just too much cognitive load for you to do all that. Uh or people would export it out and have their own complex spreadsheets color-coded with all these other indicators to try to do that, and now we're just gonna be able to do it for them. So it's it's exciting for us. Fantastic.

SPEAKER_01 31:35

So uh given that uh you know, as a platform, now uh you have all this data, uh, and with AI coming in, uh, how do you build the referral signals for this attribution? Because one is the way you're now spending money is uh you know it's moving from SEO to GEO, which is really your website uh getting AI ready, which means that those tags are giving some referral signals to your platform. That could be one way of uh building the uh you know referral signals for your uh attribution. The second one is you're already spending money on Google and Meta and things like that, and those signals are also coming in, right? And uh, therefore, uh, you know, some could be an awareness campaign, some could be an acquisition campaign, so you're getting all that data back, and you also now are saying, you know what, uh you're using your traditional uh expertise of uh what you really say. Uh uh the analytics and the insights that these platforms give you may not give you the true picture, right? So, therefore, that's really where you differ. Can you explain that a bit to our uh listeners?

SPEAKER_03 32:50

Yeah, so that difference that's what the value is in our data and the way we measure, should be different than the platforms. Or if it if if you sign up and it matches, then you you shouldn't pay us because it's the same. You'd be paying for nothing. Uh that difference happens for a couple of reasons. One being that all the ad platforms are grading their own homework, and they're generally grading it biased, they don't want you to stop spending with them and spend on their competition, which is the other platforms, and they have a last-click bias, which is uh whatever happened last, uh, particularly with Google brand search keywords being the most uh flagrant offender. Brand keywords meaning if like for me, Wick reports, if I search if I was running ads for include the word wicked reports, those are always the best performing keywords because people are already brand aware and typing in your brand to go there, and then you run ads supposedly to protect your brand, but they already know about your brand. And so it's not generally where you should spend much of your money. Um, but there's also the the uh so first of all, we're trying to be the independent, non-biased measurement of what's happening. So if everyone's claiming for a sale, which your clavio email will claim a sale for 30 days, your attentive SMS text will claim a sale for 30 days, your Google branded search and your meta and your TikTok, all five likely with 30-day look back will all say, look, we made the sale. And what our job is to say they all touched it, potentially, potentially not, but where do we move the money so that you can be more profitable each time, or at least find out you're wasting money and stop spending it, which technically makes you more profitable. So we're already about most profitable decision, most profitable outcome for you as the person that owns the budget. That's what we're trying to do. So the first part is we're traffic copying, all five of them claiming credit, we're trying to discern the truth. The second thing is because we measure for a longer period, we have infinite look back and look forward from when events happen. We can go way back in time, if need be, to say, hey, what started this journey for this customer? Because the hardest click to earn is the first one. And so we're always trying to be like, hey, what got them first interested in your brand? And we find enough of those reverse-engineered journeys, that's where you want to spend most of your budget. Because what you'll find is once all the retargeting and all those other things, that's valuable, but you need to spend more than half of your budget on trying to find new people to first become aware, that first click or two. And usually before the click, there's viewing and there's AI chatter happening before. And so we're trying to always figure out so our strategic edge is one, you don't overspend on bottom of the funnel somewhere, but two, where do you spend your top of the funnel dollars that lead to your overall business goal, which is usually new customers? You want new people, and so we measure new versus repeat, whereas the platforms blend it all in together because it looks way better when half of the conversions they claim are probably repeat buyers that are already buying off email. Well, then like Meta or Google says, hey, look, I sold another thing for you, and they did. It was your email that did it.

SPEAKER_01 36:17

So given given that uh uh given that point that you're making on the advertising side uh uh with Google and Meta, uh, but on the AI side of the customer journey, it's pretty much dark, right, Scott? Because uh, you know, uh all my conversations are not tagged, uh all my conversations are uh you know uh I would say uh not really visible, okay? And given that uh the first touch or the uh you know uh what I call it the first touch attribution is becoming harder with the AI, right? So how is Wickard Reports now solving that problem in the new platform that you're building?

SPEAKER_03 37:00

So the undiscoverable is still dark to us at the moment. Okay, the best thing I've seen, but it's not accurate enough to count on, is if you continually ask, you have to know the questions to ask, but you can ask the AI to score you on how how many, what percentage of certain queries they are referencing you, and they'll give you that. It won't be to a user deterministic level. So we're in the progress of figuring out how we're gonna deal with that. And and I we are because I my mind got changed on one thing, which was I've always been against view-based attribution, but now I realized a way to allow it in our platform, which is to be transparent about it. Because all these people have models where you don't know what the inputs are and you're just supposed to trust the model. And I already don't like things where you don't know the logic, how you're supposed to trust it. So we created a user-controlled model where um we set the settings based on your performance, but you can see our settings and change them, and it'll immediately change the impact view has on your performance. So if we can do something like that for AI, we would add it in. It's still I don't have the trustworthy uh percentage source versus the questions to map to the visits yet. That makes sense. There's still a missing it because it's like view based, uh basically the the the AI saying, hey, we had a view impression here. Take our word for it. So we're going to treat it similar. Um it's just getting the reliable data feed we want to use. No one has one yet. I'm leaning towards ahref's version. They're very solid with everything. So we may use their source if we can, but we haven't a blind spot temporarily, unfortunately.

SPEAKER_01 38:57

Okay, yeah, not so true. So therefore, literally, uh, would you therefore say server-side uh tagging uh is going to become more important, though it's viewer-based? You're kind of looking at uh server-side tagging, which is really saying, okay, you know what, so many signals came from uh people who searched for uh you know dry skin, for example, and uh they came to me uh on my website. Uh maybe there's uh some kind of a signal that you get, and uh from there on, I think you've got to find new ways for attribution given how AI is evolving, right? So I think uh it's really not uh clear as yet, but uh I think the ones who are going to really crack this are the ones who are able to think from first principles, right? It's not going to be easy, and that's really what you're talking about, right?

SPEAKER_03 39:53

Yeah, well, it you align it to business outcomes. So, like what we did with views is that you know, if your new customer acquisition cost, blended across all your marketing, is where you want it to be and you are growing healthily, then theoretically, whatever your current KPI benchmarks are per platform are good enough. And so that the click-based accurate attribution can still be the command center directional guidance you need, even if what at a click basis it shows less profitable than you wish. Like on a like a Snapchat, which is much less clicking happens, the the return on ad spend can look low click-based. But if when you increase Snapchat spend, your new customer, your blended new customer acquisition cost stays the same and more new customers come out, then you got the outcome you need. So we can infer there. So that's what we released without that's what we have coming with that this summer release is that the ability to infer transparently against the business value. The mistake that happens right now is the ad platforms show view conversion from their limited siloed view, not taking your business into account. So it shows a sky high ROAS that you're not realizing. But if we can tie it to the bottom line, your dollars in and out, then it's worth, then it's more trustworthy, in my opinion.

SPEAKER_01 41:23

And and therefore, uh, if I'm uh getting uh traffic from say five different uh you know uh AI platforms, right? I'm you know, I get from Cloud, I get from Chat GPT, I get from uh Perplexity, then the real the real challenge that you're talking about is on my website, I need those meta tags, okay, which will actually direct me to uh you know saying that hey, you know, you get you're getting these kinds of referrals, and these referrals are actually uh getting you into your website or it's getting you into uh you know some outcome that you want, and therefore you're almost saying that this area is now opening up given the fact that uh you know this is a new area, and therefore the whole idea is uh your past knowledge becomes your coppers for your uh asking these questions, and probably you've got to do a lot of experiments and start learning with it, and that's your competitive advantage as wicked reports, right?

SPEAKER_03 42:26

Yes, because you're always just trying to beat your own benchmark. Really? I mean, we have benchmark data against other people, and it's fun to see how you compare, but whatever your your current goal is, you're trying to beat it. It's the same thing like weight loss or running speed or you know, whatever your activity is, you're trying to improve yourself. It's no different with attribution. You get your own benchmarks based on accurate measurement, because like we're measuring things correctly. So if you go into an ad platform, it's almost like you're weighing something when you should be measuring the distance. It's literally that different. The measurement philosophies in some cases, they're just completely different. So, yeah, you you iteratively improve, is how it works. And with the AI, you'll keep wanting to, if there's a question you keep wanting to answer for and you're not getting the visibility, you got to keep modifying your tags and your content, and then going and waiting and then refreshing and seeing if it if it worked or not. There's no guaranteed blueprint, which is why it's the wild west right now, which is kind of fun. Just depends. It's experimentation.

SPEAKER_01 43:36

How do you see advertising evolving uh in the uh era of AI? Because you literally had search. Search led to uh you know, bidding of keywords, keywords led to uh you know, clicks, clicks led to uh you know a whole host of way you would attribute your spends and optimize your spends. That's really how the internet era built. Your advertising model, right? What's your prediction of how will AI advertising model, how do you think it's going to pan out if you were to kind of look at it into the future?

SPEAKER_03 44:14

Yeah, I think they will get better with their paid advertising options because there's so much. I mean, you're looking at how much, I mean, Meta and Google are like, you know, hundred billion dollar profit businesses. I'm sure AI wants to get their hands on that spent. So it's very likely it's going to get better. So I would anticipate more embedded advertising is going to happen because the money's too great. So that'd be my first prediction. Second one is the importance of building a brand is going to become more important and owning your audience because the audience is so hard to capture now, and it's going to be even more obtuse or you're going to be more removed from them. You can't just pay, get a click. It's going to be more effort to get that paid click. The importance of offering enough value to capture that click, capture that email address, that those email addresses are going to be much more valuable. I mean, they've always been really valuable, but now they're like, you know, gold. You can actually cut, you know you can reach them without having to pay. So I think those are the three things that I mean building brands always been important. I think it's just huge, hugely important to build. Because that's your asset.

SPEAKER_01 45:40

So those are the two important things. And do you do you foresee uh you know first-party data uh kind of uh becoming useful in the AI platforms? Because I've collected a lot of first party data. And uh uh how do I really match my first party data with these AI platforms? Do you think uh you know there's a new way of thinking with my first party data in my AI platforms?

SPEAKER_03 46:08

Uh yeah, ChatGPT already has a conversion API.

SPEAKER_01 46:12

Okay.

SPEAKER_03 46:12

So they're already doing matching.

SPEAKER_01 46:14

Okay.

unknown 46:15

Yep.

SPEAKER_03 46:16

And then also, I mean, the new the Google checkout AI, if it takes off, like to Shopify, where you can an agent can buy. I know that's all hypey, it's not a lot of people aren't doing it now. It remains to be seen. It might, it might take off. That's you know uh a transaction that then will need some because the first party data was triggered by the AI. So you'll have seamless attribution there. Because then we can pull from Shopify or whatever your card is that the AI tagging in there it happened because an AI shopper. So that'll be cool. It'd be fun and it'd be easy to attribute that if if it takes off. We haven't worried about it yet because not a lot of people doing it.

SPEAKER_01 46:58

But fantastic. And how do you see the uh Wicked Reports 2.2 evolve uh in the AI era? So, what do you think are the two or three priorities uh that you feel marketers will find valuable for the new uh transformation that you're doing as a part of your platform?

SPEAKER_03 47:20

Yeah, so I think the biggest will be decision certainty. You'll have the decisions on a platter for you, and we'll now we're logging them, so you'll be able to log and say, Yes, I'm gonna do this, and no, I'm not. Because we can we're guaranteeing three times what you pay us now, because we're certain that we can find three times what you're paying us in decisions. So it's an outcome-based attribution pricing. So that's the biggest one. The second one is we'll have uh more control over our customers' experience because we as the data unlocks insight, we can deliver it to you on a platter. I mean, no, like hunting for the data or long emails imploring you to click here and do this and that. We'll just tell you, hey, go do this. So that's fun. And then the third thing is we'll get into uh you know TV attribution and uh creative insights now in the fall because we'll have the decision piece solved. So now we can move just where else can we help you make decisions is the third piece we'll move into.

SPEAKER_01 48:25

Fantastic. Thanks, Scott. I think uh thanks for the preview uh to the product that you'll be launching in the next three to four weeks. Uh it's interesting, I think it's almost like the Wild West, as you said. A lot of questions were uh you know answered, a lot of questions people are experimenting and figuring out, but uh you've been a first mover, and uh the fact that you've been able to experiment and build this is giving you a first mover advantage, and I'm sure uh when we meet the next time there'll be a whole host of learnings uh that you will be able to share with our audience, and I am looking forward to the third conversation soon. Thank you very much.

SPEAKER_03 49:11

Thanks, Wami. Always a pleasure. Great questions as usual. Take care.

SPEAKER_01 49:15

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