9-Figure Brand Strategies: Scaling Omnichannel Ads with Universal Attribution | #229 Philippe Roireau

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Claus Lauter: Hello, and welcome to another episode of the e commerce coffee break podcast. You probably know the famous saying of the ninth century Philadelphia retailer, John Wanamaker, who said half the money I spend on advertising is wasted. The trouble is I don't know which half. So that brings us to attribution and attribution, a very important topic for a lot of merchants out there, and they don't know much about it.

We're talking about third party tracking. UTM calls will fall away at some point. So it becomes really difficult to find out where to put your budget for your advertising. We want to dive a little bit deeper into this topic today. We want to find out how the big ones, the nine figure brands are scaling their omnichannel advertisements with universal attribution.

With me on the show today is Philip Roro. He is the SVP of go to market at Northbeam. They are a universal attribution platform for the highest performing brands in e commerce. He was previously the vice president as Georgia's and co founder of deals in an e commerce focus retailer that generated over 20 million dollars in revenue in the first 24 months.

He also worked for Google and Microsoft. So he has a very vast background when it comes to e commerce and specifically with Norse beam also when it comes to attribution, so let's welcome Philip to the show, Hey Philip, how are you today? 

Philippe Roireau: Thank you so much, Klaus, for having me. Can't wait to talk a little bit more about the attribution.

Claus Lauter: Yeah, let's dive right into it. Attribution. I think a lot of people have heard the term what it is and have a bit of an idea of what it does, but I think a lot of merchants also are in a space where they have their marketing budget for paid ads. They are on different channels and they have sort of colliding information data coming in where actually the conversion comes from.

Give you a bit of a basic overview, what attribution actually means. 

Philippe Roireau: Well, that's really like at the core of what it's all about. It's understanding which one of your marketing channels are the most impactful in the customer journey. So like what's driving the most impact throughout those conversion funnels that you're running.

And you're right. Like the merchants nowadays have a slightly more complex. Channel mix than they used to a couple of years ago. There's always new platforms that are popping up and you need to keep experimenting with those platforms in order to stay at the forefront of the pack. So it's really about understanding what's working well in your marketing mix.

You might be advertising on Facebook, on Google, on TikTok. You're sending emails, potentially even like postcards or running ads on connected TV. So all of these, if you were to actually add up. All of the sales that each of those channels are telling you within platform reporting that they are making you'd be actually making two or three times more sales than you actually is.

So that's really what it comes down to. It's about helping merchants demystifying their optimal, , channel mix and what's driving the most impact in their funnel. 

Claus Lauter: Now, there's a lot of dynamic going on when it comes to this right now in the market. Obviously, everyone has heard about the changes that Apple has made that Google is going to make when it comes to third party tracking.

Also a lot of these platforms, and you mentioned that, are trying to claim the conversion for themselves. Because obviously that gives them an indication, spend more money on me. How can you circumnavigate that and get proper data that has the right integrity to make good decisions?

Philippe Roireau: Let's start by the multiple privacy changes that are happening. So there was like multiple iOS updates since iOS 14 that impacted the ability to track online journeys. And actually iOS 14, I would say was a catalyst for mid market brands to actually understand their conversion beyond in platform reporting.

Because at that moment that really like For Facebook books specifically, it really muddled the water of how clear the platform reporting was. So from one day to the other, it was like, okay, Facebook is giving me good data or good reports on what's working. And the next it's like not working at all.

, that was the initial catalyst. It was those iOS, 14 update that basically kept like third party platform from tracking the customer's journeys directly in iPhones. So that had like a pretty significant impact. And because of that impact, there's companies like Nord beam that really found product market fit.

 And you also mentioned, there was a cookie less future, that's in front of us potentially already. Safari is making significant degradation on the power of the cookies, so they will go down to, seven days. Of, cookie life. And then after that, they will expire. So it will reduce a lot of the ability to track a user on a longer, period of time.

, and there's always new, , iOS updates that, , put new little hurdles for example, there's one, I think 16. 4 now that's being rolled out that's like hindering a little bit UTM tracking. If we're just basing ourselves on one way to track. The customer journeys, , there will be a lot of missing pieces.

So like in different platforms or different interface will have different privacy restrictions. It's really important in one of the way that we're approaching this at Nordbeam is to have multiple tracking mechanism in place that can stack on one another. So first of all, you want to be able, obviously to have, so we talked about UTMs, so you want to put UTMs everywhere and it's going to work.

Like, in most places, UTMs are going to track very accurately clicks. So some places might see a little bit of degradation, but it's minimal. So that's like one layer. The second layer could be like, yeah, we, you want to have a pixel on your site and on multiple pages on your site to track the customer journey and then tag the users and keep tracking those journeys over time.

Another way will be the cookie. So you can so Nord beam, for example, puts a first party cookie on your website and uses that to track some parts of the customer journey. And finally, also, you can ingest third party data. from advertisement. Platforms. So, for example, you can have a partnership with a company like Mountain or Tatari that are doing connected TV ads, and these connected TVs can return you when a user saw an ad, so they will actually like they have an agreement with their user and they can share with advertisers the IP address.

So a certain ad. So then you can use that data as well. That is very high fidelity to model your attribution. So you have those four mechanisms just to recap, like UTMs that tracking links, cookies. Pixel and platform integrations to track the customer journey. And then obviously a lot of those mechanisms will, duplicate the tracking, if you want, like your UTM is going to pick the same thing as the pixel and so on.

So the next step after that, it's once you have all of those different touch points that are tracked, it's about. Cleansing the data. So you want to make sure that every touch point is only tracked once and then it's about attaching it to the right user on a device graph that you're building.

So like the user might be on their connected TV, they might be on their phone, they might be finally purchasing on their laptop or their desktop. So you want to make sure that you're able to say, Hey, that user has all of those devices that belongs to them. So you get all of the tracking. you, cleanse it, you remove the duplicates, you make sure everything is tracked only once, then you attach it to the right user.

So once this process is completed, this is really the underlying foundation for multi touch attribution. Then you can actually create attribution models. All of this together, that's what makes the graphic of every interaction that you have with your customers.

And out of that, you can build attribution models in multiple ways and really get a lot of value out of that data to help you scale a little bit further. 

Claus Lauter: I think Philip, that was the best explanation I've ever heard somebody saying from A to Z, like a mini masterclass on how attribution works. And I think that should create a lot of clarity for our listeners.

Now, once you have it break broken down to the. Specific user. So you know where the traffic came from where the conversion came from, whatsoever. How can I use that then basically in the reverse engineering to optimize my marketing? 

Philippe Roireau: Right. So that's the next step. So you have all of this data and then you're able to create attribution models.

out of that data. So we, so there are multiple attribution models. You're probably logging in your Google Analytics once in a while to see what's converting. So Google a lot for last click. So, and this will be really like your bottom of funnel, right? They will favor Google in a lot of cases and so on.

So there's multiple attribution models, the single touch attribution models, first click, last click. Those are really like your baseline standard that you're used to. But then after that, there was like multiple, ways to do more complex machine learning powered attribution models. So, for example, at Lordbeam, how we're approaching this because we're really focused on e commerce, brands and helping like those mid market, DTC brands, so we're creating our own attribution models that are helping you.

Philippe Roireau: Actually like media buyers get more clarity on the performance of their ads. For example, if we're like, Hey, I want to find ways to understand the true impact of my Facebook or my Google or my TikTok at the top of funnel. So really things that drive new users. So we develop a few attribution models that are basically reducing the impact of your bottom of funnel.

So, hey, your brand searches, like your organic traffic or your email marketing which all of these things get a lot of weight in Google Analytics. And instead, we're putting a lot of weight towards touches that happened at the top of funnel. So, hey, Facebook drove this first visit, TikTok drove the discovery of this thing, or YouTube, for sure, they had views that happened on this thing.

So, we have different clicks or clicks and views. Model that really help understand how your new traffic, , or your acquisition engine is doing. So that helps the media buyers. scale or really put their dollars at the right place in their marketing spend because like a lot of brands, that we're meeting are making decisions based on Google analytics and they're really optimizing on their bottom of funnel.

They're like, oh, yeah, my email marketing is crushing it, like my organic traffic or my brand. ads on Google ads are really doing well. Obviously these are doing great but I think there's an aspect if you want to keep on growing you need to really be able to understand the How your top funnel is working and that's where we come in so we're really trying to you know assess if there was any path or touch points in those more like acquisition channels and Help media buyers Put their dollars there like you can only go so far on your, brand campaigns and Google ads.

They don't have that much depth to them. If you ever try to scale that, you'll quickly run out of steam. I think 

Claus Lauter: a lot of merchants marketing departments are still struggling with GA4 because it's so much different. I can speak for myself. I was using GA for 20 years and one of a sudden everything changes and you need to really find your way around to find the data that you were so used to find very, very quickly.

Now, at Northbeam, you say you're collecting all the data, you cleans the data, you stitch it together into accurate first party data. How do you visualize it? What kind of reporting or visualization can I imagine if I log into the platform? 

Philippe Roireau: Right. That's a great question. So the first base layer is you can actually review the customer journeys of every single order.

So I would say like, this is where it starts. And again, so you can be like, Hey, click on an order. And you can see this person saw like your first ad on TikTok, like four months ago. And then they re engaged through potentially like Facebook ads or like Google top of funnel type ads. And then they searched on Google they did a brand search and they clicked on a brand ad on Google and they clicked on an email and finally they converted.

So the baseline of the, how you can visualize that is the individual customer journeys. Then if you go one step up, it's like you have those aggregated customer path. So which customer path together are driving the most purchases. But really where people make decisions is that you have this main dashboard that lists all of your different marketing channels and all of your marketing spend and all of the revenue that you did.

And then you have, depending on the attribution model that you opt in and different attribution models will be great for different purposes or understanding the impact of different channels. But let's say you're like, Hey, I want like my seven days clicks only like tracking only the clicks.

And I want all of my revenue to be distributed across all of my channels. So there's only 1, that equals 1 from your backend. Across all of your channels. So you have all of your marketing channels that are listed together and you have like all how much you spent on each of them and the attributed revenue for each of those marketing effort.

, this is at the high level and then you through this dashboard, you can click just like you would in your ads manager, all the way from like a campaign level to the ads level, but across all of your marketing channels. So you can. Imagine this as like your master ads manager, where you have the same motion that you can go, Hey, campaign ad set ads directly from one interface, but where 1 only equals 1.

Unlike if you were to stack up like all of the different revenue that all the in platforms data was telling you like equals to multiple dollars, what you actually earned. and so you can really understand the true role as. Of every single efforts that you have in there. And also there's another thing that we shipped recently that is, a lot more colorful if you want, so we have a creative analytics tool now that is really advanced that allows you to use first party data to understand the true, the true performance of each of your creative.

So every ad. that you run at the creative level on Facebook, on TikTok, on YouTube, you can now match first party data and third party data to understand how well they're doing. So for example, let's say you have like multiple variations of a certain of videos on Facebook, then we're able to present now like all against one another, like, Hey, which video has the highest.

 Thumbstup rate, which video has the highest 3 second rate, which video has the highest click through rate, and which video has the highest... Nordbeam ROAS, right? So with this data, it's really easy to understand, hey, this hook works well. Let's do more like this hook, engagement section, like music, whatever in the middle keeps the user a little bit engaged a little bit longer.

And finally, this type of call to action. really drives my CTR. I see that this video like against the same audience has the highest CTR. it seems like really they like when either the text looks like this or like the final screen of the video has like this type of offer and so on. So then you can really start to review how different assets Are performing against one another and make decisions like creative decisions that are more, analytically driven compared to usually, like, your creatives are very much like inspired, by the moment or by your designer.

And so here we're helping now creative strategists take a new angle, and a little bit more data driven angle on how they can review creatives. I'd say those are the main two ways they, that like we're using this data to help media buyers scale their ads a little bit further.

It sounds 

Claus Lauter: like a marketeer stream and a data analyst stream. Because right now you need to log into these different platforms. , depending on how they are built the show you different data, in a different visualization. And then you need to, as a marketer, to find a way to get this all together.

And Nors Beam does exactly that in a perfect way. Now, you're working with a lot of brands, how much time does a marketeer data analyst, somebody who pays for traffic spent in the platform on a daily basis? Do you have some numbers on that? 

Philippe Roireau: Yeah. So they can get value like pretty quickly, especially if they're on Shopify.

And so when they can get time to value for the platform is really quick. They'll like get insights from it, like within the first week I think the media buyers. They will log in there on a daily basis, and this is where they review. This is their first step to review , their data.

So what we're hearing a lot now is that there's really three components that media buyers are triangulating. First of all there is this MTA data that we talked about. It's like, Hey, what's the ROAS according to Nordbeam? Then there is post purchase, survey data. So this is a little bit more like, Hey, like, how do you hear about us?

 From a post purchase standpoint. So the, you'll have like friends and family and so on. So you'll have a new layer to understand what's working in your marketing mix now. And finally it's media mix modeling. So that helps media buyers forecast like how much their ad spend will produce in the future if they're adopting an optimal channel mix.

So I think that's the last like missing piece is just like, Hey, like where should I actually optimally put my dollars, not just adjust on a day to day basis based on like the current performance of channels, but actually have a little bit more of a longer vision on performance.

And so we're using now machine learning to tell our top merchants, how much. They should like how much this would invest on each channel to have the optimal output of their marketing dollars. So it should maybe be like 50 percent on Facebook, 20 percent on Google, 20 percent on TV, 10 percent on mailers.

 And so we're using like machine learning to. Actually analyze all of their past data and then project like according to seasonality and a couple of other things how much they should spend like going forward on different time ranges. So those are really the three things together now that like the top media buyers are using on a daily basis to understand where they should put their dollars.

It's 

Claus Lauter: probably one of the most common questions that media buyers and marketers get is like, where do we put the budget? And there was never a clear answer to it, but it was a lot of guesswork. But I think there's North beam, you're getting there that you definitely can make an educated decision. Now tell me a little bit on the onboarding.

What's the process? How long does it take? what kind of platforms do you support? Right. 

Philippe Roireau: If you're on Shopify, it's a couple of clicks and then you can go and integrate. Okay. All of the, your different ads platform. If you're on Magento or BigCommerce or WooCommerce, the integration, is also available, but it's just requires like one extra backfill, but it's still like.

 Quick time to value, all things considered Shopify, like most tools Shopify is seamless the other platforms, require just a little bit more effort, but you can get there quickly. And if you're custom, like if you have a fully custom site, like we have some really big custom customers like PetMeds.

com and so on in the U. S. It might take a little bit more, like, just a little bit of dev effort to install, , to do the custom integrations. If you're a merchant spending tens of millions of dollars, potentially a month, on ads it makes a lot of sense. But it's also just a caveat.

It's not only for merchants that are spending $10 million a month on ads, we have a couple of those, but where there's also more, modest e-commerce brands, maybe that's like a, a good little like it's really good for brands. I would say like one, once they're passed, like $1.52 million in G M V.

That, and they're experimenting on one extra channel. So they have their Facebook and like their performance max campaign running on Google pretty seamlessly. And now they want to go launch maybe display again or native or tick tock or outbrain. At that moment in their journey and their marketing journey, I would say Norby makes a lot of sense.

Claus Lauter: You were reading my mind because it was exactly my question asking you who's your perfect customer. Now we will come for shortly to the end of the coffee break podcast today. Is there anything that you want to share with our listeners that we haven't covered 

Philippe Roireau: yet? If you want to try a Nordbeam for yourself, visit the nordbeam.

io and just mentioned the coffee break podcast, and we can give you. 50% off for the first, two months as well, so you can really test it for yourself. But yeah, again, if you're a merchant that experimenting on multiple channels and you really want to understand the true ROAS and the true CAC of your different marketing initiatives, I think like a tool like, Norby can be a great addition to your marketing stack.

Claus Lauter: Tell me a little bit about the pricing structure. How does that 

Philippe Roireau: work? it's a fully variable based on your traffic. So, it's like, if a month you have a lot of traffic, Black Friday, it's gonna be a little bit more expensive, but then automatically it will reduce when the new year comes.

 The price is based on page views, which is basically the server cost that Nordbeam incurs. It's 100 percent variables, and it's a linear price. So, it's 2 per 1, 000 page views. Whether you have high page views or low page views, the price is the same. So like it, it really moves with your growth.

Claus Lauter: Okay. That makes perfect sense. So where can people find out more about 

Philippe Roireau: you guys? Yeah. Just visit a Nordbeam. io and come chat with us. 

Claus Lauter: Well, I will put a link in the show notes as always. Then you just want to click away. Philip, thanks so much for giving us a really in depth overview of attribution. I it's information where people lead, listen twice to this episode because it's so good.

There's a lot of gold nuggets in there. As I said, I should reach out to you if they have any additional questions. Thanks so much for your time today. 

Philippe Roireau: Thank Klaus.