If you’re not using incrementality, your competitors are…


Trevor Testwuide is here to break down marketing attribution and incrementality measurement.


Trevor is the co-founder and CEO of Measured, the only measurement and optimization platform powered by incrementality.


An expert and pioneer in marketing attribution, Trevor believes incrementality is more effective at last touch for showing brands where to invest.


In this episode, he’ll share how brands can successfully implement incrementality—and why last touch methodology falls short.


Mentioned in this episode:



Voiceover: This is Performance Delivered, Insider Secrets for Digital Marketing Success with Steffen Horst and Dave Antil.


Steffen Horst: Welcome to the Performance Delivered Insider Secrets for Digital Marketing Success podcast, where we talk with marketing and agency executives and learn how they build successful businesses and their personal brand. I’m your host, Steffen Horst. The topic for today’s episode is marketing attribution, and incrementality measurement. 


Here to speak with me is Trevor Testwuide, who is the co-founder and CEO at Measured, the only measurement and optimization platform powered by incrementality. Trevor is a pioneer and expert in marketing attribution. He has spent his career working with advertisers at leading ecommerce brands to deploy and benefit from advanced cross-channel media measurement technologies. Trevor, welcome to the show.


Trevor Testwuide: Thank you for having me, Steffen. Great to be here.


Steffen: Trevor, before we start talking about today’s topic, tell our listeners a little bit more about yourself. How did you get started in your career and what led you to founding Measured?


Trevor: Sure, so I did my undergrad degree in engineering, and I returned to business school a few years later. Coming out of MBA, my career has largely been an entrepreneurial journey. The MBA program for me at that time in my life, it tapped into an ambition, an entrepreneurial ambition and a fire me to create and build. There was something about the early stage company creation and building that really turned me on and got me going. 


And I was compelled down that path coming out of MBA. So something about defining a vision and creating a product and going after product market fit to establish a business. I think, I feel like that is a fire that’s either in you or it’s not. It’s a DNA attribute that you’re born with. For those not on an entrepreneurial path, starting and building a company looks glamorous, it really is the opposite. 


As anyone who’s done it knows it’s a sequence of obstacles and challenges and failures, or at least what look like failures at the time, but are really just lessons and learnings along the way. But that switch to start a company was flipped in me coming out of MBA. And so I left school and I joined a sequence of early stage seed funded startups that ultimately led me to a company called Visual IQ in 2011. 


And that’s where I got introduced to and got the bug for the marketing attribution problem. Visual IQ was pioneering the multi touch attribution category with some very exciting, innovative technology. The problem statement, it held tremendous promise for the industry at that time. And this was 12 years ago. People at that time were fed up with platform reported last touch metrics, and still very much are today. 


But in that role, it’s where I grew love for the industry of marketing technology and the cross channel marketing attribution problem. That is also where I met my co-founder here at Measured, Dawn. But Dawn was my VP of product, there at Visual IQ. We spent a lot of time together out evangelizing the merits of fractional attribution and learned a lot. So then fast forward a few years to 2016 still immersed in the category. 


It became quite clear that the multi touch attribution problem which is a user level path building methodology, was facing insurmountable challenges. Sorry that the multi touch attribution, the methodology was facing insurmountable challenges. The data privacy era was here and was eventually going to prevail. User level tracking was being threatened and soon gonna go away. 


And we had a thesis that incrementality measurement informed through RCT which is randomized control trials, experimentation was going to be a must have requirement for brands going forward. So as we thought about teaming up and starting Measured, we looked at the marketplace and we saw that experimentation, media experimentation, was and still is very manual. 


It’s hard to get right. It’s labor intensive, it’s fraught with error. And we had a vision to platform enable experimentation. So end to end. To streamline and automate the experimentation process. So that’s the design and market selection. That’s deployment activation. That’s the management of the ongoing experiment, and then the reporting that leads to decisioning and optimization. 


So that entire end to end process, we had a vision for platform enabling it, and we decided to team up and start Measured in early 2017. So now over six years ago. Laser focused on incrementality measurement, right? So we have, and we’ve been built here, at Measured from the ground up in anticipation that the industry would move towards incrementality, move in our direction. 


That is happening now. The industry is now finally really making a strong move in our direction. So that, yes, that’s where we start. I can tell you more about the team. That’s how we got started.


Steffen: Now, you know, the topic about, you know, attribution, in general is something you know, I’ve been in media since 2004. And I’ve worked for a number of global agencies, where we worked with Fortune 500 clients. Now, the bigger the clients, there are solutions available. I remember back in the days in 2012, when I still was working for big agencies, there was Adometry, which was later acquired by Google. 


But these solutions are usually very expensive, you know, for your small to mid level companies, almost not affordable, basically. So your solution basically, does it allow for smaller companies to get these insights that they need in order to be more, in order to optimize their media buying better?


Trevor: So not just pricey and expensive. But I would suggest that user level path building methodology where you’re connecting all the user level events online and offline to an ID, and then building that path to conversion. It’s not a matter of is it affordable or not? It’s a matter of is it possible, is it viable? Today, that methodology is not just challenged, it is an impossible methodology to land for a variety of user level mapping reasons. 


So our methodology here, based on incrementality measurement is we have an incrementality based attribution methodology that solves for the same problem statement, that portfolio management problem statement. We’re getting our clients to the same destination, but it’s now based in incrementality measurement. The goal of incrementality is to inform contribution, the contribution of the media to your business goal. 


And then we have a methodology to apply these incrementality reads to a full portfolio of cross-channel recording and optimization for decision. So, today, the two most relevant advanced measurement methodologies are experimentation incrementality and then also media mix modeling. If you’re familiar with media mix modeling, yeah.


Steffen: Yeah, yeah. Now, let’s clarify a little bit the incrementality. So when you talk about incrementality, what do you mean by that?


Trevor: Yeah, essentially, I mean, contribution. And I mean, contribution informed through an experiment. Okay, a test and control experiment. So we have a platform that enables test and control experiments, you have an audience that is exposed to media, you have a mirror audience that is not exposed to the media. 


And the difference in the two conversion rates informs the incremental marginal contribution. So our goal is to inform, to determine the causal influence of the media. And we do this by deploying these controlled experiments on the media. Those can be informed at the channel level, a tactic campaign, ad set, ad group level.


Steffen: Yeah. It’s interesting that we have this conversation today. I recorded a podcast yesterday. And the day before too, and in those two podcasts we talked about the impact of brand advertising on performance, basically. And the challenge that companies have, or that agencies or the media buying team, whoever manages the media buying part, have to justify investments in the upper and mid funnel. 


So in the more awareness and consideration stages, because so far, there are very few systems or most system available that can really tell you, well, if you invest X on a book top that enables the trickle down effect to the bottom of why. So what I hear from you is, you know, with these tests that you just outlined, that technically should be possible. 


You technically should be able to say you know what, if we invest X amount on brand awareness activities, with the one group, we see this amount of sales on the bottom. If we don’t do that, for the other group, we only see this amount of sales on the bottom. Am I getting that right?


Trevor: You are. And so this is very strong for performance based media, as well as high funnel, mid funnel media, depending on the consideration cycle. So if you have a six month consideration cycle, it’s much more difficult to display an experiment that is going to be able to capture signal on that experiment six months out, right? 


So experimentation is best served to inform those questions as long as six to eight weeks out. If you’re looking for contribution, read beyond six to eight weeks out, or you’ll typically look to an econometric model or a media mix model to model that influence.


Steffen: That might also explain why are you focusing more on the ecommerce side, because obviously, the windows there are much shorter than probably on a b2b side, you know, where, as you said, you know, you could have several months, and some companies have a year long cycles. 


And you know, they might not even get enough information along that timeline, because they’re probably then also very expensive from buying that solution, therefore, low amount of leads, for example, which means it’s quite hard for any model to get some valuable information out of it and make predictions.


Trevor: That’s right. The ecommerce problem statement is also a very solvable problem statement. So understand the relationship between paid media, whether it’s online or offline and an ecommerce transaction is very solvable, incrementality question statement. In this world of advanced analytics, there are quite a few unsolvable problems, and there certainly are solvables. And we maintain a lot of discipline here to make sure we stay in the lane of solvable question statements. And so we really go deep and focus on EComm that we have a clear line of success on.


Steffen: Yeah. So how is incrementality measurement different from last touch, first touch, multi touch attribution, media mix modeling?


Trevor: Sure. Why don’t I unpack those provide a little context on those very quickly, let’s just touch on them. So last touch. Platform reported attribution is anchored on the last touch methodology. So the platforms Facebook, Google, TikTok, Criteo. All the media platforms deploy last touch methodology where they take 100% of the credit of each conversion or sale that they are in the path of, and they assign 100% credit to the last touch point. So any path that they’re on the path of that leads to a sale, regardless of whether that sale would have happened anyway, without the ad, they’re going to take 100% credit.


Steffen: Let me stop there, Trevor. I mean, probably for good amount of people that listen to the podcast, they might know the answer to the question I’m going to ask you, but why is lost touch, probably not a good solution?


Trevor: Because it’s assigning 100% credit to every platform’s last touch that was in the converting path. So you end up with, you can end up with severe duplication, right. With a comprehensive media mix, you have several platforms that can end up being in the converting path, each assigning 100% credit and ultimately resulting in the platform’s taking far more credit than they deserve. 


Clearly, each of those platforms does not deserve 100% credit for their last touch point. It’s also a correlative methodology. And there’s a lot of ways to gain the methodology to insert yourself into that last touch position. Right. So it’s incredibly flawed for a variety of reasons. The reason it’s stuck around for so long, really since the first display ad is because it is very easy to operationalize and align to.


Steffen: Yeah. And I think what I obviously also in the past have seen a lot is that if you use a system that kind of aggregates all your sales, it might skew to a platform. You know, if you do retargeting, retargeting all a sudden, might see a spike in sales. Talk about ecommerce here. Or search sees a spike in sales because it’s kind of a, you know, a lower funnel activity, but it disregards the media activities that came before that, that might introduce a product to an audience. And without that first touch, the actual conversion might have never happened.


Trevor: That’s exactly right. So you mentioned too, we call them low funnel demand harvesting tactics. So they’ll sit at the bottom of the funnel and they’ll harvest that demand created further up from the funnel. The reality is, and we’ve done a lot of incrementality testing on these low funnel demand harvesting tactics, they’re tipping it in, right? 


And so retargeting may influence the sale by 5, 10, 15% on an incremental basis. Whereas higher funnel, or mid funnel media that is introducing and building awareness, and really bringing attention to a product or service, you’ll find that media can be much more incremental to the tune of 80% ,90%, 100% incremental.


Steffen: Very interesting. So what do your clients do with the information that you provide? Because I would assume, I mean, although you are, you know, a platform where, you know, optimization can happen, but you’re natively integrating into Google, Facebook, you know, DSPs, etc? Or where do your optimizations start and where do they stop, if we think about optimization?


Trevor: Sure. So, the data layer, we do integrate into the really the entire ecosystem, anywhere that we need to integrate into we do and will to support the use case or the engagement. There’s two core use cases that consumer brands engage us for today. One is to enable media incrementality measurement at scale. 


So through our platform, we will streamline and automate best in class media experimentation. Most of the brands that come to us they’re tired of all of the manual work that’s fraught with a lot of issues. It’s a lot of challenges and toe steps along the way, that we relieve all of that pain by fully automating the experimentation process from design, deployment, management, reporting. 


And then we line up the experiment insight to a decision or an optimization that we surface. So that’s one use case. The second use case is we have an incrementality based attribution methodology, where we are direct substitute for multi touch attribution. So we provide consumer brands with cross channel attribution reporting and planning. And we have a workflow where we help clients look across their entire portfolio of paid media. 


We apply incrementality coefficients at the channel campaign, ad set, ad group level to help them validate investment plan, optimize your advertising spend now using incremental metrics. So our platform we deliver them includes the cross-channel incrementality based attribution reporting, it includes a media plan optimization tool, which is essentially a scenario planning tool to identify the optimal composition of your media mix. 


And then we’ve deployed at this point deployed over 25,000 experiments. And so we have very rich incrementality intelligence, and a database that we harvest for very interesting benchmark learnings for our clients.


Steffen: Interesting. Now, what advice do you have for brands considering deploying incrementality? And how do they set themselves up for success?


Trevor: So quite a bit, as you can imagine. I’ll provide a few comments, but I’ll highlight one. If the listener takes one piece of advice, this would be it. The organization must be aligned and ready to drive the business now based on incremental metrics. So incrementality and incremental metrics will be a new currency for informing decisions. 


And all of these companies have institutionally adopted last touch metrics. So you’re now shifting the entire organization from last touch metrics to now incremental metrics. And all stakeholders need to be on board with that. Finance, the C suite, marketing, your agency partners will all need to line up to this new incremental metric or currency. 


And when you make the shift, you’ll see that the decisions can move pretty radically. And so people need to be reassured that they’re not going to be held responsible for decisions made in the past that may not look so great now through the lens of incrementality. Right, the brands also need to be clear on operationalizing this new metric, this new currency. 


So organizational alignment, being ready to institutionalize this new metric is number one. A couple more, one would be find a neutral partner that is independent of any motivation to see media perform. They cannot and should not have a horse in the race here. You know, the number one rule of any measurement is you want to be crystal clear on the questions that you want to answer stepping into measurement, right. 


So you need to align on a testing plan to support the key questions that the organization wants to inform. And then also you want to align incrementality to your source of truth transaction data. So your transactions as opposed to platform conversion tracking or pixel base conversion tracking, which is now pretty broken. I can go on, but I think those are the things that I’d highlight right now.


Steffen: Yeah, what you just said is actually an interesting point to probably dwell on for a second. Obviously, at some point very soon, you know, all the cookies go away? How is that going to have an impact, positively or negatively, on this entire thought of, you know, incrementality and running these tests in order to identify what mixture of works better in order to keep a company’s revenue to grow?


Trevor: You’re right. So cookies are going away, this is exactly what we have been built for. So we talk about this as future proof methodology. User level measurement now is very challenged, right? It’s becoming extremely threatened. Incrementality measurement is a cohort base methodology. Cohort meaning, a collection of anonymous individuals in an audience segment. Right. 


So this is built for a cookieless environment. So as user level data restrictions continue to evolve, we can target and split audiences based on first party data and geos, where no user level tracking or cookie based tracking is required. So we were built for this cookieless environment.


Steffen: Interesting. Before we come to an end today, Trevor, are there any do’s or don’ts that you would say? I mean, we talked a second about, you know, advice for brands that want to start with looking at incrementality. But are there any from your working experience with working with brands, agencies, etc? Are there any do’s or don’ts that come up again, and again, where you say, you know what, keep that in mind when you embark on this journey?


Trevor: So my first point of advice is the organization has to be ready to adopt this new incremental metric. What I can tell you now is the industry over the last 18 months, is finally now making a hard move in the direction of incrementality. And the benefits are very meaningful. 


I’ve had many clients come to me after adopting this new set of metrics and show us the case studies of how they’ve radically course corrected the direction of the business, now moving from this severely broken last touch metric to an incremental metric. 


My advice would be if you do not have an incrementality practice, you’re behind. Like your competitors are adopting incrementality for decisioning. And they will have a significant edge if you’re still anchored on last touch metrics.


Steffen: So when we talk about advantage, what you’re basically talking about is they probably see much greater growth rates than someone who’s focused on last touch, basically.


Trevor: They’re much more clear on how to invest in an optimal way for their business.


Steffen: That makes sense. Trevor, thank you for joining me on the Performance Delivered podcast and sharing your thoughts on attribution and incrementality measurement. Now, if people want to find out more about you, about Measured, how can they get in touch?


Trevor: You can go to our website, measured.com, m e a s u r e d.com and you can reach me at Trevor@measured.com.


Steffen: Wonderful. As always, we’ll leave that information the show notes. Thanks, everyone for listening. If you’d like the Performance Delivered podcast, please subscribe to us and leave us a review on iTunes or your favorite podcast application. If you want to find out more about Symphonic Digital, you can visit us at symphonicdigital.com or follow us on Twitter at Symphonic HQ. Thanks again and see you next time.


Voiceover: Performance Delivered is sponsored by Symphonic Digital. Discover audience-focused and data-driven digital marketing solutions for small and medium businesses at symphonicdigital.com.