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Insider Secrets for Digitial Marketing Success
Steffen (00:12)
Welcome back to Performance Delivered, Insider Secrets for Marketing Success, the podcast where we explore what's actually driving growth and performance in today's complex marketing landscape. I'm your host, Steffen Horst, and today we're diving into a topic that sits at the intersection of data, psychology, and real business impact. Why experimentation programs often fail to drive meaningful growth and what it actually takes to fix them. Most teams today are running tests.
Steffen (00:38)
They are optimizing lending pages, tweaking headlines, testing creatives. But despite all that activity, many experimentation programs struggle to produce real, sustained growth. So what's missing? The answer often isn't more testing, it's a deeper understanding of how people actually make decisions. Joining me today is Shamir Duvason. Jameer is the co-founder and managing director at Smart Panda Labs, a technical marketing agency focused on enterprise B2C brands.
Steffen (01:04)
Over the past 25 years, he's worked across industries including travel, entertainment, and technology, partnering with brands like Southwest Airlines, the Walt Disney Company, and NBC Universal. His background spans product management, digital strategy, UX design, web development, testing, and analytics, giving him a uniquely holistic view of the customer journey. Today, he focuses on helping high-consideration brands rethink the post-click experiments.
Steffen (01:30)
Where decisions are actually made. Shamir, welcome to Performance Delivered. It's great to have you here again.
Shamir Duverseau (01:37)
Thank you so much
Shamir Duverseau (01:37)
for having me on. I'm excited about this one, Stephanie.
Steffen (01:39)
Now, Jamie, let's start by grounding the conversation. A lot of organizations today are running dozens and sometimes hundreds of experiments, but despite that effort, many still struggle to see meaningful growth. From your perspective, why do so many experimentation programs fail to produce real business impact, even when teams are actively testing?
Shamir Duverseau (01:59)
Yeah, I I really think a lot of that has to do with what perspective they go into experimentation with. so what are they hoping to get out of it? A lot of times it can be very, very basic, very surface expectations. So essentially they expect to see some graph where they'll see the conversion rate of the website kind of slowly climb up over time.
Shamir Duverseau (02:18)
and frankly, that's not something you're ever going to see. that's not a realistic expectation. Really, experimentation is is much more about learning than it is about anything else. it's a decision-making framework, and it's enabling organizations to make better decisions over time, which will holistically have a better impact on the business. So you're not gonna see that one.
Shamir Duverseau (02:39)
Graph that one line consistently kind of going up and to the right the way that you'd like to. But what you will see over time that the organization culturally is just making better decisions, better user experience decisions, better product decisions, better strategic decisions because they're basing it on experimentation and using that learning that they're getting, that feedback that they're getting from customers, whether they're internal to customers or external customers, to make those decisions.
Steffen (03:03)
Okay. So one of the most interesting aspects of your work is how you connect experimentation with human behavior. When we think about high consideration purchases, whether it's travel, financial products, or major services, the decisions the decisions process is really linear. What's actually happening psychologically during that customer journey and how should marketers think about it differently?
Shamir Duverseau (03:26)
Yeah, I I think we we like to think as marketers that someone goes to Instagram, they see an ad, they click on that ad, they go to a landing page or a PDP, they do a little reading, a little scanning, add it to their cart, check out, enter their credit card information, boom, they make the purchase. and in a perfect world that would happen, but we live in far from a perfect world. So that actually pretty much never happens. Maybe on Amazon. That's about it.
Shamir Duverseau (03:52)
But that's also because it's a pretty low consideration purchase that you're just kind of going, you know, going through the process. but what actually actually happens in most purchases, and in particular, as you mentioned, in higher consideration purchases, is a number of kind of psychological barriers that you're having to go through. There's these that decision hierarchy that you're kind of working through without even realizing it, but we all do it. just determining is this relevant to me? Do I trust what I'm seeing? do I have any mo and motivation to move forward?
Shamir Duverseau (04:19)
Am I properly oriented to what I'm looking for? Right. So all these kinds of things are happening that are helping you work through the uncertainty that you often face in terms of making a decision. And marketers often underestimate the power of uncertainty to freeze a consumer in their place. And more than anything else, more than any competitor, more than any price point.
Shamir Duverseau (04:41)
Uncertainty is the marketer's greatest enemy. So you're trying to create certainty. You're trying to make this person comfortable in taking the next step and the next step and the next step in the decision and ultimately make that purchase. And there's a lot of things that end up going into that. But first you kind of have to recognize what your true enemy is in order to be able to kind of create that weapon to be able to combat it.
Steffen (05:02)
Now a lot of optimization efforts still focus heavily on surface level metrics. Clicks, bounce rate, time on page, but those aren't always translating into decisions. How should marketing leaders think about differences between optimizing for clicks versus optimizing for decisions?
Shamir Duverseau (05:19)
Yeah, it you know, it really depends on where is that person kind of in their journey and and what is it you're trying to get them to do? What's the next best action, right? So there may be times where you're trying to optimize for clicks because for example, maybe you're you're very early on, you're top of funnel, you're trying to get a person's attention. And and ultimately if that person doesn't click on that Instagram ad, if they don't click on that paid search result.
Shamir Duverseau (05:41)
Then there's no movement forward. So you've got to get them to click. but you can't look at that click in a vacuum because I can create an ad to get someone to click. You know, tell me that you know you're giving away a thousand dollars. I'll get a lot of clicks, right? But those clicks aren't gonna convert when they find out you're not actually giving away a thousand dollars, right? So each of those kind of micro metrics, those vanity metrics, they have their place in kind of understanding what the person is doing, but
Shamir Duverseau (06:06)
without looking at that holistically, without kind of backing away and having the full context of ultimately what is the entire journey, what is it you want the person to do? It's easy to get lost in those vanity kind of microm micrometrics and you're not focused on really, okay, what are the milestones I need to get them to? How am I getting this person to ultimately add this item to their cart to actually check out, to actually go to the conversion process or to begin filling out the form or
Shamir Duverseau (06:30)
whatever it happens to be that you're trying to whatever action you're trying to drive online. So it's a matter of really looking at things more contextually, but not ever losing sight of what the ultimate prize is, which is to get that person to hit submit on that form, to hit checkout, to hit purchase, to enter their information. And everything ultimately is a means to those ends, right? To to be able to move people through those milestones in the process. So when you recognize that, now all of a sudden the click matters, but
Shamir Duverseau (06:57)
the quality of the click all of a sudden matters a great deal as well. So that changes your perspective on how you're trying to optimize for the click because now you want not just the action, but you want a quality action to take place where the person feels comfortable and saying, okay, I made this click. Yeah. Okay. This is what I thought I would see. This is relevant to me. And the person feels comfortable. And that barrier, that level of uncertainty has been released. Now what's the next step? well, can I even trust where I am? Is this is this a trustworthy website or landing page? Okay, great.
Shamir Duverseau (07:25)
You've removed another barrier of uncertainty. Now what's the next step? Right. And how do you continue that engagement in a positive sense? So, as you mentioned, some of those metrics can be very deceiving. Something like time on site that can tell you that the content's very engaging and people are kind of digging into the landing page of the PDP. It could also tell you the content's very confusing and they're spending a lot of time searching around, trying to find the right thing, and they just can't find it. So you've got to recognize that in the proper context and say, all right, how am I getting them past the barrier of uncertainty?
Steffen (07:35)
Mm-hmm.
Shamir Duverseau (07:52)
surfacing the information they need in order to move to the next step in the process.
Steffen (07:56)
So is it is it about connecting different metrics to get a clearer picture and then also using some of these metrics as earlier signals? Because if the end signal is I want more sales, right? And I just focus on okay, how do I get more sales? I might miss something on the way to getting more sales because as you just talked about it, someone might get lost on the side because the path to sale is not clear enough, right? So if I just focus on do I get more sales?
Steffen (08:23)
I might miss something on the way to that.
Shamir Duverseau (08:25)
Absolutely. So you know you think about like maybe a traffic accident took place and you know a police officer shows up at the site of the traffic accident and he says, What happened? And he's gonna ask five different people what happened and they're gonna give him five different accounts.
Shamir Duverseau (08:39)
Now that will be things that will overlap in those accounts. And when he gets all five of those accounts, then he'll probably be able to create a somewhat accurate picture of actually what happened. But if he just focuses on the account of one person, he's probably gonna go down the wrong path in terms of what actually took place in terms of the truth of the accident, right? So it's the same thing as we look at people on the web, we tend to focus on one thing. We tend to say, well, let's look at the web analytics.
Shamir Duverseau (09:04)
And how many people went to this page, and then how many people went to this page, how many people clicked on this? Okay, that that's what happened. Well, that that's only telling Paul or story, right? So when we look at the web analytics, we look at the experience analytics, we look at session recordings or heat maps, we look perhaps at like feedback and survey data. Well, now all of a sudden we're starting to speak to different witnesses, right? We're looking at that data point from different perspectives, and then we're able to then we're able to analyze that.
Shamir Duverseau (09:28)
Put that information together, and now we kind of have a sense of okay, now we have a picture of what's truly happening contextually. When we had that picture, now we're able to understand, all right, now I'm able to see more clearly this was the particular challenge. what caused the accident? it was, you know, the cat that ran across the street. That triggered this person in the bike to swerve and they tripped and they right. So now we're able to put together kind of the the story about of actually what's taking place.
Steffen (09:35)
Mm-hmm.
Steffen (09:46)
Mm-hmm.
Shamir Duverseau (09:54)
And now we're able to say, okay, this is what I need to address, right? or this is what I need to you know, not so much give so much information or or so much attention to, rather. So that that's the importance of what analysts need to look at. It's it's really a story of having to look at everything, multiple data sources, doing this thematic analysis of what's taking place to create the story. From that thematic analysis will come meaningful insights. From those insights will come recommendations, from those recommendations will come actions of
Shamir Duverseau (10:20)
This is what we should test or this is what we should change or perhaps here's a gap in what we're measuring. And it's that process that's ultimately gonna lead to the kind of learnings that are gonna have that larger impact in the business.
Steffen (10:30)
Is software and and AI these days helping to aid finding these stories because it can go through data sets so much quicker and can kind of build connections much faster than than than a human?
Shamir Duverseau (10:44)
Absolutely. yeah, I mean AI is really speeding up the process significantly and being able to do that. the real warning with AI has really with anything is AI is really good at making someone who who knows what they're doing better at it. It's not very good at making someone who doesn't know what they're doing and giving them a new skill, right? So it's one thing for someone who is an analyst, for someone who is a URX strategist.
Shamir Duverseau (11:08)
To kind of take information and insights from AI and say, okay, AI, analyze all the all these metrics or analyze all this customer feedback and kind of tell me what the themes are. That's great because when they get that information back, that strategist or that analyst is able to look at that and they're able to put that in the right proper context. They're able to say, that doesn't seem quite right, or they they're able to access other
Shamir Duverseau (11:30)
Add this other piece of information that perhaps the AI didn't take into account, maybe you lost that, you know, you lost track of it, whatever the case is. And that context makes a good decision. But if kind of Joe Schmoe comes in and Joe Schmoe is, you know, I don't know, in finance or something, and they say, Well, okay, well, just look at this data and tell me what's wrong with this page, not having that that skill set behind them, not having that context.
Shamir Duverseau (11:51)
It's not as easy for them to discern what are the gaps in the AI. It just seems like it's correct. It seems like it's right enough. And we're just going to move forward and kind of go with that. So, as with all technology, AI does a great job at being an accelerator to what you're doing. It does not do a great job at replacing what you're doing, contrary to what the powers that these say. And it's funny, I I heard her interview the other day making a great point about AI, and it really made the point that.
Shamir Duverseau (12:14)
When you hear people say AI is gonna replace jobs, right? It's gonna it's gonna make it so you don't have to hire as many people, all those kinds of things, though the people who are kind of putting those stories out are the AI companies who are trying to drive up their valuations, right? That that's where that's coming from. That's that's not coming from real users. really, when it comes down to it, when it comes to large enterprise organizations, AI adoption is pretty slow because businesses move slow and they move methodically and because the AI capabilities are starting to level out a bit, at least at at the moment.
Steffen (12:24)
Sure. Of course. Yeah.
Shamir Duverseau (12:42)
Right. So we're not quite seeing what kind of we all the hype that we've been hearing, which is why again it's important for AI to be used as a tool by the expert and not as a replacement for those experts.
Steffen (12:50)
Yeah.
Steffen (12:53)
Yeah. I it it's interesting and we could probably now pivot this conversation into a completely different direction. but I'm I'm of the exact same opinion because I can put myself in a race car and I can drive it probably around a racetrack. The question might be how good? But I will never be able to push it to the max and get the most out of it. And it's kind of the same thing with AI. If I don't understand what AI is able to do, if I don't
Shamir Duverseau (12:58)
Yeah, we could. I I kinda went to tangent there. Sorry about that.
Steffen (13:19)
If I can't call BS on the output and and and can further fine-tune things, the AI is not going to help me. You know, I I might get 60, maybe 70% out of the AI, but I won't get this this this great output from it. So yeah. Anyway, let's let's go back to talking about the topic today. But so in in complex buying journeys, customers often hesitate.
Shamir Duverseau (13:34)
Exactly.
Shamir Duverseau (13:38)
Yeah.
Steffen (13:44)
Even when the offer is strong, that hesitation where many or that's where many conversations actually get lost. What are the most common psychological barriers that prevent customers from moving forward and how can teams start to identify them?
Shamir Duverseau (13:59)
Yeah, I mean there there are so many, depending on the nature of it. trust is a huge factor. security is a huge factor, stimulation. So those are three kind of big kind of things that block what's happening. So trust, do I feel strong enough about this brand that I can spend those dollars and and and feel like I'm I'm gonna get exactly what's being promised here. security certainly is important and of course that
Shamir Duverseau (14:23)
factor becomes more important as the purchase price goes up, right? As the stakes begin to go up. and and stimulation, right? So you it's one thing to have the idea of spending a large amount of money to maybe buy a new car or to go out on a vacation. but it's another thing to actually say, all right, you know, charge my credit card $5,000, $10,000. All right, I'm gonna take out a loan for $50,000, right? Actually doing it.
Shamir Duverseau (14:42)
requires some semblance of like, okay, I like I need to feel like I'm comfortable kind of going over this hump and and actually having that charge and and taking that responsibility on. So the idea of it and the the actual action are often you know two very different things in our minds. And from crossing one crossing over from one into the other becomes a real issue and challenge for for for many people. So to answer your other question, how do you figure out where those barriers are? Well
Shamir Duverseau (15:09)
A lot of times it's where in the experience you're seeing that drop off and hesitation. That's certainly a pretty good indicator. I'm a big believer certainly in analytics, but I'm also a huge believer in gathering intelligence. So asking questions, looking at page feedback, looking at chats.
Shamir Duverseau (15:23)
chat logs, looking at customer support calls, right? It's when those people are interacting and the kind of questions they're asking, those kinds of things give you a lot of information. Being able to inject just a couple of questions when someone maybe exits the process and say, hey, I saw you left today. You know, do you mind saying why?
Shamir Duverseau (15:39)
Doing those kinds of things and getting that real raw input and feedback from customers is invaluable because in that you'll tend to find patterns of, wow, you know, we don't talk anywhere about what our return policy is. Right. So we're we're not getting people's trust because, you know, they think I'm gonna spend this money and then I'm gonna be stuck. And if I don't like it or, you know, if there's an issue or challenge or my life changes, I won't be able to cancel my plans and I've lost out on my
Shamir Duverseau (16:05)
know my deposit or I've lost out of my five thousand dollars because they didn't know that, hey, you have until seven days before to cancel or you have a 30 day money back guarantee or whatever the kind of things are, right? So those kinds of things usually come up in those more
Shamir Duverseau (16:19)
quantitative measures that we put into place. And a lot of that again is just happening by by nature in things like chat logs or customer support calls that are just by nature happening anyway. And picking up on those patterns will help us to say this is the information I need to surface in the process that people perhaps aren't finding as easily as we thought they should or would, or perhaps we're not even surfacing at all, or we're not surfacing at the right time in the process to be able to you know deal with those particular barriers when people are have those things on their mind.
Steffen (16:28)
Yeah.
Steffen (16:45)
So it sounds like you're going way beyond kind of what the normal CRO service offering usually includes. It's kind of where we're developing tests and we're looking at, you know, which elements on the website we're going to change, which which which messaging, imagery, or not on a very very basic level, et cetera. it sounds like you go beyond that part, really also looking into into into kind of user interviews and and and and and
Steffen (17:11)
those data sources to get a better understanding of what works and what doesn't work.
Shamir Duverseau (17:15)
Yeah, absolutely. I mean, anyone who's like, you know, serious about experimentation, I mean, there are certainly ideas, good ideas people have. People, you know, wake up on the right side of the bed one morning and have a good idea, and that's great. You know, awesome. Congratulations. But if you want to build a real framework and you really want to build a culture around testing and experimentation, that really needs to come from having a framework around gathering consistent feedback from users. Again, both qualitative and quantitative, both kinds of feedback. So we
Shamir Duverseau (17:43)
Getting great data from analytics from Google Analytics or from Amplitude or whatever, from a content square or a full story. You're you're getting some great insights there. But then what are you also doing on the research front to gather some surveys, to look at those logs, to look at those conversations, and use the combination of those two to begin again, feeding that loop of research leading to ideation, leading to test, leading to analysis. Then again, starting that loop again. So now we've made this change. Well.
Shamir Duverseau (18:09)
The nature of a change is going to now generate different kinds of feedback and different kinds of questions. So it becomes a repetitive loop in and of itself, but you've got to set up the right framework to be able to get that flywheel kind of going and turning. And if you in fact are generating those ideas from actual research and feedback and not just kind of from someone's idea, you're going to see just in general better learnings from that. Because now you're not.
Shamir Duverseau (18:33)
You're getting kind of out of your own head and the own biases that we all marketers have when it comes to our own products and services. We think we know so well what people think of our products and services, and almost invariably we're horribly wrong. We just we're just
Steffen (18:36)
Sure.
Shamir Duverseau (18:45)
We're terribly bad at it. We're way too close to our products and services to be able to anticipate how people feel. So getting that flywheel and pace and getting that constant feedback is gonna be critically important to being able to set up and establish that that that that flywheel and framework to be able to get that good testing results.
Steffen (19:00)
Yeah.
Steffen (19:01)
Yeah, makes sense. Now if experimentation is meant to uncover what works, then understanding those barriers becomes critical. But many testing programs don't incorporate that layer.
Steffen (19:11)
This also brings up a broader organizational change. Exploitation doesn't live in a vacuum. It touches marketing, product engineering, and analytics. What does a healthy experimentation culture actually look like when marketing, product, and IT are aligned around improving the customer journey?
Shamir Duverseau (19:27)
That's a good question. you know, collaboration, orchestrating stakeholders is incredibly important in order to get anything actually accomplished for the sake of the customer. and that comes down to kind of two big things. So, first of all, from an organizational standpoint, from a business standpoint, what are we aligning to? So what what is the ultimate goal here? Because every department is gonna have their own objectives, goals, OKRs, right? All those kinds of things.
Shamir Duverseau (19:51)
IT is being measured on one thing, marketing is being measured on another, the product team is being measured on another. And ultimately, as humans, we kind of do what's in our own best self-interest. So we're worried about the measures that affect us and affect our department and what am I going to be reviewed on? And the other departments are doing the same thing. So in order to really have an effective program, you need some executive sponsor to kind of come in and say, yes, you have these different OKRs, you have these different goals, but they all roll up to what we're trying to do as a company here.
Shamir Duverseau (20:18)
And here's how experimentation fits into that and feeds into that. So now everyone can say, okay, so this is a North Star that we're all looking at. We're all looking in the same direction. This is what we're trying to do, right? So from a business standpoint, that's super important. but then you've got to realize that, especially as a marketer, if if you're the one kind of leading this charge, you've got to recognize you've you've also got an internal customer that you need to serve. And and just like you need to have insight about your
Steffen (20:40)
Mm-hmm.
Shamir Duverseau (20:43)
external customer and really kind of understand them and and their behavior and what they're looking for and what they want. Well, it would behoove you as a marketer to also understand that from your IT partner and from your product partner and from your data engineering partner. Because they're not just roles, they're they're people and they have personality. So understanding that is going to help you deal with them and coordinate and collaborate with them better, kind of on their level in terms of what's important to them, so that all of a sudden the time that you're spending working through this becomes more efficient. So now
Steffen (20:53)
Yeah.
Shamir Duverseau (21:10)
You've got the same North Star, you're treating them like a customer. So you're trying to look at things from their perspective and kind of meet their needs, understand their goals and their challenges. And now you're kind of working it from both ends. And by doing that, you're slowly bringing things into alignment. And now everyone's kind of moving in the same direction because they see how it's affecting them personally. They see it's how it's affecting their job. They can see why they should therefore be invested in in moving an experimentation program further.
Shamir Duverseau (21:36)
And that creates that culture of collaboration that you need in order to really have that learning begin to flow throughout the organization.
Steffen (21:42)
Yeah. Now before we come to the end of today's podcast episode, what are the biggest mistakes organizations make when trying to scale experimentation and how how can they avoid falling into those traps?
Shamir Duverseau (21:55)
Yeah, that's a difficult question because it's every organization is so different. And there are certainly different schools of thought around experimentation of how to either centralize it or democratize it. Are we giving it to different product managers on different teams? Are we having one central team do it? Are we having a center of excellence?
Shamir Duverseau (22:12)
And and each of those ways of doing it really has its pros and cons. a lot of it depends on the organization. It depends on the goals and what you're trying to accomplish, and then weighing those goals and and what you're trying to accomplish against those pros and cons, and then determining, okay, for our team and for our organization and what we're trying to do, this seems to be the best way to end up tackling this. honestly, what we see more than more than anything else in the space that we operate in is the
Shamir Duverseau (22:37)
difficulty and challenges of people having even getting started. So we have many, many, many organizations that we've worked with, c clients that we've come across, we had conversations with, where they have the tools in place
Shamir Duverseau (22:49)
to be able to gather data, together research, to actually run experimentation, but they have no processes in place. And every time it kind of sort of starts up, it kind of really falters and maybe they run one or two and then that kind of peters off over time. So the challenge that we usually find is just getting started, getting over the hump of of of being able just to get started and get the process going, trying to get maybe some quick wins up front to kind of show the value in it. And again,
Steffen (23:15)
Mm-hmm.
Shamir Duverseau (23:16)
looking at it from the lens of making a decision because an experiment that wins is is great. An experiment that loses is almost just as if not more valuable oftentimes. So there's been times we've gotten organizations into experimentation by launching an experiment that ends up losing because it was maybe, hey, you know, so and so has wanted to do this for a long time. They really want to make this change in the website. So then we run it and it's like actually if you would have made that change, like you you would have lost money. Like that would have made things worse on the website.
Steffen (23:25)
Mm-hmm.
Steffen (23:36)
Mm-hmm.
Shamir Duverseau (23:42)
So now do you know not only not to make that change, but the time and cost wasn't spent putting that change in the roadmap, expending resources on it, right? Actually making the change. So right there, we just saved you money, right? Maybe we didn't make you incremental dollars, but we saved you money, which is just as valuable, right? To the ultimate bottom line of the organization. So going in and trying to get those wins, going in and trying to and by understanding what
Shamir Duverseau (24:06)
the power of experimentation can be just from a learning standpoint and how we can both create incremental dollars, how we can save dollars, how we can help to prioritize resources, production resources. Looking at it from kind of all those different angles will help an organization to say, all right, well, let's at least get started. Let's start to get some of those quicker wins that we can get by better prioritizing projects, by better allocating costs across different resources.
Steffen (24:27)
Yeah.
Shamir Duverseau (24:30)
And then we can begin to pick up speed. So I'd rather get started and then get to the point where they have the problem of, okay, how do we how do we organize this? How do we really scale this? How do we really grow this? Because they want to do it and now they want to figure it out. that's a better problem to have than well, we can't even get this off the ground. And
Shamir Duverseau (24:45)
The problem is now you're not learning anything. You're just kind of doing what you've always done. And that's not gonna help the business to be able to grow. Cause every single piece of data and research we've seen says that organizations that have that culture of experimentation with their challenges and problems, but those organizations always grow faster than the ones that don't because they're learning.
Steffen (25:02)
Because their decisions are based on data in the end, right? And not just the gut feels like, today, as you said, you get up in the morning, it's like, we should change the colour of our website to red because I feel like, you know, makes sense. Jamia, thank you so much for joining me on the Performance Award podcast and sharing your perspective on on our today's topic. It's clear that experimentation alone isn't enough. real growth comes from understanding how people think, how data is cite, and designing experiences that help them.
Shamir Duverseau (25:13)
Exactly.
Steffen (25:28)
move forward with confidence, basically. for listeners who want to learn more about you, your work, and want to connect with you, where's the best place to reach you?
Shamir Duverseau (25:37)
Yeah, they can certainly please connect with me, follow me on LinkedIn where I post about this all the time. Post not just about experimentation and the postweek experience, but about the importance of collaboration and working with the other teams to be able to move the business forward and accomplish those marketing goals. and of course you can always check us out on smartpanda labs.com. But feel free to look me up on LinkedIn. I promise you I'm the only Shamir DuVousot on there. I'll be easy to find and we'll be able to to connect.
Steffen (26:02)
Okay, perfect. As always, we'll leave that information in the show notes. Thanks everyone for tuning in. If you enjoyed this episode of Performance Silver, please subscribe and leave us a review on iTunes or your favorite podcast platform. To learn more about Symphonic Digital, visit us at symphonicdigital.com or follow us on X at SymphonicHQ. See you next time.