The Marketing Millennials: Deep Dive into How to Think About Your Marketing Metrics With Jordan Narducci
Their experiences shed light on the significance of storytelling, leveraging advanced tools, understanding data analytics, and the continual pursuit of growth and innovation in marketing strategies.
Performance Tools & E-commerce Insights
A spotlight on Black Crow, a tool leveraging Shopify data for refining digital marketing strategies, particularly through targeted and retargeted efforts aimed at conversion.
Jordan's transition from consulting to e-commerce marketing reveals the vitality of embracing mistakes, experimentation, and the journey of learning, especially in the fast-paced e-commerce domain.
Crucial Role of Data Analytics
Accurate tracking and data analysis emerge as critical for informed decision-making, with shared Google Sheets and detailed analytics dashboards being highlighted for their utility in monitoring key metrics.
Deep dives into customer behavior, product performance, and understanding crucial metrics like customer acquisition cost (CAC) and lifetime value (LTV) through clean, reliable data.
Emerging Marketing Strategies
Subscription models are praised for their potential in achieving predictable revenue, with strategies to enhance subscriber rates and understanding churn for sustained success.
The necessity of prioritizing marketing efforts based on data is emphasized, alongside fostering a culture of testing everything to allow data-driven decision-making.
Conclusion
In essence, these discussions provide invaluable insights into the role of data in shaping effective marketing strategies, the importance of adaptability and continuous improvement, and the potential of innovative approaches to drive growth.
It serves as a call to marketers at all levels to leverage their experiences, experiment boldly, and prioritize efficiently to adeptly navigate the complexities of the marketing domain.
Read the full discussion in the transcript below 👇
Audio OWEWK5626288523.mp3/2024-03-12
Welcome to the Marketing Millennials, the No BS Marketing Podcast. I'm Daniel Murray, and join me for unfiltered conversations with the brains behind marketing's coolest companies. The one request I tell our guests, stories or it didn't happen. Get ready to turn the f**k up. You have to grow constantly, which is why I like this space and you, anybody can get into it, right? You can kind of like, like I did, right? You just test your way into it, you make mistakes, you figure it out and then as long as you continue to get better, that's what matters and there's going to be setbacks and stuff along the way. But I, that's kind of my favorite thing about this world is you can just constantly test and learn and iterate. Black Crow is the performance marketing tool whose job is to make e-commerce marketers better at their jobs. It's a pretty sweet predictive model that uses your Shopify data to automatically make all your digital marketing channels more efficient. Targeting and retargeting shoppers most likely to buy. Visit BlackCrow.ai flash Daniel to get 30 day free trial and $1,000 credit for your first monthly contract. What's up everybody? Welcome back to another episode of the Marketing Millennials. Today I have an old coworker from one of the first jobs I ever had at SnackNation. His actually little known fact was Ari's first boss and Ari's first role in e-commerce. This was exciting to chat, but Jordan, welcome to the pod. Thanks man. Yeah. Happy to be here with some pretty amazing alumnus of the SnackNation days. It's been fun to see you and Ari grow in your careers. I want to get started and for the people who don't know who you are, how did you get into e-commerce and marketing? Totally fell into it. Like I feel like a lot of us, I spent the first chapter of my career, six or seven years in consulting and then I went and got my MBA and was like, needed to find something that I was way more passionate about and that led me to the startup space and SnackNation. I joined in a very nebulous title as the chief of staff and was doing strategic projects for the business as I graduated, as I was finishing up my MBA. It was during that time that they were like, we want to launch a direct to consumer side of the business. I had proven myself that I could start things from scratch for the business and that was my first venture into direct to consumer and launched our SnackNation's direct to consumer side of the business and made a ton of mistakes and pivoted a bunch of times as you saw along the way and worked with some really great people. That led me to, I ended up working for a few years at Kellogg in a global fashion, basically leading their global direct to consumer strategy. I've got to work with a bunch of different bigger brands, but also got to launch some new and exciting brands through that channel. Then I've worked at a mix of smaller companies since then. I worked at a brewery that had a pretty big side of their business that was like a direct to consumer, kind of like a wine membership, super premium product. And now I'm at a supplement brand, which is probably my favorite category that I've worked in. It's certainly a lot easier than food in terms of margins and cost to ship. It's been a fun space, but it's a very crowded space, much like breweries. I'm excited for you. It's also one of the most known nutrition brands, supplement brands now in the market. It's exciting that you're going to be on the rise of it, so it's cool to see. I'm glad, I'm happy you feel that way because I think the average person hasn't heard of Momentous yet, which gets me excited because I think we have a lot of runway. But yeah, we definitely found our way into a great market with just being differentiated from everyone else based on the experts that we partner with, the quality and the testing that we do. And yeah, I've personally just gone on a journey ever since reading Peter Atien's book, Outlive. As I hit my late 30s, I'm like, I want to live a healthier life as long as I can. So that's kind of put me on this journey around supplementation myself. And I had never really taken a lot of supplements before Momentous. So the more I've learned, the more I've been like, wow, this is foundational to health that everybody should be taking certain, or most people should be taking more of certain products, like protein. None of us eat enough protein throughout the day to build mass strength for the future. So yeah, I've got really into it along the way. Awesome. And I know one thing from you, because I know from like the Snack Nation days and you talk about the Momentous days, is you've always been a big proponent on spreadsheets and data and making sure things are tracking well. Can you walk through a little bit of like the importance of it, and then we can walk through like how you recommend people setting up data and tracking? I feel like it dates back to our Snack Nation days in terms of how we looked at things. I've always been a big fan of pulling data into a spreadsheet. You know, now it's obviously Google Sheets that it can be shared across a team, but identifying like what are your key metrics that you want to look at? For us, it's like, at least initially, I was pulling a lot of those from Shopify, going down in granularity, like what's our top-line revenue, but what's our revenue for subscriptions, what's our revenue from new customers, and what's our revenue from one-time returning customers? But then looking at conversion rate by those areas, average order value by those areas, and all of these other areas around that I feel like that you can get in Shopify, but most people don't, just look at Shopify's kind of key dashboards. But what then you miss out on is like the tracking and the trends over time. So I'm a big fan of like setting your columns like a weekly cadence, and then having like a monthly target in terms of your budget goals, and seeing how you're pacing each week along versus your target for the month. And yeah, I think when I joined Momentus, we were doing a lot of tracking, but what I feel like we brought to the table since then, it's like really going into a level deeper around like retention, and like, you know, everybody talks about it in e-commerce around like LTV, right? You should be looking at LTV, you should be looking at your CAC, like customer acquisition costs. But I feel like there aren't great tools for looking at that. There's some apps on Shopify that you can do it, but the data is really messy. So I've been on like a journey since joining Momentus of like, how do we clean up our data and like truly manipulate it in a way that we can start tracking and looking at it with accuracy. And I feel like we're finally getting to that place. And I'm happy to kind of like talk more about that. But it's been a really powerful tool and some insights that have come out of that that I can also speak to. The problem when you're looking at data as like a whole and blended, like sometimes if it's blended good, the data, like you don't look at the inefficiencies in in the whole pipeline or in the business. But also if it's bad, then you probably could be like messing with things that are actually efficient that you shouldn't be messing with. And it could be something else that you should be. So like having a way to look at it by segment, by channel, by landing page, by all the different touch points helps you look at things and be like, oh, actually, Facebook is doing good for this segment, but not that segment. Like we should actually just look how we can improve here, not there. I feel like on the meta side in particular, that was an area that like when I joined, we were primarily looking in platform at our metrics. And I was like newer to Northbeam and Triple Whale and some of these tools out there that you could use. But like I really don't trust what you get in platform, especially for meta. And what we did was we really just started using Shopify to start like truly last touch, right? Like last touch attribution of like what was meta doing for each of our campaigns in terms of new customers? And you can get CPA from meta, but you're not getting CAC, which is a very important distinction. You're getting cost per order, but you're not getting cost per acquisition. And the problem with meta is you don't know if you're targeting, like obviously you can specify that you want to prospect and allocate a certain amount of your spend to that. But like the reality is a lot of your revenue can come from returning. And so it's really important to use either Shopify and like use that as like a guidance between because you know that like the reality is that it's somewhere between what you're showing in platform and somewhere that between what Shopify is showing as last touch in terms of CAC. And so I've found like starting with that as a basis, we found like a 3000% difference, which is just insane in terms of our customer acquisition costs between the two. And so you can imagine like we were optimizing in a lot of the wrong ways. And so since then, we then compared Shopify's CAC to Northbeam and we ended up finding that it was close enough that we feel confident to move to that. But I do think it's important for people who are listening to like really just like don't trust. Obviously, you need to use the platform metrics when you're optimizing within them, but you need to have a source of truth outside of that as well and like reground yourself. And I think the other thing on just like attribution that I think we've done that I think it's unique maybe to our business that a lot of people don't do is we started looking at like a blended mer across Amazon and dot com, which I think is a really interesting way of like saying, OK, if we as a company, we run a lot of podcasts like we have a lot of audio ads. The reality is that when you run an ad, even if that promoter is saying like, go to livemomentous.com slash Tim or whatever the landing page might be, they still are probably like half of the people that hear that podcast are probably still going to Amazon because they're like, I shop on Amazon. That's my first place I start. Right. And so if you really want to track performance across channels, you actually should be looking at a blended mer across both for us, Amazon and dot com, or if you have multiple channels, you know, across multiple channels and then look at your spend across all of those channels. So that's something that we've done that I feel like is a little unique. And it's it's been a really good way of like looking at us, looking at the business a little more holistically than we have historically. I just want to ask for those who don't know, why should you look at mer and what what does mer actually what does it stand for? So just for people who don't know what that is. Mer is basically just like your overall revenue versus your overall spend. Right. So it's like a percentage of your revenue to your overall spend. Now, most people look at like row ads within a channel, right? You might say like, you know, our row ads within Amazon is 400 percent, which means you're getting four dollars for every dollar that you put into your ads. But when you only look at it on a channel by channel basis, which is also important to do for trends and tracking over time and as you as you change your ratio of spend across channels. But if you only do that, then you're not going to see more holistically about what is your blended look like. And I think the reality to answer your question around, like, why is it important is that attribution is really hard. And, you know, it's the only thing I know for certain is that it's not 100 percent accurate, right? Because you have to kind of draw a line in the sand about where you're sourcing your data from. And for example, like we use post-purchase surveys, but then we also have discount codes. But then we have also have UTM parameters, right? And then you have GA4, right? There's like and you have Shopify, like there's like five areas that you could get, you could that all of those could could show you a different attribution. So it's really important for you to figure out, like, what is your attribution model? How are you prioritizing those things? And then how do you want to look at that? So Merck kind of like gets rid of all of the kind of messiness of that, of how channels take credit, because Meta wants to take as much credit as they can. If they show you an ad, if you haven't even scrolled to that ad, but it's at the top of your feed and maybe like you could get to that, like they're probably going to take credit for that. And so, you know, that's where I like, I'm not a big fan of views in Meta because I feel like they claim the world. But every platform, you know, email, Klaviyo, they're going to look at a different attribution window than maybe GA4. And so it's really important for you to look a little more holistically. It just allows you to kind of blend that, zoom out and be like, am I hitting my overall revenue targets for the business based on spend? We also look at a blended CAC, which is basically the reverse of that, right? You're just basically dividing it now. So you're basically dividing your spend by your total number of new customers, you know, which is different than your total number of purchases, right? Which because you are returning versus new. Yeah. And I also think it's important because especially in a subscription business, like you could be spending on the same person over and over and that's not efficient either. I mean, if you're not like a business that's trying to get a different purchase on your site that's not subscribing, it's like you're trying to say, OK, but if this customer already came in to buy a protein and they come again through Facebook and buy the same protein, like that's not an efficient way to keep them buying protein for you, but keep bringing them in the funnel more and more. I mean, what you're hinting at is like it is a lot cheaper to retain a customer than it is to purchase a new customer. And it's gotten more and more expensive as I've been in this industry in the last seven or eight years. So, yeah, I think we put a lot of emphasis on that and like retention is something that I feel like I feel really proud of in the six months or so that I've been at Momentus. We've made some pretty big strides in terms of one metric that I just I feel like is really important for people to look at if you have any sort of business that looks at subscriptions is the percentage of new customers that are subscribing. Some people call it like a take rate of an offer or a take rate of a subscription. It is a really important metric to look at. In the time that I've been here, we've seen that metric double and we've gotten insights around like if you message the upside of a subscription discount combined with a new customer discount, you can talk about like up to 40 percent, right? Because we offer 20 percent off on subscriptions. subscription, and then you can get another 15 or 20% off, depending on which offer you're coming through. So when you talk about the upside of like, get up to 30% or get off up to 40%, there's a lot of power in that than just saying get 20% off, subscribe. And that's been a huge unlock for us that we discovered during Black Friday. Our business is becoming more and more of a subscription business as a result of that learning. So I think that's just like one thing that I haven't historically looked at, but now it's like the number one metric I pay attention to. Predictable revenue helps you as a marketing department too. You don't have to keep guessing that, oh, how many new proteins do I have to get sold this month? It's like, okay, I already have going into this month an average of this amount of, that is gonna be already buying because they're subscribed. And then you just can be like, okay, here's our average churn during this time. And then you can start doing more predictable stuff in marketing when you have a predictable revenue going month over month. A hundred percent. I mean, it just becomes a lot easier to forecast. You also have a lot, you can have much more predictable return in terms of how you expect a subscriber to stay on. For us, the big unlock and the reason why we pay attention to that metric I talked about is like the LTV of a customer when they subscribe, when they first join as a subscriber versus a one-time purchase is two X within the first 12 months. And it gets bigger and bigger as obviously time goes on. It's not rocket science. Like everyone's like, that's intuitive, right? Like a subscriber stays longer on average. But if you know that data, then you can start prioritizing like how you message and maybe I'm willing to spend a little more on a subscriber than I am on a one-time purchaser. And then some really interesting stuff, like we started working with an agency in India to create like a retention dashboard for us. That basically it takes those like Shopify apps, you know, like Lifetime, there's a few of them. It takes it to the next level because I felt like the challenge with a lot of those other apps is you couldn't trust the data. There's a lot of like noise. Like maybe you have like wholesale sales that come through Shopify and kind of like messes up the data. This team in India has basically helped us both pipe all of our data into a Tableau dashboard, but then also clean it. Like I think a lot of the work goes into like cleaning and manipulating the data to make sure it's legit. And so what we can now look at is like lifetime value for .com versus Amazon. But then what we can do is sort by product, right? We can say like, here's all of our products, but here's the lifetime value of like, say creatine versus omega-3s versus protein. And they all have drastically different LTVs, which then allows you to start thinking about, okay, which of these products should we prioritize? And the other interesting thing is we can look at of those like new customers that I mentioned that are subscribing, we can also look at like what product are they coming in through? What's the number one product that new customers are purchasing? And that obviously is driven a little bit by your marketing tactics, but also by just like what converts best, right? And so by having that data, we've been able to both identify like, what are the products that sell best to new time customers, but then what are the ones that stay on longest? And there might be some that like, we drive a lot of new customers, but the LTVs crack. And so actually we shouldn't be prioritizing those, or if we do, we need to have like really strong upsells to get them on additional products. So we're like just now getting to a place where we have like much more sophisticated data to be able to look at like on a product by product basis. We can also look at it by channel, right? Like how's a Meta customer versus a Google customer, or we can look at it by partner, right? Like how's a partner that came in through like the Tim Ferriss podcast? How's that versus someone who came in from another pod? You know, like, so it's allowing us to get a lot more granular and also using like post-purchase surveys to attribute revenues from that. So it's been a really powerful tool that I feel like that's like how you take what we did in a manual basis from Shopify to the next level and really start automating it, which has been a powerful tool for us. But we still like, even with all that work, we still manually pull, because I feel like the process of pulling stuff and looking at it on a weekly basis and talking about it for 30 minutes as a team is really powerful because it talks, because you identify trends and challenges. And if you have budget for each, if you have KPIs and targets for each of those metrics, you can identify like what's off or what's on, right? Like, so I think it's just like a really powerful process, I think, even with that automation. Black Crow AI makes you better at customer acquisition, full stop. Connect it to your Shopify stack and watch that predictive model supercharge the performance of your digital channel. Take Meta for example. Black Crow predicts target audiences that are most likely to buy, driving the right users to your site from your Meta ads. Then helps you retarget customers, and you can get a 30 day free trial for your first monthly contract. Black Crow AI is a free trial that you can get in the past seven days with true first party, privacy friendly tracking. Visit blackrow.ai slash Daniel to get a 30 day free trial and $1,000 credit for your first monthly contract. I think it's so cool to have a process where you have the best product to get them to stay in our world. And then once in our world, like how can I upsell them to be into more and more or cross sell them into more and more products? Because it could be great that you can look at it and say like, okay, people buy protein, eventually they're gonna wanna buy creatine or something else because they're working out. I mean, we used to do this in SaaS company a lot, but we did it more for like what segment of customers. So it'd be like if they came in and they were like, say service time, for example, when I was at a service, they came in through like plumbing or electrician companies or there's like HVAC companies, which ones are gonna be like the highest retaining customers that we can have? And then should we go after like HVAC first or this first? It lets you kind of prioritize your marketing, which is one of the hardest things to do in marketing is like prioritize your marketing and stay focused. So that's what this helps you do. That was the problem. I mean, first of all, I feel like, yeah, B2B SaaS companies do that really well. Like a lot of them do that really well. It's like identifying like grouping leads and then identifying like how do those leads convert? And then how long do they stay on? What are the best types of customers? Because then you can go after them. I feel like when we were starting at Momentus, it was like, we have a lot of products, like which products should we prioritize? We knew what our best sellers were from Shopify, but you don't know like that next level of granularity around LTV by product until you do this analysis. And then you also don't know like, what are the products that drive the most new customers? Because it gets blended, it's just hard, it's messy, right? It gets blended in with all those subscription recurring orders and all those one-time purchase orders. But you don't know like if it's new versus returning by product, like, yeah. So I found it to be really powerful, especially as like GA4 has just become, I think harder and harder to trust. Like I've found it to be like anywhere from 10 to 20% off from Shopify at any given time. So this gives us like a source of truth that like matches Shopify to the scent, right? And then it looks at our attribution across all of our channels based on what we've aligned there are the priorities. And it allows us to look at like how our products convert and then how do our customers stay on based on those products. So it's been powerful. I can speak a lot to this company that has helped us with this process. They've been extremely efficient and great to work with. So if anyone wants to DM me, I'm happy to connect them as well. You kind of have another layer added onto this business too because you have someone who has a big brand attached to them that is also part of it. So it's kind of like how many people actually know him that are coming to Momentus versus like how many people we driving that didn't know him into Momentus. So you have like even a, cause like eventually someone who's like an influencer, you have to get past their influence when you're doing marketing. So there's also like another layer too. I think that's been an interesting progression for us as a brand. And one of the big initiatives that we focused on was like, how do we scale beyond just a handful of partners that we were working with in the past? And we really started figuring that out. I think this past year has been where we've kind of graduated from being like growing through like a handful of partners to like really using more traditional funnel marketing that has been really powerful for us. And I think we're just, we're like still at the very beginning of that process, which is why like for a business that's already has, you know, established itself to be like just going to that, it's a pretty awesome place to be in. That's where I get really excited cause I know we're still early days of tapping into the target audience that it's already resonating with. So I'm really excited about it. I know we kind of got deep into the conversation, but I want to go back to you just explaining what your dashboard looks like so people can have like an understanding of what that is. So if they wanted to maybe build something a little similar, they can do that. Let me start with the Shopify one that everybody can build, right? Because the first thing I did when I joined was I built this dashboard. So I think this is just like a good rubric. So, you know, it's basically has weeks in the column. And then at the very end, after the four to five weeks, depending on the month, there's kind of like a month to date, like how are you pacing for the month versus your target for the month, right? So I have like a pacing that I look at and that's really like the source of truth. We update it every Monday. And it's like, if we're three weeks into the month, it might be like three fourths of the target or if we get more sophisticated, we'll forecast eventually better. But essentially you're saying like, how are you pacing to your monthly target across key metrics? So that would be like, we look at Amazon revenue. We look at our .com revenue broken down by returning revenue, subscription, new revenue, and then new customer revenue. And then we look at like orders on those same basis. We look at AOB and then we look at conversion rate. The other thing that I feel like is really important to look at that we haven't talked at all about, but maybe at the end we can come back to this if there's time, is we also look at our funnel metrics, which you can get from GA4. And I think for when you're thinking about like conversion rate optimization, one of the things that's really powerful is to look at your like, what are called like intra funnel metrics, right? So not just looking at your overall conversion rate. So say, you know, your conversion rate might be 5%, but there's a lot of metrics that you can look at along the way to say like, is this where we should be focusing our efforts on optimizing our website? So that could be like getting people from the homepage to the product page, or getting people from the product page to the checkout, or getting people from checkout to purchase. There's clear benchmarks for each of those steps along the way that you should be looking at. And it might be that like for us, for example, we are focusing our efforts right now on the homepage to product page. That's where we see the biggest opportunity followed by the product page to checkout. Like our checkout to conversion is really strong. And so like, it allows you to kind of prioritize where to focus by looking at like those four steps along the way. We also look at like revenue by channel, we look at landing page conversion rates, we look at subscriptions, right? We didn't talk much about this yet, but like we look at existing new churned subscriptions and subscribers, which allows you to start forecasting like you said, churn rate and things like that. We look at our email rates, like open rates, click rates, revenue. We also look at like overall emails in our database, but we also look at the percentage of emails that you get from new visitors, which I think is an important metric to look at, right? So it's like our 5% or 10% of your customers who are new customers who are visiting actually filling out the pop-up, right? Which is an important metric to track. We look at SMS, we look at paid. So we look at our overall spend by channel. And then we look at like a blended CAC and a blended MER. All of those things you can pull from a mix of Shopify, in-platform metrics and GA4. So I think like that's just an Amazon. Those are like the four places. So I just started with like a tab each month. We have a new tab with our budget and our goals and KPIs for each of those metrics. And then we track week over week and trends. And then the retention dashboard that I mentioned, that's in Tableau. That's more like looking at a cohort analysis. So for a given month, how many customers did you acquire? And then what happens over time to those customers? And so that has things like our customer lifetime value, our customer lifetime revenue versus value, our CAC, our spend, our subscription take rate, I mentioned that. And then retention rates, like percentage of customers that come back each month. So for that, you can basically filter by a host of different things. Like I said, you can filter by partner, you can filter by channel, you can filter by products, you can filter for .com versus Amazon. So a bunch of different ways to kind of like manipulate the data to kind of like, glean insights from in a really powerful way. So. I also think the cohort analysis part is important too, because I think a lot of people look at it and be like, how many people churned this month? And it's not like when they came in and then when do they churn, it's more like how many people churned off this month and they're not looking like, how long do they stay? Where do they stay? All that stuff. So it's good to know like, by like the people who came in March, how long are they staying and when did they churn? And how is that dropping? And then at what point does that like number keep going down to a point that you're retaining most of those people in that cohort, so. And I think like there's ways that you can get early indicators of LTV by looking at like month one, month two, month three retention rates, right? Like by looking at that and your AOV for each of those, you get kind of an idea of like, what will my 12 month LTV look like? What will my six month LTV look like, right? Like it starts giving you kind of like early indicators of how you're trending over time. But more importantly, like identifying how that compares each month is also important, right? Like how does your month one, right? If month zero is acquisition, how does month one compare over time is really important for different cohorts, right? If is that going up, hopefully it is. And then if that's going up, that should have all of your LTV numbers go up. The numbers go up. There's like really like three buckets you could put everybody in. It's like, how many people are we bringing in? Are they converting when we bring them into our world? And then like, are they, are they staying in that world? And then you kind of can go in those. So you can look at the top of the funnel first and be like, what levers can we pull over there too? Cause we can spend more or can we do this? Can we use it to other channel? And if we go down the funnel, we can be like, do we need to optimize. Website, like, like our website, our landing page, our form, our product page, whatever. Even if you go lower, do we have to optimize that checkout process or we had to optimize the email that goes, like, you can kind of like look at the levers once you've identified those things, but like the simplest form have those like three, those three big levers and then find those little levers. And so like you said, you're optimizing homepage to product page, which is like. You could see the biggest lift from that lever. And that's when, once you find that lever and then you can focus on it. Yeah. I think also, unless you're tracking these things, like what you just described, you're not going to know where to start. Right. So I think it's really important to put it down into a sheet. Even if you have to manually pull it yourself, it's, it's a powerful tool. It takes us like 30 to 60 minutes a week to pull that data. But it's like really powerful to everybody that's involved in the, in the management of it, because then you can really start to optimize and, you know, let's say revenue drops and you're like, okay, why, right. This helps you answer like, oh, AOV slipped because, you know, we drove. 50% more new customers last week. Right. And they didn't, they didn't buy like as big of a bundle, you know, they just bought single products. It's like, okay, that, that makes sense. But if you're just like a revenue's down, you're like, oh, like if you don't have the answer, you're just kind of like, you're worried, but you don't know the why. So most answers are there somewhere in the data and that most of which you can just pull from Shopify. I think if you have a subscription business or a business that's based on like a lot of purchases over time, if that's your goal, I do think a retention cohort type of dashboard is really important to also pay attention to. Yeah. I mean, this is bringing me back to like the stagnation days of like how much we had to track, but it works if you know how to do it. So PTSD from those days. No, it's just, it's a good time. It's, it helped me like understand marketing. And I think like, that's the way to understand marketing is like getting the data, understand what, what everything means. Why is it working? How do channels perform? How did conversion rates perform? And then you can, you become a better marketer that way. What does a marketing hill you would die on? I'm a big fan of testing everything. I like the data drive decisions versus I feel like there's a lot of subjectivity in this industry and I think that's okay. But I'm, I'm always a fan of just being very objective and letting, letting, letting the data do the talking. So I'm, I'm a, I'm a huge fan of testing. I think like I will test almost anything. So I think there's like sometimes conflict, there can be conflict within teams when it comes to brand versus more like digital. It's actually like not at all the case at Momentus, which has been really nice because we're all aligned with, we like, we should be testing a lot and we're still very early days of optimizing our experience. So, so far it hasn't been too much conflict, but I've certainly faced that a lot in my career. And I'm like, why don't we just let the data decide, right? I mean, it ends a lot of arguments if you, if sound like, cause then makes like, there's no bad idea. It's just like, yeah, just this test idea. And if it doesn't work, we know. And then we learned and we don't have to do it again. And you figure out the smallest possible tests that you can set up. Obviously you don't want to say like, Hey, let's spend a million dollars like sponsoring like a basketball team. Like that's not a good test. Like it's more like micro tests that you can. Yeah. And, and understanding how you're going to measure it, right. To make sure you, you can, you have a hypothesis and that you get the results back that, that, that have clarity. Otherwise you'll continue to argue. But I think that is generally like, I guess the theme of this, of my career in this space has been like, there's no real failure, right? You're just like constantly testing and iterating and changing and optimizing. So as long as you view digital marketing through that lens, like you really can't get it wrong. It's like you, you should really constantly, there's no, there's no, like I've gotten to this state of like you won or you figured it out. It's like the market's constantly changing. The channels are constantly changing. You have to grow constantly, which is why I like this space and you, anybody can get into it, right? You can kind of like, like I did, right? You just test your way into it. You make mistakes, you figure it out. And then as long as you continue to get better, that's what matters. And there's going to be setbacks and stuff along the way. But I, that's kind of my favorite thing about this world is you can just constantly test and learn and iterate. Yeah, I think plus one about that. I mean, that's what keeps it interesting. It's just a constant testing, reiterating, relearning, unlearning, redoing. But if you don't, if you don't have these methods to do this, like you kind of like get stuck at your old ways and that's where your old ways will eventually catch up to you. Lastly, where can people find you and what you're doing? Oh, probably, you know, I'm not the most active on any platforms, probably mostly because I have my head down operating as much as I can, but probably LinkedIn, I would say the best way, you know, Jordan Narducci, N-A-R-D-U-C-C-I. I'm like pretty, always open to chatting with people, learning, you know, from others. I'm like a huge fan of networking, both digitally and in person. So, yeah, hit me up if this was interesting or if you have learnings or things that you can share, I would love to hear. Well, thank you so much for joining. I really appreciate it. And it's really helpful for people to understand like how people are tracking, how data works, why you should do these type of things. So thank you for breaking it down. Yeah, man, I was happy to. Thanks so much for listening. Tune in next week to hear more great insights from marketing's coolest operators. If you haven't already, please consider subscribing to the Marketing Millennials podcast and giving it a five-star rating. It helps bring more marketers into our community.