Why Revenue Is Up But Profit Isn't Moving: The Unit Economics Blind Spot Most Shopify Brands Have - Misha Druzhinin | Why Revenue Doesn’t Equal Profit, Why Scaling Profit Beats Scaling Revenue, The Hidden Danger Of Discounts (#481)

Speaker 1: I think one of the major things we should believe is like true across multiple brands we're working with is actually nobody owns the margin across multiple folks. I saw literally one group who had like person who was responsible for PNL and contribution margin as like his main day to day job in majority of brands. It's like scattered between different people or CEO himself or themself, literally calculating PNL and of the months if they like it, visit. And that's basically.

Speaker 2: Hello and welcome to another episode of the E-commerce Coffee Break podcast. A lot of Shopify brands are chasing growth right now. More ad spend, more tools, more channels. But the problem is, more revenue doesn't always mean more profit. And that's where many brands get stuck. So how do we actually grow profit and not just topline revenue? To break this down, I'm joined by Misha Druzhinin. He's the co-founder and CEO of Finzi, an AI grows platform built for e-commerce brands. Before Finzi, Michele worked on large scale systems at Datadog and Amazon, handling billions in transactions. Misha, great to have you here. Great to have been here. Klaus, how are you doing? I'm very well. Let's dive right into it. Why do so many Shopify brands struggle to grow profit even when sales are coming in? I think one of the major thing that we should believe is like true across multiple brands we're working with is actually nobody owns a margin across multiple folks. I saw literally one group who had like a person who was responsible for PNL and contribution margin as like his main day to day job in majority of brands. It's like scatter it between different people or CEO himself or themself are literally calculating the PNL end of the month if they like you visit. And that's basically it. And when things go and on average things go and like very differently. Ironically, we literally had like one person who we recently start working with who's like after Black Friday, Conway and like million in sales for Black Friday. And they're like, hey folks, it wasn't like great months. But my bank account doesn't show in it. I need to figure that out. Okay, that's probably the wrong way to do it. And you're quite right. I don't hear it very often that people are focusing on their margins, on their net profit. Mainly they're talking about customer acquisition cost rose and on on these things. So why do you think brands are so close, so focused on Rolex and not on customer quality, on churn and other things? Well, first of all, it's like we don't like to work with Rose, but at the end of the day, it's useful metric. You put some money like you put $1, you get $2 out. It's like easy to think about it. Like what's how to think about this? Like compounding effects and like how like your customer buying from you next time all this field. But like when you're looking at narrow eyes, it's easy to say like, hey, let's have like 2.53 x target and you think it will work out first. And second, I think it's like historical because when you're in like business stuff like sales once. Yeah, it's totally fair to look on Rose. It's cost me to bring the person this like I got this money. But I feel like for Shopify brands for like any DTC customer relationship is actually where you getting money from. And there you like big opportunities laying down. No. Quite right. I think it's sort of people are trained on Roas, specifically when they're spending on paid platforms like Google Ads, meta ads. That's the thing. They're sort of trained for talking about channels. And I want to dive a little bit more in channels and see how the churn is, how you can bring customers back to your store. What's your sign there? What's what's the kind of a warning sign that you are scaling into the wrong direction? Get in the wrong direction. Like for we work a lot, for example with subscription brands and with them like wrong directions, usually cancellation on the first day, on the like on the first week. So you literally grab to a lot of like gamers buttons and phantoms. And for like brands who doesn't have a subscription, it's usually actually like when you discount, when you're like doing like deep discount. And you see like huge spike on it. Your revenue is going up. The literally working with one brand right now who's like, we trained our customer to buy only on discount and so was on purpose and like discount actually drive top line systematically and owners wanted to help top line. It's like I think it's feel good. Like when I have an extra day like, oh, it's feel good. And because of that, like a lot of things under the hood is start breaking up. And when you feel like when you discounted flow discounted audience this proportional to actually like your normal audience that's something you drive inland to like into dangerous territory. Let's put it this way. I totally agree, and I think you gave a very good example that you have so many times a year is like a 7.89 figure store, which is all revenue and basically doesn't tell you the whole story. They might be still making a loss or on a very small margin. Now what I hear from you is data, because that's I think it's the only way to get control over what's really happening in your business. And you built Finzi for a reason. Tell me about it. What does it do? That's the reason come up from basically some level of frustration. Because you like, especially for e-commerce, you have like multiple systems, which is like slice and dicing your workflow, but no one is showing you it like systematically across the board, basically like Google will show you Roas and you are absolutely right. Each platform is literally like scream into your eyes like clay. We will show you something. We'll show you something. Shopify will show you something. And then you have to like, put all these things together. And I consider it it's like, you know, driving some like aircraft where you have a lot of sensors, but most of them is like a bit noisy and a bit full to you. So you have to like, put yourself, this in your head, like what's exactly happened. And that's like basically why we built fancy. Like we wanted to give it to four great product owners and brands to grow faster. And basically not getting into this like dangerous territory. A lot of them about this dangerous territories early before they will get get into it. I think a lot of our listeners can relate to that, that you have a number of dashboards and interesting enough, normally the numbers never match. That's my experience over a couple of years. You look at Google, you look at meta, you look at Shopify, and to expect to have the same numbers and they don't match for various reasons. Now AI is here to help. Tell me how I really can bring you up to the next level. And that is like two different aspects. Feel like heavily leveraged. Okay, for that. First of all, you need some sort of hardcore structure for it. You need the metrics. You need. You don't need the AI to have a metrics. You don't need the AI to calculate, you know, but you need to do it on now on a basic daily basis. You need to see how metrics is driving and where it's going. But together with that, what we now able to unlock is waste amount of qualitative data about your customers. So for example cancellation the reasons reviews feedback like survey forms. We literally have like some folks who like to like pretty big surveys and like, oh cool, you have so much data. Let's dig into it. Let's summarize it. Let's see basically how different people like basically what people who stayed with you for like six months say about you versus people who stayed with you just for months. What does it mean? And that was one of them, like he did. You analyze this data. They're like, yeah, we're collecting it, but we never have time to look into it. Done. And yeah, that's one thing. And another thing we heavily leverage on here right now is the basically help you to focus because as I said, like you have like so many sensors around you. So you literally overwhelmed with the data and the what are we AI is doing it via operators outside of I work for Datadog. I hate dashboards. I need to spend too much time with them. And I using the AI actually to not have the focus is like, hey, this is like three things today. Or it is like three things this week, which is require attention across like all these things because it's maybe like some spike on spike on, customer acquisition cost on method and it's spike across everyone. Don't pay attention to it. But there is like some systematic trend and you need to start paying attention to it. So basically AI becomes terms around a lot AI agent. But I think in that part it becomes really a team member helping you to get the right information in the right moment. What kind of KPIs are you looking at? Are you looking at? I don't know, it's units I it's cuz it's bigger picture. What's the most common numbers that come up? That's actually a good question because now is the AI be able to start looking on unit based. So for example, on school level. And we can work on like profit and customer behavioral on the school level. Or we can start to have a look on like customer journey in the sense like what they buy first. Like what what they stay in for a start start stuff like this. But you know, old style KPIs are still good here. For example, we work a lot on average order value, visit brands and like making it much these acquisition cost. So it's famous about LTV cork. Proportion 3 to 1 at least. But that is like so many ways to drive LTV. So first you can like first what we're doing is literally okay, let's figure out how to get the average order value in the zone where it's not dangerous overall, where it's basically like you're not losing money on the first order or you're losing money, but you're doing it kind of on purpose. So you know that you will have like for example, 2 or 3 purchases and you can afford this. So that's basically like character LTV. It's becoming like paramount in the sense, but it can go in multiple like very different ways. Next is the churn obviously. Like how many people like or second or third purchase depends on the brands. Actually it's like ironically we start seeing more and more people who wasn't like transactional business, who was like sitting on the ones right now driving more and more, subscription revenue. We have a people who have like, for example, KPI to have 20% of subscription revenue for the store. And, yeah. And I would not say this product is like sticky, but customer coming back and, people literally value this. So instead of paying 30 bucks of 60 bucks to meta to get new one, maybe I can pay five bucks as discount or loyalty for my existing customers and they will stay with me. That's a good, good example that you brought that I mean, in the past. And to give a really good example, a lot of brands were betting on basically break even on the first sale and, and hoping that the customer comes back to buy more of which not always happens. And then you're basically just changing money, but you're not making money. If you're using Finzi, what's usually creates the fastest win for a brand, fastest wins is usually like repeatable purchases. It's actually another place where I can, like, supercharge you. Like we influence what we call this retention architecture. But in reality, it's a set of email flows. It's a set of like different email communications, but we doing it on complexity, which like humans, for example, cannot handle in some cases because like brilliant example from actually this week we had like cart abandonment for one brand and it's stopped happening like because the increase ad free shipping threshold and they increase it for shipping threshold because you need the economics was not getting together. So we first figured out this one and then we have trouble vs cart abandonment. So to deal with it we actually built like complicated flow because we don't want to give a discount to everyone, but we want to still give discounts. So for example if person bought from us 2 or 3 times, they already are loyal and we already bought them, so flow become more and more complicated and sounds like, oh, if LTV of a customer overseas, we'll give them this discount. If LTV of customer overseas, we'll give them this discount. And if your buddy and Hunter who did not apply. Yeah. We'll send the email about like hey maybe like you forgot and you need to add more and here's like benefits of a product. But we will not use discount first. And that's how it can be done like dramatically different and faster. As I said, like you getting another employee in your team especially like instead of paying someone, then you can use this money for more like customer acquisition and like increase your growth. So you start getting this famous Amazon flywheel. You start getting more money, you start getting more like your customers. And it's like, basically amplify itself. I definitely can see the synergy effect there from reading the data and then putting it into place. Talk me through how a normal day to day workday was. It looks like. Who's working with Finzi? What are the tasks? How does it look like that's, actually a very good question. We currently have like, actually three personas. What can we see? We can see it, like majority of our customers call it like very comprehensive platform because because we started to use it, we wanted to have like one platform. So people will work with it. And our primary person who work in is, let's say grow manager or grow marketing manager, head of e-commerce. So like someone actually who's responsible for revenue growth and in some cases they literally are responsible in profit growth and they use it differently. They use them, for example, for daily anomaly detection. So like great brands, who's like moving fast actually checking numbers data and the we basically bring in them like Morning Brief. It's like your newspaper. But this newspaper is about like what's happened with your brand yesterday. What went upwards went down. Like how you promotion campaign for Mother's Day will perform, which we already send to people and like basically sometimes like words went not as expected and basically where you need intervention then we deliver on them like more comprehensive overview about business on like weekly monthly basis. So like something for more strategic level. And at the same time we have like functionality for example for email flows, campaigns and understanding and managing meta performance. And like sometimes it's another person for example like a manager or performance ads manager. In some cases we have like literally one man show person who's like growth manager, who running ads, who are running on retention and using sync like across everything. So she's like, oh yeah, I built my mother. They campaign and they put the ads and they look through your system for like how it's performance. And I put two more experiments. So in a time while it's probably would the sound, a bit harsh, but in the time when others still in debate of like brief with the agency, this person already launched everything and already launched three experiment. It makes perfect sense. I want to dive a little bit more in the tech sector because we are talking about different platforms. You're talking about Shopify, we're touching on meta. I'll be talking about Klaviyo. From where do you pull the data and to which kind of platforms can you connect? Our philosophy like we push and we want to put the pull data from everywhere. Like literally every signal we want to have attention. Right now, it's like Shopify. It's clever. It's me at the Google TikTok up live in Falkirk, a couple of brands, and we're also connecting to loyalty program, for example, two surveys and two reviews platform and to support and like these three usually not coming together with numbers. But we see a lot of value is actually like analyzing customer behavioral on the support side and like mapping it out to LTV. And obviously we working a lot with subscription. So like subscription video, your cancellations like all customer behavior which is like becoming important in reality we can derive a lot of this data out of Shopify itself. But subscription videos have this more and last piece, which we start connecting recently. And I'm like really excited about it. We connecting the platform, with providing us demographics data on kind of like more deeper levels than, you would expect it to have. And because of that, we are now able to differentiate, for example, between retired person who is buying the product for like one benefit versus like entrepreneur or person who is buying the same product for like totally different reason they solving the same problem, but it's two different types of people. And now we can see like LTV, we can see like purchase behavior between them, which is really amazing, especially when brand gets in, let's say done like 10 million ish. Like you're not having like one audience. You now having like three, five like different people buying you for different reasons. You like solution. You want solution for different problems. And that's become very interesting because now we can like having this piece. We can like communicate to people why they bought instead of like 20% discount. That's amazing. And it makes me, as a digital marketer, smile, because having demographic and such a graphic data is so valuable. And because usually it happens, you do your surveys, you get some results, and you have a gut feeling who your customer is. But as I said, as you grow, you have more than once and it might change your complete marketing strategy. Once you figure out there's other people buying from you. No, it's really amazing because you can start seeing drift in your audience in real time. Basically, like you start pushing more for like specific type of customers. For example, this like once you she's like, this category is our best customers. She knew it before data showed him. That's his gut feeling is right. She's like, I want to push more. Now you start seeing how like share of this customer growing and like together, you see this will be a long game effect because like we know LTV for this type and we know how it will impact the business. But it's so amazing to see it literally on like day by day basis. It just confirms when you have the right gut feeling. But if you don't have the right at the right feeling, then obviously data helps you to find the right customer. You already gave a couple of examples, but can you share some success stories or case studies of businesses that you have worked with, and what kind of differences they saw in your business? In their business? Well, it's like, you know, each brand is unique in terms of like what friction they have with the customers and stuff like this. For example, for some of brands we saw that's like the email marketing was what can but how they collect it was not working. I like see highlight that is like key you below like benchmarks and expectation for email clicks like again the session which customers on the website and be like hey like let's figure this one. It's like easy fix 20 minutes and it's basically doubled, collection of emails, what we did with them and it's had like very drastic effect on everything else. Because currently now because of that, they have like they sell maybe like 40% out of my list. And that's become amazing. So like a year ago they was like totally on meta in the sense in December they sent pre order for new subscription box, just the email list and was sold out. And the owner was like, hey, they like he we did not expect like before. This launches did not work out for us. But now because we like systematically collect it's like good email list of people we launch it and we sold out. So they was like the probably three of the original expectations of like now we have a traditional problem, but it's good problem to have. Okay. Like yeah, actually we had like couple of brands use the same success story. Basically the operational team was not able to catch up with a grow. So like one brand that likes to systematically treat 20% month over month growth. And they were on the key. It's will be low season. So we're not sure if like it's will work. Kind of like look our data show in this deals. It is a gap we still can share. It's actually a good example of when your gut feeling is wrong, because the gut feeling was based on last year's data and on how they managed it, but in reality, they have pretty big, gap in the market in terms of like what they can push for, like increasing other budget in this case, it feels like graded increase in it. And cock was like there properly together with it. We work out on LTV so we literally discussed with them a key. Now we can afford 35 bucks instead of 25 bucks, and it's moved you to different categories. So you you less competing with others on it. And that's giving you like flywheel. So currently like 20% month over month. They literally twice was like had the operational issue in terms of like we don't have enough supply. We need to like slow down our ads because we cannot deliver like, okay, well if you get it out, yeah, figure it out. And I think this is a problem for another day. But if you have this operational problem in sourcing more products, then that's a like serious problem, to be honest. But I think you gave just a masterclass, a gold nugget away. And I think our listeners need to listen to this podcast, these twice on how you grow your revenue in a way that you can profitable, that you can acquire more customers. So very good idea. Who's your perfect customer? What kind of brands to your work with? What kind of industries? The perfect customer is? Let's say someone who have like product market fit or who's like start actively scaling, who want to grow like 2X3X in the next year. And they usually pretty lean. Team. This team is like they have a brand who have like seven people. Team total for like 25 million operations, which is like amazing if you think about this way. And yeah, they have a couple of functions inside. For example this grow manager. We love this people because they are driving things very fast. They currently some of them quote unquote WIP coding themselves and like rebuilding website or building like a loyalty program, building some gamification to website. So the all new customer experience and we helping them as like some kind of pit crew to move it faster so they can focus on what's important for the customers. So they it's something they focus on, like great product and like machinery around it working. Okay. What points for a typical onboarding process for a new user? What steps involved? How long does it take it to get up and running? Wow. Thank you for asking. Because personally proud about it. It's literally 15 minutes onboarding how we call it. We we was driving for 15 minutes. I know how annoying. And for a brand and bought and when we talked with like multiple of them they're like, oh, you're implementing this system. It's taken us three months and like it's kind of business. We implemented the system like you spend 15 minutes to give us literally access or install like several ups into your store. And basically in next day you already have like 12 months audit report about your business. So we know everything what you already probably know and something which you forgot and we can talk about it. So we have like our x ray and after it we can start working exactly as I mentioned on like what pieces need to be tuned up specifically. And so like where should attention should be spent. Oh that's amazing. Is there any kind of homework that machines need to do before they can get started? Not really. Really. We actually use in how 12 months audit conversation actually do like tuneup with the brand because something sometimes you look in into like, hey, you should do this and say like we're not doing it and it's a decision, oh, we honor this decision. And actually, oh yeah, I've like putting our conversation together because our agents. So that's one of amazing thing I love nowadays because before like you need to tune up your dashboards, change the goals or something. Now we talk can visit brands during onboarding. And we capture everything out of this conversation and we give it to our agents. So now it can drive like recommendation where they want to be. So for example, this I mentioned like one brand to want to grow to 20%. The, subscription revenue. And for them it's more important. That's growth in revenue overall. They want to get they actually want to get less dependent on meta. And that's like higher priority than like growth and top line. That's why we love them. And yeah. Who doesn't want to get less dependent on meta? I think everyone wants to get rid of them, but they're just part of the game. How does your pricing structure work? How do you charge for things? We charge and basically on, and all the revenue level. So based on 12 months revenue levels and currently we starting from like thousand dollars for like smaller brands and going to like two and three for like brands over 50 mediums. And we also for like little brands who let's say have 15,000 monster sales. We working with them as a small growth agency because in reality they don't need grow agency and they don't have like price is not justifiable at this stage. But when we using their agents like we can do the same for fraction of the cost and we can offer them this for fraction of the course. So for smaller brands we actually start working more as like whole platform which helps them to grow. Okay, now that sounds good. Before our coffee break comes to an end today, is there anything you want to share with our listeners that we haven't covered yet? I think they shared that already, but one of like, think I want everyone to think, when you will like thing of this podcast is basically how you growing your LTV higher. You can afford less competition. You get in and that's like new growth cycle. And so instead of like optimizing at AWS, which I know a lot of folks doing, and it's like it's understandable seeing how to push LTV further and get out of competition. So like is it is like currently two categories of people. One who say like, oh, my cock is grow from like 25 to 35 and it's disaster on my unit economics. I kind of long for that. And then I was the one who's like yeah, cool. It's grow to 35. It's not ideal. But we grow our LTV even further. So we're still making money on this customer and we can push this envelope even further. I think it's a very, very important statement that you made there. And I think there's this marketing saying and know probably, but right now it's like the one who can spend the most wins the game somewhere and just got a guideline and was customer lifetime value. Obviously, you're getting there much easier than just focusing on the first sale. Where can people go and find out more about Finzi on our website since we have, demo button there. So like, go go there, click a button to talk with us. We will show you like how it work and like will onboard you. So that's good. I will put the links in the show notes as always. Then just one click away. Misha, thanks so much for giving us an overview about Finzi and how it can help you in your business and to increase your profit margin and your customer lifetime value. And I hope a lot of listeners would reach out to you. Thank you so much. Thank you, as always, because it's for the pleasure.

Speaker 3: Have every.