How To Master Demand Generation

Welcome to the E Commerce Growth Stories podcast. If you worry about your growth, if the business model isn't working anymore, if you're running out of ways to optimize your E commerce, or if you're looking to get the E commerce fundamentals right, then that's the show for you. Hello everyone and welcome to a new edition of the E Commerce Growth Stories. I'm here with Dennis, which this time is in Utah.

Hey, Dennis Utah. Like Dennis Utah.

Right? So in today's episode we're gonna address the demand generation topic which is a burning issue for a lot of e commerce companies as ROAS is down at 2x 2.5x luckily 3x. So how to do demand generation nowadays and how to do demand gener by having customer lifetime value in in mind and why should you do it like, like this? So stick around, let's, let's get the party started. Dennis, what's your, what's your thought about why you should be measuring CLV when you want to do demand generation?

Well, if you look at demand generation when you're generating a lead, some kind of lead magnet, that eventually leads to a product sale and that product sale leads to normally some kind of recurring SaaS, kind of then if you know what percent, if you know what, what percent of the leads become, any of the six categories of customers that we show and reveal based on clv, you know, RFM models that tells us what that lead is worth. So if you do something to increase CLV customer lifetime value by, you know, double because you put in an email sequence or you nurture that customer, that allows you to spend twice as much on the lead. But most people aren't even figuring out what demand gen is worth because they're trying to drive only to the sale. So if you drive straight from cold traffic to the sale, you're going to have all kinds of penalties because of the competition or if you're running ads on social networks, you're going to pay a lot more because your relevant score is lower, your engagement rate is lower. So the people I see doing a really good job, for example Colin Wayne, I talked to him yesterday, he runs Redline Steel, everything that he's now $100 million business. By the way, if you're not a hundred million dollar business, don't think this doesn't apply to you. His whole focus is on demand gen and getting those email addresses say for less than $2 because if he gets it for less than $2, he knows what percentage going to come in and buy on a $2 Tuesday what percent is going to upsell buy to a regular product at $40, $50 and what percent will continue to buy and he knows what his deal is so he can acquire leads all day long say at $2. And so you need to know what that number is. You can't just make up that number.

Yeah. So here Dennison, a very important aspect is if you're not data driven when you want to do demand generation. So if you don't know the CLV and customer lifetime value throughout the time, so you don't know also the payback period. So in how many days or months you are going to compensate the investment to acquire a new customer. You will be very caut with your marketing budget. And let's look at company A which is very cautious with the marketing budget and company B which is data driven. They know that they can spend, I don't know, 2.25x ROAS because the CLV is justifying and the margin is justifying and they will break even in, I don't know, 22 days after acquiring a customer. Company A is not going to acquire market share, is going to acquire only customers very prudently so without actually going the extra mile and without leveraging their marketing budget while company B is going to acquire market share, is going to learn more because the sample size is going to be bigger and is going to raise money and eventually is going to do an exit or whatever, they are not going to raise money but they will afford to get talent within the company because they will have the numbers to justify it. So it's all the way. The outcomes of being data driven are way further down the line than just yeah, you can acquire more customers, but who cares?

Yeah, absolutely. And we have one e commerce player and their customer lifetime value is about $2,500. And we know that we can acquire leads for $20 to $30 because of what the different breakpoints are along the way. And we found the last couple months that their biggest issue was that they weren't converting the leads by nurturing them. They collected an email or they built a retargeting audience but they didn't continue to build that relationship. So of course calculating CLV and knowing how much you can pay for a customer acquisition all the way back to a lead is good, but I think what it really does is expose where you have holes where you need to fix. So how do you know? Is it the landing page or is it the ads? Right. Is it the pricing? Can you afford to pay more? So the Mechanics I find most people are missing because they are ad optimizers. But it takes someone who's the business owner, who has real P and L responsibility to be able to say, you know, we actually have been, you know, we've been acquiring customers a lot less. You know, we've been running at a five row as when really we're okay, we probably could run at a two row as based on what our margins are. Right?

Yeah. And that leads to a lot of problems down the line. I mean, I think the data, the actionable insights can solve a lot of issues in the entrepreneur's life, in the culture as well. Because if you're having a healthy business and if you have healthy margins and if you have a healthy number of new customers that are coming and buying from you, then you can solve a lot of problems because you will not, let's say, be very tight on resources. You will not ask people to do three jobs instead of one. You will not have this multidisciplinary, generally generalists which are not able to leverage on their job because they are focusing on a lot of things. They do email, they do ppc, they do xyz. So I think there are a lot of issues and it's all starting with doing the math. Doing the math, realizing how much you can pay, looking at the customers, doing customer research and understanding which are the best customers that you're after. And of course, another important thing if you do customer value optimization is that the acquisition is going to be informed by these insights. Imagine knowing that your best customers are buying because of X, Y and Z and the main products that they are buying are this, that, and the other. So knowing that your ads are going to be different, your messaging, your narrative is going to be changed and adjusted to acquire your best customers. The alternative is throwing spaghetti on the wall and seeing if, if that will stick. And unfortunately, most of the companies right now are just, let's say, switching to Google Ads instead of Facebook ads without, without noticing that they could leverage Facebook ads. It's not about the channel, it' messaging, the targeting and the offer that, that you're having.

Yep. Amen. And we find it's easier to take a channel that is working or was working than it is to go into a new channel. Way easier. That's what most people are missing. I see guys that do less than $10 million a year. Usually they have one channel that's working well. It's amazing. You know, maybe it's just email or just SEO or ppc and you know, that's all it takes just one channel optimized well. And all the nonsense about Facebook removing data and the cost going up, I see that as a great opportunity to spend more on Facebook because we can optimize better. It's going to flush out the people that don't know how to optimize.

Yeah. At the end of the day, if you look at which are your super consumers, which are the customers that are buying despite all the barriers that you put in front of them, because there's nothing such as perfect company, you have hiccups, you have issues in your customer experience. However, there are some customers which are so pleased about it that they are somehow hypnotized about your brand and about your offering and about your products. And they, they don't care about the small issues because they, they love what you're, what you're selling. So if you go after those customers and help help them verbalize and, and come up with the excerpts from how they explain why they buy your products, those are perfect ads. You can even record them. You can even do this type of creatives because word of mouth is by far the most effective channel on this planet since, I don't know, trade was invented.

Yeah. I was in Orlando last week with our client who sells magnolia trees that you plant when the loved one dies. And they were working as pure SEO and ppc, but now that they're telling stories to the loved ones and then they have one person, their general manager who's been there 25 years, Maria, she speaks Spanish, not her English isn't very good, but telling her story and telling the stories of the people that have been there and how it's creating jobs and how they built a four acre pond in the back so that that way they're saving a billion gallons of water that's being recycled because they want to help the environment. And it, you know, it causes people to want to buy from this company, a family farm versus some gigantic manufacturer or going to Home Depot or Lowe's or whatever to buy a tree. And I find that that's the kind of lead gen that causes people to buy as opposed to the coupons or discounts or things like this. And that particular client, the majority of the sales are coming from referrals.

Yeah.

Because of those stories.

If you also consider that the fact that you can find all those things, I mean, what caused customers to buy from you, I mean the thank you page, you can track things like the channel, the utm. Right. You can track things like what they are saying. If you ask Them what made you buy from us today and where you've heard from us first time. Those things that can be shared can be extrapolated, right? And those can be leveraged because it's now in this moment where tracking is from my perspective, biased, right? At least biased. You need another way to track that. So if you track these things with the zero party data on the thank you page on the post purchase, you can look at statistics afterwards. So you get, let's say, let's say you have 20 customers today or 200 or no matter what, let's say you have a response rate of. I've seen something from 25 to 40% response rate on the thank you page. Because people over there, they've just bought, they've made the conscious decision and you need to diminish the buyer's remorse effect and you need to talk to them, right? So the questions that they have in their heads is instead of asking themselves when this is going to arrive, have I made the right decision? You can go out there and start a conversation with them, hey, have you heard about us? And so on. You can even do video to ask this kind of, kind of questions. We've been using Go Tolstoy. Thanks for the tip, Dennis. To do these things on the E Commerce game, right? And people are actually interacting with the, with the video way more easier than they are interacting with the text because they see that there's a human being over there behind the, behind the business and the website and the nice design. There are actually human beings which are talking to them. And collecting this type of data is going to help you a lot to make data driven decisions. Because if you don't learn, then you are stuck, right? You get, maybe you get some good results, but you don't get great results unless you become smarter.

There's some things that are not immediately obvious with data. You know, I'm a data kind of person too and I would prefer, you know, working spreadsheets and ads and not talk to people and do the creative side. But I'll tell you, the thank you pages I see on most e comm sites are terrible because they feel like, oh, I already got the sale, I don't really need to gather anything more. But the most valuable thing you can do is collect that feedback. Just like you talked about, Valentin, where people, you know, you have the video saying, hey, Valentin here, man, I'm so glad that you purchased. I'd love to hear if you could just say in your own words really quickly, what was it that inspired you Right. And when I was with the Magnolia Farm folks last week in Orlando, because I said we need to collect the customer feedback and put it onto the product pages. And people who bought this product, let's show the other customers and show their feedback. Not just like Mary S and say a sentence or two. Right. That's what most people do with these review plugins. I said we need to actually tell these stories. Right. So he printed out, the owner, printed out a bunch of these emails that people submitted which were great. They said very, very positive things. And I said those are good stories. But wouldn't it be so much better if you got that on video if you had a bunch of little videos along the way? And this is something that just looking at your landing, at your post purchase flows, the data alone is not going to tell you because you have to actually put different content there to be able to then have data to look at. So I see the big failure with a lot of E Comm is not building those stories into post purchase and especially the video stories and then following up with another email or text message a day or two later saying, hey, you know Matt here, I'm so glad that you ordered a new lemon tree. It should be arriving in the next week. But I just wanted to tell you a couple quick tips on how you should take care of your lemon tree so it produces the best fruit for you. Just anyway, 1, 2, 3. Just wanted you to know. Right, that's it.

Yeah. And I think one, one important aspect that we, we also need to take into account is the fact that running the numbers is one thing, but extracting the insights, it's another thing. One of our data analysts here mate, a very good guy and he's so good with the numbers. Back in Q4 they made a really in depth data audit. They've extracted a lot of insights like visitor data, customer data, a lot of things. And his colleagues made a qualitative research on a few customers and at the end when they started to generate insights and ideas to improve that business, he said that all these hours, I've spent 60 hours of data analysis and I got nothing compared to what I found myself in what the real customers were saying. So qualitative research, I think it's really impactful and if you blend it with the quantitative research, that's the most powerful thing. Last week, one of the agencies that were using Reveal, they used this audience builder to do lookalike audiences and we were really excited to see the results. So the thing works like this. We do know for A fact that Facebook is recommending to use the list of the best customers. They say that if you have 1,000 to 50,000 people that bought from you and that you know for sure that they are good customers, you can use them as a seed audience. Because now the Facebook algorithm is affected. We've seen the story with the Q4 being the worst and the Facebook stock going down. So you build audiences based on the best customers. We call them the Soulmates. With the RFM segments, they launched these lookalike campaigns on Facebook with customers that look like the best ones. Then the Facebook algorithm is more powerful because it has other profiles that may not look the same. Before doing this type of affinity research, and then the users are being attracted based on the relevant insights. At the beginning, the agency was kind of threatened because there was a huge difference in terms of the cpc. So the CPC was something like four times higher. But when they looked at the conversion rate, that was 45% higher and the revenue per visitor was at the end, 18% higher. So mainly the ROAS was actually way better than with the normal lookalike audiences. So the idea is not to be afraid to invest, not to be afraid to test out new things, because unless you do this type of advanced things, the other competitors are going to do it because the competition is there, while the inventory, let's be honest, it's not like the inventory of Facebook and Instagram is way less than it used to be. One quarter ago, the drop was something like 0.01% in terms of daily active users, according to their statistics. So there is inventory. The algorithm is not that good. The competitors are trying their best. But if you use your seed audience, your best audience, you will learn more and eventually you will make it, because it's an ongoing optimization process. So you need to think like an experimenter. You need to match the creative with the audiences that you're trying to acquire.

So the higher quality localized convert better. But what about the high quality? The Soulmate that you talked about is a seed audience versus just broad targeting. Have you noticed any differences?

Yeah, the difference is fantastic, man. So there. There is 31% uplift in the conversion rate with the lookalike audience and with the broad audience, it's like the conversion rate was 3.2% with the Soulmates and with the overall Facebook ads was 0.48%. So it was 6.7 times higher than with the broad audiences.

Wow. How about the cost of acquisition on broad versus lookalikes?

The CAC was only. It was something like 22% higher with the Soulmates. So mainly they were making up in terms of the revenue per visitor. And that's why the CAC was 22% higher while the CLV was, the conversion rate was higher. And the CLV, we will track it down the line to see it. Because that's the thing with customer value optimization. You need to track those customers down the line and to draw the line after 2, 3 months, depending on the purchase cycle so that you can consciously say, yeah, that's a better campaign. Now from the early results is clear, that is better because they are making up the CAC from the first acquisition. From the first order.

Yeah. Wow. What have you seen with the other audiences? Maybe just, you know, with vintages along the way.

Yeah. What was interesting is that they could also activate X Lover. So this company is selling sport apparel. So the idea they had was that the lovers, which are so there are the best customers, Soulmates, then the lovers, then the ex lovers. So from all of those RFM segments they made campaigns on all of them. The best ones were for the ex lovers. So in terms of all the metrics, because ex lovers are customers that used to buy from a brand and then something made them stop. Right. So x lovers placed 3, 4, 5, 6 orders on a particular store. But the trick here is that this is highly dependable on the vertical that you are. These guys are selling clothes and shoes. I mean it's clear that at some point you need to dress again, you need to buy new shoes with some pace. Right. The idea is to have the biggest share of wallet for the vertical that you are in if you would be selling low frequency items. Right. Like I don't know, whities or mattresses or whatever, that magnolia thing there. It's all a game of making up from the first order and leveraging the word of mouth from your existing customers. So it's acquisition and amplification is the game where the purchase frequency is lower. Where the purchase frequency is higher, customer lifetime value retention and amplification. Word of mouth are the key there. Right. Because if you leverage those, you'll be in a good position to acquire better customers and to increase your marketing budget.

Have you seen any sort of averages or benchmarks for demand gen? Maybe by industry or overall or trends?

Yeah, in the demand gen I don't have too much access on a lot of data, have things regarding to the post purchase. But hopefully we're getting there because we're working on this crazy project to ingest data from ad sources. So at this moment, what I do know it's on a limited amount of customers. We've seen the drops in terms of roas, something like two times. Is two times worse than it used to be in the summer. In terms of Rosa, how much that.

Do you think is just data being missing versus actual drops?

I can't say for sure. I mean I do know for sure that 8 out of 10 customers, companies have their data tracking messed up completely. I do know that because we look in Google Analytics, we look at how they define a visit. We look at the fact that they are not ignoring certain things of that they are doing. Just a second. I just, I just got a smoothie.

Oh, smoothie.

Yeah, that, that's, that's the, that's one of the perk to be, to be. To having a great wife. Right.

Who works in the office two floors below you.

Yeah, exactly.

Fantastic. Well, I always love spending time with you. And you had to get up early, right? Is it 8 o'?

Clock? Yeah, yeah, it's 8 o' clock now. But the, the first, the first, the first call was on at 6am so we.

Oh wow. Who's doing the 6am calls? Australia. Australia.

It was 4pm or something like that there.

I would love to record a bunch of sequences for our e commerce game, but I still need a couple days to put some of these things together. Yeah, very excited about that. And everyone else who's watching, we're working on an incredible choose your own adventure. I think you guys will love it.

Yeah, we're tweaking now the data and this is going to be a great project. It's actually one of the most exciting projects that I've worked so far because it's really personalized, but it's mass personalized.

Yeah. And any of you guys that are watching, we want to tap into your brain. We want to know what are the things that you guys are observing in your data? Rules that you use to optimize things that you know that could be based on an if then statement. And I want you to tell Valentin and I so we can put it into the system. And these are rules that we can use just for your data or just general rules that will scan across data and be able to then make recommendations. Like a check engine light. Right. Are there certain things maybe set them up in, you know, Facebook with the, with advanced rules or other kinds of logic or you set up inside Google where you're looking for certain thresholds or alerts. Let us know about what those things are. You don't have to tell us what the exact number is, but the kinds of things that you're looking for. And then we'll give you access to the dashboard that will find out when those thresholds are triggered and then tell people what to do about it. So imagine it's not just alerting people but telling people, here's what you need to do. This is the tool we think that's going to help everybody in E Commerce improve. Imagine it's like having Valentin on your shoulder looking at your data. What would that be like? Looking for mistakes, looking for opportunities.

Yeah. To give a bit more context about the project. So imagine that we are flooded with a lot of data. We are looking at some particular insights but we are trapped by the medium that we're using. We look at the customer behavior, then we look at Facebook ads, then we look at Google Analytics, then we look at Google Ads. Mainly we are looking over there, but we don't have an overview. Also the human brain can't prioritize that well. And that's why we want to aggregate this data. We want to ingest a lot of data from these various sources and then according to the impact, to come up with recommendation based on the anomalies that we're seeing over there. Because as I've said earlier, for a company which has a low purchase frequency because the vertical is like that, it doesn't matter too much to focus on improving things like customer retention or customer lifetime value while it's more important to focus on acquisition and on nailing the CPC or roas. So according to this type of customers of companies, we're going to come up with recommendations.

Amen. I'm excited. And with E Commerce and any other performance driven, web driven thing, there's so much data that we can look at different. It's easy to look at the same charts every week and miss one particular kind of filter or grouping because you know, you think I can look at, you know, the email channel four or last week for this product, buy this, buy that on this particular metric. And so you have a needle in a haystack problem. So we want to do is eliminate that issue and have the system scan for you and look for things. That's what I think will be incredible. And it's not something that Google Analytics is doing. I've been looking at Google Analytics for 20 years. A lot of my people went to Google's team over 20 years ago and they never built analytics. In fact, I don't believe anybody in the industry has yet built analytics. They built reports. But analytics is thresholds which require understanding what your goals are. So imagine if the system doesn't know what your ROAS or LTV or the ratios you need to have, then it has no way of being able to notify you. If the system doesn't know your industry, if the system doesn't know what you expect to have, you have to explicitly tell it, then it can't watch out for you and help you optimize.

Yeah, and one important aspect which is being neglected a lot is the fact that Google Analytics and Facebook ads, and Google Ads, they don't know your gross margin, they don't know where is profitable for you. But you know that, right? The problem is that you have so much data and most of the e commerce leaders are being trapped in their day by day things, you know, they don't have the time to get a few steps back and to see the bird view and to come up with the insights. So our intention is to do exactly that. So to ingest this type of data, we do know that the levers of e commerce growth are clear. So you need traffic, you need conversion rate, you need purchase frequency, you need average order value, you need customer retention, you need customer acquisition costs. So how much you spend and customer lifetime value and of course the relations between them. Because if you have, you are seeing, hey, that's great, your customer acquisition cost is going down. Congrats. Yeah, but if customer lifetime value is going down as well, that's not so great news maybe. And it's not about how much you spend, but how much you manage to keep from a customer. Because if you're profitable for after you acquire a customer, then that's great. And the trap is that you think that you should be profitable with every order at every touch point. But that's not the case anymore. The idea is to be profitable down the line and to invest maybe for a few weeks or a few months because you know that you are increasing the chances for the customer to come back and make up for the that you've specified.

Yeah, Amen. Increasing the payback period instead of one day, maybe make it a couple months if your business can sustain that and then you can mix in these other channels. I'm excited to talk about TikTok ads and what the metrics look like for that. But we still need a few more weeks to gather more data before we can say more.

Yeah, it's a fantastic channel. I've seen that Facebook is migrating to short form video as well. I think the game is on. I mean we thought if you think It. Well, Dennis, two years ago we thought that this is it, that social media there is the king and all those things will stay like this. But surprise, surprise.

And even Perry Marshall, who wrote the number one book on Google Ads and the number one book on Facebook ads, he and I had talked a year and a half ago and I said, you know, time is right for the book on TikTok ads. So we've written the book, we just have not. It's still in editing, so we're going to publish it soon. Wow, that's exciting to share. I'll give you the summary. It's taking what was working on Facebook and making fresher 15 second videos. Right. Instead of relying upon images or carousels or longer videos, it's all about quick, short videos that do not look like the professional. And that's making all the difference because the cost of the Traffic is 1/5 and the algorithm is smarter and there's a stronger organic component. And we can boost what our best customers or influencers or other people have. We can boost off of their accounts, which right now is possible on Facebook and Instagram via the branded content tool. But most people aren't doing that. So we've been testing different techniques where you have a great customer and they talk about how they like the sleep mask, then you can boost their post from their account. It's called Spark ad. And that behaves completely differently than from the brand itself. So TikTok is just going all out on influencers or creators. And Facebook's never really made that switch because they haven't put the money in to reward these creators, which is the new term for influencer. And the traffic's so good, the algorithm, so smart. TikTok is a video first platform and Facebook has not been. So we'll see what happens with that shift.

Yeah, it's incredibly impactful at this moment. And I think that one of the most impactful things from TikTok is that they are leveraging the fact that the attention span is going down and the younger audience, which are digital natives, they are just looking at this, looking at that swiping. I'm looking at my, my daughter as well. And she's there, you know, I mean she can be, it's not like she's not present, but she already have it ingrained to do this type of gestures and the way that you are consuming content, that we are consuming content because we are not digital natives. Right. We are seeing this. It's a separate world. Yeah, yeah. I'm not saying that we're Old. I'm saying that we're different and we behave different because at the end of the day, these generations are going to become the new normal at some point and we're gonna look behind and we're gonna say, oh, back in The, I don't know, 90s when we are using Sony Walkmans on the street. Yeah. Dennis, I want to ask you something regarding the, the budgeting. So how would you plan if you would be teleported into an E commerce brand and they've said our Roas is a mess, we're not making it happen. How would you budget, how would you invest right now to make that company thrive?

Well, first we need to know what is the, the minimum ROAS we can accept and still be break even. And I would adjust the main winning campaign to that roas because I've seen really large and really small accounts and usually there's just one or two creatives that do really well and they're often under budgeted or over budgeted or they have losers that we need to kill. Right. So the first thing is just adjusting, like we talked about before, to what is that roas based on what we know the LTV and CAC is. And often it's random. So if you don't feed the right signal and if you just do automatic bidding or if you're manually bidding to a CAC or ROAS that isn't, it needs to be like one penny above break even. Especially if it's on Facebook or whatever where you know you're losing 30% of the data. So often cases we see with ROAS with Ecom with of 1 ROAS, which is unprofitable because assuming your product is free, even a 1 roas is actually okay because we have this word of mouth effect and we have the other data that's just not coming through. So just the simplest thing that we can do is just figure out bidding, budgeting balances for the number one, the winning. There's always one winning creative. I wouldn't go and just create lots and lots of new campaigns or create lots of new targets or create lot. That's I think, the rookie mistake. But anytime you come in, the first thing is I need to zero in on that one ad, that one campaign that's doing well. See, can we spend more against it? And then from there, see, okay, how far off are we? So maybe if you know, the owner says or we agree that it needs to be at least a 2 roas because of our cost of operating material costs, it depends on what the product is right. Some products have a really big market, but we're actually at a 1.2. Well, you know, then we're gonna have to look at it a little bit differently. But if we're actually operating to three and we only need to be to two, we have a lot more room because we can basically bid up. So those are two completely situations where we're not even making the minimum roas or we're above what we know we could actually do. Then it's a matter of, okay, is it content or is it something on, on the customer lifetime where we can pay more? It used to be content and targeting used to be like if the campaigns were performing, change the targeting or change the content and one of the two, the intersections of relevancy. But it's not the case so much anymore. At least on social, I mean Facebook or I mean Google, you have the direct intent with the keyword and then, you know, different kinds of match types. But, or display. But especially on Facebook, increasingly the targeting doesn't matter as much. So really it's about the creative and how we can build this journey and pay the most for those particular customers. And I've audited so many accounts and every time, the number one issue is they don't have the creative that we can, we can rearrange the targets and campaign structures. But if you don't have interesting vertical creative featuring your customers that looks authentic, that's entertaining. Even if you have customers that are over 30.

Right.

People think, oh, this is just for kids. No, it's the same thing. Right. I'm 47 and I spend time scrolling through Instagram and whatnot. I want to see things that are entertaining. Right. I'm going to go in there and I say just two minutes. And then pretty soon I spent 40 minutes looking at these things. Right. And I'm sure you have too, if you're willing to be honest.

Yeah.

So there's the adjustment of roas and all that, but it's increasingly the issues of the creative. Right?

Yeah. I think one important aspect here regarding the ad strategy and the demand generation strategy is that I recently had a conversation with the CFO of a company. He was arguing that customer lifetime value should be measured for first time customers and for returning customers. And I was not agreeing because at the end of the day all the repeat customers were at some point first time customers. So basically it's like judging if the mother of Michael Jordan hasn't anything to do with the success of Michael Jordan. Right. So mainly it's first time, second time, third time purchase. And that's why CLV should be measured for all the customers and shouldn't be measured in a financial way because the financial way looks at, at months while you should be looking at the total lifespan. Right?

Yeah.

This particular assumption was regarding the fact that customer lifetime value is like this. You have a third of your customers from a month are going to buy again in the next month. So the customer lifespan according to this assumption was only three months, while the reality was that was two years. So the mind also. Yeah, huge difference because eventually with our real data set, looking at particular customers, I mean real customers and their customer behavior, not in a financial way where you look only at numbers and not real individuals. The difference was that we were saying that we were seeing that the customer lifetime value was around $300 and they thought that is 130 huge difference because that means they've informed the company not to, not to spend that much on the, on acquiring a customer. Which is crazy. And that's why you need to be really, let's say literate about what customer lifetime value is so that you can rely on it. Because garbage in, garbage out. If you, if you don't have reliable data, you're not going to make it. And another important aspect is that you can look at customer lifetime value retroactively based on the products or the brands that they've bought that your customers bought and see if there are anomalies. Or you can look at the customer lifetime value. Let me give you an example. A shoes retailer, they realized that their CLV was 60% higher in smaller cities than it was in bigger cities because there weren't shopping malls over there. I mean, the explanation was pretty simple. But you need to look at the data because when you compare the revenue coming from, I don't know, New York or San Francisco with the one coming from, I don't know, small city, smaller city, you think that you need to go to New York. Right. And San Francisco, but there the competition is higher and your CLV is actually lower. And that is not justifying to double down on acquiring customers from New York if you compare them to, I don't know, Denver.

Yeah. Smart segmentation. Who would have known? Right. The averages lie. Average everything out.

Yeah. And you need same thing for cohorts. Yeah. You need to take into account these lows. Right. Where you need to go deeper. You know, you don't need to stay shallow and to rely only on the averages. And that's it. So CLV needs to be segmented by brand, by channel, by the purpose of buying. Right. What's the reason that you wanted to buy from us today? X, Y or Z? Are there any differences if the customers are buying because of Z against X? And if there are, then you can acquire more, you can push more on the ads which are on this narrative, on the X narrative. So these are tweaks that you need to do. And again, now the job is multidisciplinary, right? So if you're an E commerce leader, you need to take into account things like customer research, because the one which is closer to the customer wins. You need to take into account data analysis, you need to take into account email sequences. Right. While email is actually a fantastic channel to boost profitability.

Amen. Mic drop.

Yeah. So, Denis, what else do you want to cover in our today's session? What haven't we addressed and you think it's important for E commerce people watching us today?

I have new topics that are not quite ready, so I'd like to keep these things shorter if we can. If we can keep it at 30 minutes. You know, maybe some people, for some reason they want to keep meetings at one hour, but I think, I think we can be punch here and do it in 30 minutes.

Let's do that.

Yeah, let's do that. Perfect. Time back.

So, everyone, today we talked about demand generation, how you use clv. If you have any questions for us, let us know. You can find out on. Find us on Twitter, on LinkedIn. And that was it. See you next time at the E Commerce growth stories.

See you guys.