If You Don't Understand Data, You Don't Understand Email Marketing

0:00If you don't understand your data, you don't understand email marketing. And you end up like 99% of brands who just look at open rates, click [music] rates, and how much revenue Claio is making for you, completely blind to the actual bottlenecks that are holding [music] back their email and holding back the amount of profit you can make each month. And if you don't know what to do and you start panicking, you just start sending more emails, changing creative to unproven formats, and just throwing around discounts, hoping that the revenue will come back and follow. But we actually have brands where we've taken them from $200,000 a month in

0:27email revenue to $400,000 a month, not by increasing the amount of discounts that we're using and not by dramatically increasing the amount of emails that we're sending. The difference came from understanding the numbers behind their business that everyone tends to ignore, which allowed us to exactly understand why customers are buying and when. And we've done this across over 300 brands at our agency, WellCopy, where we manage email and SMS [music] for seven to nine figure brands. So, in this video, I'm going to show you every piece of data that moves the needle and what I look at and in what order. Starting with why I

0:56don't immediately start changing emails. When a brand isn't making that much money from email, usually their first reaction is to change up all their emails. Maybe we need to send more. Maybe we need to update the designs. Maybe the copy could be better. Then, when that doesn't work quickly enough, they just start spamming discounts. Now, obviously, if you start giving somebody 20% instead of 10%, you're going to get more sales. But you're doing that at the sacrifice of profit. And that's not really telling you the core reason why people would buy more. We've had many instances where we've dropped the amount of discounts we send and we dropped the

1:25number of emails that we send for a brand and their revenue and contribution margin aka profit go up because usually these problems have very little to do with email themselves. Prime time to hit a customer with replenishment emails might be on day 14 instead of what you're doing on day 45. You might be trying to cross-ell a product that customers are not buying or you might be giving a discount to customers who are already going to come back and didn't need it. You can't work that out just by looking at open rates. So the first thing you need to do is you need to understand your brand in the broader

1:52metrics and when and why people are actually buying. Let's break down those broader metrics that you need to know and track for your brand. The first thing I want to know is how many customers are coming back and what percentage of my revenue is coming from repeat orders. So if you go over to Shopify and you go over to reports, you can pull up some really nice reports here to give you a sense of what the data is telling you. So, some of the base ones that I like to look at are new versus returning customers, returning customer rate over time, new versus returning customer sales, and customer

2:20cohort analysis. So, if we look at this past 30 days for this brand, we can see right here new customers versus returning customers. We can see here that we're about 85% new customers compared to returning, which definitely means that we are heavy on the acquisition side. We can see here in this next graph the returning customer

2:37rate right here, which is about 15%. meaning 15% of people who buy from us will come back and buy again. You can see again, you can get another sense of it looking at the revenue side of things, the new customer revenue versus returning customer revenue. And so I highly recommend you pull that up and understand how many of your customers are buying. Usually for brands that are one-time products, like this brand is an accessory brand. Accessories and clothing, 15% is definitely low. This

3:02brand actually used to be at around 10%. If you're an accessory brand with good customer retention, then you want to be at around 20 to 30%. Whereas, if you are a CPG, consumable brand or supplement brand, you want to be up towards 40 to 60%. If you're below 40%, then you probably have a problem. To get a little bit more insight on this data, we can look at the customer cohort analysis tab right here. Now, this is a very important tab to look at because what this is showing us is how many customers we acquired in these given months and how many customers from that cohort

3:33placed another order in these following months. So, for example, this January 2026 cohort, what this graph is telling us is that we got 19,000 new customers and about 5.75% of them bought again in month zero, which is January. And then you have 1.48% 48% who bought again in month 1 and 74 and so on and so on. And my favorite here to look at is amount spent per customer. So this is giving you essentially your LTV and you can track it over time how much your customers are worth. Now this is a low repeat order brand. So you see month zero a customer

4:09is worth $112 and then by month 11 $121. So about a 10% increase. This lets you track how cohorts mature as well and if your retention efforts are going well. So, like we could see for this brand, their month zero retention rate, so how many customers bought again in the same month, jumped from around 5% to consistently above 8%. And month one jumped from kind of like in the ones to then consistently being high ones in twos. And of course, that was after we looked at this data and implemented these changes, which would be timing the customer repeat orders, upgrading our campaign content and emails, doubling

4:45down on SMS, and having a ton of new product releases. We can see right here that our repeat customers for this brand has actually gone up from 5.4% to 11.9% which is massive. A double in repeat customer rate over the past 12 months since we've been working with them. All because we understand this data. So understanding our repeat customer rate and the sales and the amount of sales that are coming from our repeat orders versus new customers is incredibly important. The next thing that I like to

5:10understand is the time between orders. When are customers actually placing new orders? And this is the one thing that most brands and most agencies have no idea about. So that's why we built WellTV, which is our custom retention analytics platform, where essentially we built all this to track all this for our brands. One of my favorite things to look at is this time between orders tab right here. This is going to show us when somebody places an order, when do they place their next order. And we can filter it by maybe first to second order if we want to do that. And we can also filter by what product was the first

5:43product that they bought. We could see right here if I go to first to second order, this is what this curve looks like in the first 90 days. I can even extend this out to the first 180 days right here. And just look at how heavy the repeat order range is in this day 10 to 16 window. And you see just how big this jump is as well, right when they first initially placed that order. This is an accessories brand and they were thinking people aren't going to buy multiple of this product within a certain window. They're going to try it and we'll hit them again with messaging

6:12at day, you know, 21 to 30. But look at this. By day 22, 50% of all the repeat orders within the first 180 days have already happened by day 23. So what we know then is when somebody places an order, we need to go aggressive in this time period. You are the hot new brand on the block. You're the exciting new brand. And this is where you hit them with messaging. And just by changing when we send our messages, that will have much bigger of an impact on your repeat order rate and your email marketing performance than adjusting some subject lines. And so that is typical for accessories and clothing

6:46brands. Within that first 21 days, you have that massive spike in repeat orders. With CPG and supplement brands, it's a little bit different. Now, what I've done is I've excluded subscription because if we look at repeat orders with subscription, then you get a ton of orders on day 30. But we go to organic and we can see just how that period evolves. What's super interesting is compared with clothing and accessories, there's really low repeat orders in the first few days until the customer gets the product on like day seven. They're not buying at a super high rate cuz they haven't tried the product. They don't know what the taste is like. But right

7:19when the customer gets the product and they're starting to like it, they're going to go stock up. So you see this massive increase in surge until days 35, which this brand sells roughly a 30day supply. In this brand's messaging, they weren't sending emails until day 40, but they were missing out on adding fuel to the fire in this period. You can see

7:38it's already decreasing a ton by day 40. 50% of the repeat orders in the 180day period had already passed. So this is incredible insight that you need to know as you're building out your messaging. You can see the jumps that we were able to make for this brand comparing the repeat customer repurchase rate just by making a couple changes about 15 to 20% increases in the repeat customer rate of

7:5830, 60, and 90 days within that period. And these cohorts haven't had time to mature on the 180 days. So right now it shows this, but it's going to be much higher. You can see the data still maturing right here. So I want to understand when a customer buys one product, what do they buy next? So that's where we can look at our product journey right here. And you could use AI to help you put together some of this with your data. But this brand, for example, they were trying to cross-ell people who bought pants to go buy shorts and trying to cross-ell different products. But I'm able to look at this

8:26data and be like, look at people who bought joggers. We can see that the people who bought joggers, what did they buy next? 158 of them bought joggers again versus 61 of them bought shorts, 36 went to sweatshirts, 52 went to short sleeves. So, we could see that our most valuable cross-ell or upsell we could do is selling the same product. When somebody proves that they like joggers, they like joggers and you can sell them different colorways. But not every brand is like this. Some of them cross-ell

8:54really, really well into other products. This is often the case that we see. So, we know what our messaging is going to be. What do you think is going to get somebody to convert better? An email promoting the product that the customer wants or a random product that you're trying to predict they will cross-ell into. That's why you need to understand this as well. Now, if you want access to this software and you want a team who's actually looking at this data to create strategies for you, we'll do an audit of your setup using this technology. build your email and SMS strategies that you won't be able to get elsewhere. Link's

9:19going to be below to book a call with us. So, now that I've looked at sort of the store's broad metrics and the customer behavior, now we can actually look at our email and SMS marketing platforms and understand the data here. So, let's get into it. The first thing that you need to make sure you know when you're looking at your account is what your attribution settings are. Cuz if you're looking online and you're seeing like, hey, you should be at 30 to 50% of your total store revenue from email and SMS. and you look at your data and you're at 15%, you might freak out, but

9:48it all just depends on what your attribution settings are. So, if you go over here to attribution, you can see where your account is currently at for attribution. And so, for this account, it says anybody who has opened in the last 5 days or clicked an email in the last 5 days and they happen to make a sale, that email is going to get attributed with that sale and it's going to be marked as revenue generated. and then text message. If anybody has delivered an SMS and they place an order within 12 hours or if anybody clicked that SMS and they buy within five days, it's going to count. And this is the

10:17general attribution settings that Claio gives and what most people are looking at. You can see obviously it's quite generous. So, it's up to you on how you want to look at your attribution, but it really does change the numbers that we're targeting. If you want lastclick attribution, like somebody bought directly from this, you would do clicked

10:34one day email and clicked one day SMS. But the standard that most people use and when they're talking about a lot of these metrics is they are using 5day open, 5day clicks. So just for the sake of comparing apples to apples, I'm going to use that for most of it. So let's take a look at this brand and what are the numbers that I'm looking for in the benchmarks that I want with these attribution settings. So we can see right here that in the past 30 days they've done $164,000 in total revenue

10:59and 51,000 coming from email and SMS. And this is an accessories brand as well. Now, typically for accessories brands, what I like to see and shoot for is around 40% from email and SMS with these attribution settings. So, I know right off the bat, okay, we're a little bit low. Let's take a look a little bit deeper at some of the data. And what I see here is campaigns sitting at 33% of that revenue at 17,000 and 66% comes from flows. And we see that 24,000 of that 33,000 just comes from this welcome series. The other thing that we see is that email makes up 95% of this compared

11:35to SMS at 5%. Now, just based off of my experience, I have a ton of alarm bells going off here. 31% is definitely low. It's interesting seeing 33% coming from campaigns. Usually, we like this to be around 50/50 for an accessories brand of an average sort of like regular sort of AOV oftent times. And then email and SMS depends on the brand again, of course, but I like to have this SMS be at least 20%. So, I have these alarm bells going off and I'm like, "Okay, there are probably a few simple levers that we can pull because they're likely underutilizing campaigns or not doing them correctly and they are

12:10underutilizing SMS." Now, this is of course going to depend brand. That's why you need to have experience and why I highly recommend getting audits from experts to let you know and have experience. It does differ. And so, how would I tackle this account? First, I would look at campaigns. And what we see right off the bat is how often they're sending. We have SMS right here. three SMS in the past month and 1 2 3 4 five

12:34six email campaigns in the past month. So when I'm looking at these numbers, you have to understand why they are so low. So this one, it's so low at only 33% of the store's revenue because they're not sending email campaigns three to four times per week, which we recommend. Now, if they were sending emails three to four times per week to their list and the revenue was still low, then I'd actually look deeper at who are we sending to and what the content is. But really, all that we'd do, taking this over, is we just double

13:00the amount of emails that we're sending. And that right there is going to get them to the 40% attribution mark. And that right there is probably going to 50% to 100% increase in their campaign performance. And so we'd do that on email. And then SMS, we would double this to two SMS per week. And we would get their own performance. And now when I'm looking at SMS, it's still a bit low. You know, 5% from SMS, and they sent three campaigns. Let's double the amount that we're sending. It still would probably be low. So let's take a look at our flows. When we look at our

13:27top revenue generating flows right here, I can see with this little icon that we do not have any SMS flows. So that's going to be our biggest bottleneck right there for this brand in terms of SMS revenue. We just literally are not sending any automated flows. And so implementing that is going to get us up there in terms of revenue. So just by having benchmarks on this data and understanding what goes behind it, I really have not clicked into any specific emails, none of that. I haven't looked at subject lines, nothing. and I'm already very confident that I would get this to 40 to 50% plus of their

13:59total store revenue. But let's look a little bit further and get you some more benchmarks to look at. First, let's go to our signup forms. The biggest thing I like to see is our mobile opt-in rates on our pop-up form. And right here, we're sitting at 6%. Now, in general, we want to be at 10% plus of people who see our form to opt in. There's going to be a little variance brand to brand, but I always like to verify once I look at the creative as well. And after looking at the creative of this brand, it's just a standard pop-up form that asks for

14:24somebody's email for a secret discount. And there's no sort of engagement first with anybody. And that's usually not converting nearly as well as if you use a sort of gamified pop-up experience. So if we go to Alia Pop-Up's website, they have a ton of examples of what these forms should look like. And these are the sort of pop-up forms that work the best. You ask some sort of question

14:44before you ask somebody for their email. like this. This isn't going to convert as well as something like this where you engage with the customer first. It seems low barrier to entry. They answer this question for 15% off and then you ask for email like this. The form I'm reviewing just asks for this right here. So, boom. Right there. I know I'm going to be getting 50 to 100% list growth on this brand. Let's go within our flows now. Now, we could see we're pretty much majority of the welcome flow. $24,000 and then the rest of the flow is making very little. Now, that's not necessarily

15:12a problem. This is often the case for a lot of our brands because if you have a really good pop-up form in a strong offer, then this is going to happen. So, it doesn't particularly jump out at me as something that's too big of an issue. But, I just want to go through these emails and take a look at the conversions and where we stand with all of these and what the performance is like. But something first that's very important that I like to track as well is when people opt into our email list, what percent of them actually buy? And so, just real quick going through some

15:39of these numbers for the welcome series. We typically want this to be around 10% conversions. And if we look at this right here, we have 6.8% of people convert right there. We have 4.3 right here as well. And you can see the rest of these emails, 0.1, 0.1, 0.5, 0.3. And so we actually do cross that mark. And so that's a good benchmark and threshold to look at initially. When we look at checkout abandon, typically right here, I like to be at 5 to 6% plus. When I look at the conversions here, we're at 1.5, 0.8, and 0.7. So, we're converting at half what we should be here. So, I

16:13know that I am going to focus on this. So, if you're auditing with me, shoot for that 6% mark. If there's anything lower, then you know you have some big issues. That's not to mean if you're at 6%, you're all good. It varies brand to brand. And that's why you need an expert to kind of like review your account and give you that sort of insight. And when we look at Carter Bandon, we're at 0.8, 0.9, and then 0.4. And so, for Carter Bandon, I like to be at least 4 to 6% as well. And we're falling below the mark here as well. So those are specific

16:41numbers that you should have and you should be considering as you are reviewing your flow analysis is those abandonment conversions. Last one here is browse abandon. I like to be at at least 3%. It looks like right here they're kind of almostish there kind of at like 2.2%. They're getting there but not there. So I know looking at this account the welcome flow seems to actually be pretty solid but it's the abandonments that are leaving revenue on the table. They've only got three emails per abandonment. They're all below KPI on conversions and there's likely a lot of upgrades and messaging that we could do. Taking into consideration earlier

17:14what we found about repeat orders for accessory brands where it's super heavy within the first 30 days. We can look at the first purchase flow right here. Take a look at this. They wait 1 day, they wait 2 days, and they have the sale message. And then they wait 7 days. But this email is not even on. They just have two emails in this period and only 0.2 and 0.4% placed order rates. So that is very very low and I know right here based on looking at the data that they are leaving significant amount of money on the table. Now I'd like to have a 5%

17:45plus placed order rate in this post-purchase sequence and so we're well below that just because we're not sending and we don't understand our data right here. So that again is a large lever. So hopefully that gives you some insight on flows and overall account performance. The last little bit we're going to touch on is deliverability and where we want to be with our engagement metrics. You can go to this deliverability tab inside of Clavio and get a sense of your deliverability score and what your core metrics are. And they give you some base sort of standard metrics to go after. I don't agree with any of these and so I don't think you

18:17should really put too much weight into this, but here's my take on where your opens, clicks, unsubs, spam, bounces, and everything should be. Open rates, I don't want anything lower than 50%. So, this is good to see right here. If we're at like 40% that can be okay, but 33% is way too low. We want to be at 50% plus. And the way that you impact that is just by sending to tighter lists on your campaigns. So right here they got 44% opens, but they're generally getting above 50%. So that's okay. We're in a decent spot there. Click rate 1.78%. I

18:48don't care too much about click rates. As long as you're not below 0.2% and you're just blasting to a ton of profiles that are unengaged, you're going to be fine. Clicks don't have a massive massive impact on deliverability. The biggest impact on deliverability, it's going to be open rates or people opening your emails and also spam complaint rates. For spam, you

19:06want to be at lower than 0.03%. You can see right here at 0.01, that's a good place to be. And you can even look at recent campaigns that may need attention. And you can see like for example where your spam complaint rates are and where you might need to pay attention. Even on the flows, I can look at spam complaints. I read 0.05 05 on the welcome flow, but across the whole account, we're in a decent place. You might be able to pinpoint specific emails that are causing spam for you so that you could tone them down a little bit, but overall that's okay. You can

19:34see Claio and how they say like poor poor and all these poor metrics like 0.4, 0.57. I don't agree with that. And so, I really wouldn't look at that too much. I just want to make sure my opens are good, my clicks aren't astronomically low, like 0.1%, then maybe I want to look at that. And my spam complaint rates aren't above 0.03 03 to 5% and then unsubs at like 0.3 to 0.5% is fine and bounces below 1% is fine as well. So you can get a sense of that and where you want to be and if any of those numbers do look out of whack then you need to know your numbers

20:05and you need to adjust this. Now there are a lot more nuances on data and knowing your data such as even like if you're a subscription brand there are massive differences if you're a subscription brand and how you look at your data. So, if we look at this brand for example, sitting at 20% of total store revenue coming from email and SMS, that looks a bit out of whack. And you're like, "Wow, that's low performance." But we don't take into consideration the rebuilds. So, this brand's a subscription brand. So, you have people who just are doing nothing and getting rebuild on their subscription, which is taking up this

20:35revenue that's not getting attributed to email because we're not sending active subscribers emails. So, that makes these numbers look a lot worse. And so if we use our custom metric right here of placing order without rebels, we see just how much this drops. We can see that email then makes up this 36% share right here and campaigns and flows are at a more healthy split. So that's where you really need to understand your data and most brands have no understanding of this and the nuances that come into play. Now I teach all of this inside of my school community as well. You can see an attribution question right here on if

21:05you exclude Apple privacy opens. But this is my private community where there are two live calls every single week. You've one live call with me. There's a classroom with email marketing course. There are 250 plus email templates, new templates added every month. And even AI tools right here, like a custom claw skill you can download onto your computer. You get all the call

21:24recordings and everything right here. And I teach this with a daily insight right here that you won't find in other places. And you get early access towards all these insights. And then you also have access to me to ask questions 24/7. So if you want to have these sorts of insights then you should join my community links going to be below. Now once you start looking at email this way you understand the broader metrics and how email is a part of that you have base numbers that you can go off of expectations and get the sense of how I look at things. Now you still need to

21:50take what you've learned in this video and actually create the emails. And so in this next video I'm going to be talking to you about Clavio email flows. What to set up what the creatives are like copy design everything. If you want to see how I turn everything we've covered here into actual practice, then click that next video and I will see you

22:05over there.