Stop losing revenue after the click! Let’s find the leak before your next ad.
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Are you optimizing your site based on what looks good or what actually converts? Most brands are bleeding revenue because their CRO strategy starts with design opinions instead of hard data. If you’re copying competitor layouts or A/B testing button colors without first identifying your true ‘metric on fire,’ you’re solving the wrong problem.
In this episode, Tier 11’s CRO lead, Ned MacPherson, is back for part two of our three-part series. Ned walks through a live data presentation covering engagement rates, funnel drop-off analysis, mobile vs. desktop conversion gaps, AOV benchmarks, and demographic distribution modeling.
We also review a real-world case where a brand’s mobile add-to-cart rate was nearly half that of desktop, despite a good landing page design. If your CRO audit isn’t moving the needle, this episode will show you what you’re missing and how to find the one metric that, if fixed, creates a disproportionate impact on your entire funnel.
What you’ll learn:
- Why copying competitor designs is a dangerous CRO mistake
- How to identify the single ‘metric on fire’ that’s killing your conversion rate
- Key engagement rate benchmarks e-commerce brands should measure against
- Why a low mobile add-to-cart rate is often a content problem, not a design problem
- How to use mobile vs. desktop funnel data to uncover hidden conversion gaps
- The cart-to-checkout friction fix that boosts conversion rates on all devices
- The urgency engineering tactic that converts abandoned checkout carts
- Why AOV should always be equal on mobile and desktop
- How demographic distribution modeling helps in audience segmentation
- The step-by-step CRO loop and growth model
Mentioned in the Episode:
Previous Episode with Ned MacPherson: https://perpetualtraffic.com/podcast/episode-796-stop-redesigning-start-diagnosing-the-cro-method-that-actually-works/
Perpetual Traffic YouTube Channel: https://www.youtube.com/@perpetual_traffic?sub_confirmation=1
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Follow and listen on Apple: https://podcasts.apple.com/us/podcast/perpetual-traffic/id1022441491
Follow and listen on Spotify:
https://open.spotify.com/show/59lhtIWHw1XXsRmT5HBAuK
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https://www.youtube.com/@perpetual_traffic?sub_confirmation=1
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Connect with Ned MacPherson:
- Instagram: https://www.instagram.com/nedmacpherson/
Connect with Ralph Burns:
- LinkedIn – https://www.linkedin.com/in/ralphburns
- Instagram – https://www.instagram.com/ralphhburns/
- Hire Tier 11 – https://www.tiereleven.com/apply-now
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READ THE TRANSCRIPT:
What a Live CRO Audit Reveals That Your Design Agency Never Shows You
00:00:00:00 – 00:00:08:17
Ralph
This is the kind of thing that most businesses have never really looked at in a site like Amazon. They’re doing it. Shouldn’t you be doing it as a business?
00:00:08:18 – 00:00:22:21
Ned
The next presentation, I’ll be going through all sorts of different visual ideas based on data that is going to translate into better conversion rates, but now getting into more of the meat of it. These are some of the most important metrics that you’re ever going to want to look at. What?
00:00:22:23 – 00:00:47:04
Ralph
Hello and welcome to the Perpetual Traffic Podcast. This is your host, Ralph Burns, founder and CEO of tier 11. Very excited to have back for episode number two. I don’t know why we waited so damn long to have him on, but Ned McPherson, who runs all the CRO here at tier 11 and if you haven’t listened to or watched the first episode, we will leave that link in the show notes here.
00:00:47:04 – 00:01:06:18
Ralph
You definitely check that out where we talk about the philosophy of CRO in 2026 and what makes what we do together really, really different. And just as a quick recap, a lot of people think CRO is sort of a this designed based methodology of changing the color of the button and all that. Yes, that has something to do with it.
00:01:06:18 – 00:01:30:14
Ralph
But today we’re going to get into a little bit of, sneak peek, open up the kimono a bit as to how Ned thinks about all of this, and we’re actually going to do a screen share of ODL and how we utilize data to figure out one of my favorite expressions that you ever say that is the metric on fire, and figure out how that affects businesses.
00:01:30:14 – 00:01:47:03
Ralph
So really excited to get into today’s show. So anything you want to add before we get into the screen share? Obviously we’re pretty damn excited to have you on a show two of a three part series here. On what makes your CRO methodology so different than everything else that’s out there.
00:01:47:05 – 00:01:59:21
Ned
Yeah, no, thanks for the intro. The only thing I’d add is that a lot of folks will ask me. They’ll be like, metric on fire. Is that like a good thing? Like on fire in a good or is that bad? And like just to clarify, it’s not good. It means like the metric that is literally on fire that’s holding your business back.
00:01:59:21 – 00:02:17:08
Ned
Not to say that every brand has only one metric. Usually it’s a it’s a confluence of issues, but more often than not, we’ll see what a brand has. One particular like intro funnel metric point that if we were to solve that improve that dramatically, it has a disproportionate impact on the rest of the conversion rate for the site, the average revenue per user, etc..
00:02:17:08 – 00:02:20:22
Ned
So that that’s generally what we mean by, by metric on fire metric kind.
00:02:20:22 – 00:02:24:07
Ralph
Of fires and not the fire emoji, but the fire as in like the the.
00:02:24:07 – 00:02:25:18
Ned
Like. Oh my God. 911 the.
00:02:25:18 – 00:02:51:16
Ralph
Buckets. Yeah. Right. Right. Related to that, you were pretty much on fire in the emoji sense a week or two ago. I got a minus. Ned is actually I don’t know how you describe it, but you were at I’m sort of an F1 fanatic because of the Netflix series. I’m a recent, you know, disciple of that sport, but you actually are a lot like, what exactly do you do?
00:02:51:16 – 00:03:03:10
Ralph
Like, I know from what we’re talking about, pre-record. It’s unbelievable the stuff that you’re doing right now. Yeah it was the F1 was in Miami and you actually raced at F1 Miami just a few weeks back.
00:03:03:12 – 00:03:17:23
Ned
Yeah, yeah. I did an what’s called the support series. And so you know, very similar to, you know, say you would go to see a band play some big name band. They’ll have support bands that will come on you know, before it kind of warms the crowd up. You see this in like, comedy shows. Do you see in a lot of entertainment based things?
00:03:17:23 – 00:03:37:02
Ned
So it’s no different in motorsports, right? So when you have like the flagship event, like a formula One race, you’ll typically have what are called support series, which could be like Porsche Carrera Cup, you know, Sprint Cup in my case, racer McLaren. So this is called McLaren Trophy North America. And it is a multi-stage series where we compete at different well-known tracks.
00:03:37:02 – 00:03:53:13
Ned
And in this case, yeah, we were at Miami Formula One. So quite literally, like on Saturday, Formula one had their sprint race. They came off 30 minutes later. I’m on track right. So same crowd, same day, same track. Pretty wild experience, right? To see that many people in the stands and we could possibly show some pictures or what have you, but yeah.
00:03:53:13 – 00:03:58:18
Ned
So that’s how I get my adrenaline rush out is going about 180 miles an hour around a racetrack.
00:03:58:20 – 00:04:03:04
Ralph
Pretty amazing. And, how many people were there on that Saturday? Like, I think they said.
00:04:03:04 – 00:04:23:13
Ned
Attendance at the event. Attendance I think was 275,000. There’s not sure exactly how many were in the stands the moment, but I mean, it’s it’s a pretty visceral experience. You know, you’re coming around turn ten at 160 and boom, that’s just like Stadium of People appears in front of you and you. It actually distracts you at first because you got to stay focus on your lines and your break point and all that, and all that.
00:04:23:13 – 00:04:30:03
Ned
You just see the sea of people with their phone out recording you. It was it was quite an experience. I, you know, signed a lot of autographs, had a lot of fans.
00:04:30:03 – 00:04:31:02
Ralph
Coming up.
00:04:31:04 – 00:04:32:15
Ned
On. So. Yeah.
00:04:32:17 – 00:04:50:07
Ralph
So crazy. Anyway, we’ll leave we’ll leave some images or some links, to what you were on show notes just for people because, this sort of stuff is incredible. I mean, you and I are sort of car guys just to begin with, but I mean that you’ve taken this to the whole next level, which is absolutely insane.
00:04:50:07 – 00:04:56:23
Ralph
And this is in your backyard because you live in Miami. But are you going to go around traveling? You’re not going to go to, like, Dubai and like, yeah.
00:04:57:00 – 00:05:02:11
Ned
Oh yeah. He racing a bit in Europe this summer actually. Yeah. So it’s funny you mentioned Dubai, the actual I believe.
00:05:02:11 – 00:05:03:05
Ralph
It’s.
00:05:03:07 – 00:05:18:00
Ned
Next year, one of the world championships nurseries I’m in will be in Jeddah in son. If I make that a qualify for it will be shipping the car and the team over there. And it’s actually analogous to what we’re gonna be talking about today, because a lot of the keys to to getting faster on the track is measuring telemetry.
00:05:18:00 – 00:05:39:18
Ned
Right. Understanding data. So you basically compare things like your your break point, your steering angle, your acceleration points, your threshold of acceleration, all these very I mean, there’s potentially thousands of variables that you compare up against a different driver, like your coach or someone like that, or even a hypothetical ghost car, all in the name of trying to figure out where do you optimize to improve time.
00:05:39:18 – 00:06:05:02
Ned
It’s actually very similar to what we’re talking about today, which is in this mass of data. What do you what are the core 1 to 2, three things that, if you focus on, are going to have a disproportionate impact on your businesses conversion rate, revenue, production, etc.. The other interesting thing that’s actually quite analogous is when you’re on the racetrack, the variables are changing sometimes by the minute revolution, humidity, tire degradation, rate degradation, traffic around you.
00:06:05:02 – 00:06:20:16
Ned
All these things change. So you actually have to change how you operate a little bit. And it’s similar in digital because a lot of their conversion rate, they’ll get it dialed in. And then what happens you say, well we want to grow. So let’s open the proverbial top of funnel. Let’s go find some more exploratory traffic. Let’s get into Tick Tock.
00:06:20:16 – 00:06:38:08
Ned
And all of a sudden you drive a huge new amount of traffic in which, doesn’t convert very well. So now, not only does it bring your overall conversion rate down, that oftentimes sends a signal back to add engines or other things that you no longer convert at that rate. So the variables have changed. Exogenous variables have come into the equation.
00:06:38:08 – 00:06:56:06
Ned
So what do you do. You go back to the drawing board right. And you you iterate. You test different things. You experiment and you understand how to what to optimize for for that current state that you’re in. So yeah, actually a lot of a lot of honestly analogies when you’re doing data in a race car and also data when your business trying to optimize for for conversion rate.
00:06:56:11 – 00:07:13:15
Ralph
Yeah, there’s a lot of similarities. And then you mix in a healthy dose of adrenaline into that. Yeah. Yeah. This more intense in the car. But yeah yeah a little bit more intense. Yeah. There’s the life or death situation going on there. And CRO it’s not necessarily the case but you know, life or death in the business to a certain degree or, you know, acceleration of a business.
00:07:13:20 – 00:07:31:13
Ralph
I don’t think people realize that in F1 there’s hundreds, literally hundreds, maybe even multiples of hundreds of people that are actually analyzing data and assisting with the driver, like the driver is just a figurehead. There’s all the people that are behind the scenes, and a lot of it’s driven by all of this data analytics stuff, which we’re going to be talking about here today.
00:07:31:14 – 00:07:48:10
Ralph
Yep, in a very different way. But the same kinds of things, like if you increase, you know, one quotient, like just a fraction of a second and another one and another one, another one, all of a sudden you have an advantage over the competition, which is a lot there’s a lot of similarities there with what they’re talking about here today.
00:07:48:10 – 00:07:55:18
Ned
Now, you’re absolutely right. Yeah. I mean, literally thousands of people work on those organizations. So the drivers tend to get all the credit. But the car is, you know,
00:07:55:18 – 00:08:00:06
Ned
I mean, a famous line said is you could take the best driver on a grid, put them in a worse car. They’re not going to win.
00:08:00:06 – 00:08:04:14
Ned
You could take the worst driver on the grid, put them in the best car and they’ll probably win.
00:08:04:14 – 00:08:24:22
Ned
So it’s like it’s a team sport. So to your point, like a lot of these brands folks listening to this, you likely have departments. You know, you’ve got the life cycle departme of those focused on search optimization, those focus on paid media acquisition. I mean, it’s web conversion optimization, creative influencer affiliates to the degree of which there is a synergistic effort across all of those, right?
00:08:24:22 – 00:08:46:16
Ned
Where like the CRO team at maybe an agency or internal is sharing learnings with the affiliate team, the influencer team, it could spark ideation to better perform there. So I mean, you hit the nail on the head, like if the team can face this empirical backed methodology on how to scale the brand together, you’re generally going to see outsized growth and success with your business.
00:08:46:18 – 00:08:47:13
Ralph
Yeah, well,
00:08:47:13 – 00:09:06:02
Ralph
let’s get into how you actually do it here. So we’re going to do screen share just to tee this whole thing up over on, perpetual traffic forward slash YouTube. Check out our YouTube channel. If you click on that link, we’ll leave that in the show notes. And Ned’s going to go through just an example of the initial audit.
00:09:06:02 – 00:09:34:02
Ralph
This is and this is typically done by one tool. I know you guys use a tremendous amount of other tools, but this is sort of pre show. If you do want this service from us over at tier 11.com/cro. This is the type of audit that you’ll get. And I think this is the kind of thing that most businesses have never really looked at in this depth, even at the initial stages.
00:09:34:04 – 00:10:03:07
Ralph
And we’re actually working with your team right now to, to increase the CRO efficiency and the conversion rate of tier 11. And it’s amazing to me being the clients, you know, Eric, quoting how deep you all go and was just the first part of it, which is deep enough like, well, I remember our first conversation with the members of the CRO team and it was just amazing all the different ways in which I was like, man, I never knew all of these things.
00:10:03:07 – 00:10:21:09
Ralph
And I’ve been doing this for 20 years now. So yeah. So yeah, so this is obviously a screen share. We’re going to be going through this here today talking about this analytics model and how it really does differ from the sort of design centric model, just the way the sort of traditional CRO is done. So check us out over at.
00:10:21:11 – 00:10:28:08
Ralph
So check this out over at perpetual traffic.com/youtube. So take it away net.
00:10:28:10 – 00:10:58:13
Ned
Yeah. So and one thing I want to just preface is what the slides we’re going to be running through today are the, the first half of the the audit style presentation. Right. So if you listen to the first podcast review that we had, you know, I came out, we talked a lot about and you references today not following a design centric approach to reiterate the way most people approach CRO individuals, internal teams, even agencies, unfortunately, as they’ll take a look at your brand site, the look at competitors, look at brands that are maybe not competitive, that are tangential, right, or adjacent to to what you do.
00:10:58:13 – 00:11:16:19
Ned
And they’ll say, you know, look at how they did their site, Carter, look at how they did their navigation or look at how they built their hero section. That looks nice. Let’s try that. And that is a dangerous approach, because that is a design centric impetus behind the ideation, where for all you know, those things that you’re replicating are the weakest performers they have on their site.
00:11:16:19 – 00:11:34:18
Ned
Right? So you’ve got to come at this from an empirical lens. So we’re going to be walking through today is some of the data slide. You go even deeper than this even on the initial complimentary audit. But some of the data slides that start to uncover clues, so to speak, that start to point us in the direction of where we need to focus to get outsized success.
00:11:34:19 – 00:11:55:01
Ned
Again, one thing I’ll reiterate is the success that we’ve had as a senior organization over the years is really predicated not on us coming up with these like crazy zero day ideas that no one’s thought of. Yes, we have some good ideation. Absolutely. But the real genesis of it is focusing at the right section of our website, to the right audience, at the right time, like mobile users.
00:11:55:01 – 00:12:13:05
Ned
Top DMA card to check out. Right. And we say that point in the user journey is the weak point. That’s where we need to focus and we just run experimentation there. We move the needle. That’s the elixir to, success that we’ve had, so to speak. So we’re going to walk through some data slides today. I do want to preface on our next presentation will be walking through some of the visualization.
00:12:13:06 – 00:12:24:12
Ned
So kind of pique your curiosity on that one. In the next presentation I’ll be going through all sorts of different visual ideas based on data that is going to translate into better conversion rates, but nonetheless, let’s kick off here, starting.
00:12:24:12 – 00:12:24:20
Ralph
With.
00:12:24:20 – 00:12:45:18
Ned
Always looking at super high level. Where’s traffic coming from? What does it do when it first lands on the site? Most particularly, what are new users doing. So there’s a couple metrics here I’m just going to harp on. Again, we’re going to do just a little snapshot that give me a good understanding of base case. How good is the brand doing at its first job, which is getting somebody not to leave right away?
00:12:45:20 – 00:13:10:16
Ned
And that may sound basic, but the reality is most brands experience enormous abandonment rates and exit rates on landing for new users. Take a look at this brand as an example. Their initial engagement rate here is just a smidge over 50%. So what that means is nearly 50% of their traffic does not engage from a new user perspective, not engaging means they don’t click, they don’t scroll, they don’t navigate, and they leave within 10s.
00:13:10:17 – 00:13:26:01
Ned
That’s basically someone who ends on your site, maybe reads or maybe just looks and says, now this isn’t for me. That’s a problem. So the next thing we have to look at is, well, what is the landing event? Let’s assume it’s home page. The above fold section is going to need disproportionate effort in this case with this brand.
00:13:26:01 – 00:13:45:03
Ned
I know right out of the gate because of the poor engagement rate. Generally speaking, we want to see most brands at at least 60% or higher here. Ideally, if you’re brands in the 70s, you’re doing really well. Anything high 70s or even low 80s is world class like. Exceptionally good position of your traffic. Keep that in mind too, right?
00:13:45:03 – 00:14:07:01
Ned
So if you have a brand, I sells products to dog owners, right? And you drive a bunch of cat owner traffic to the site, that’s going to be a problem. Most of them are likely going to abandon. The site isn’t structured well because it’s just the wrong audience. So it’s not always the fault of the site. It can be traffic related, but nonetheless, this is a clue to lead down, to understand what is potentially going on here.
00:14:07:03 – 00:14:11:12
Ned
Another metric that’s important to look at is sessions per new user. So this is a fun.
00:14:11:12 – 00:14:13:12
Ralph
Metric because you don’t want this too.
00:14:13:12 – 00:14:31:19
Ned
Low, nor do you want it too high. If you have this at around one, that basically means the typical new user is going to come to the website and they’re one and done, they’re going to look at the site and they never come back, right. Alternatively, if that was like a three, that means new users on average come to the website a bunch of times before they actually do a thing, right?
00:14:31:19 – 00:14:49:19
Ned
They actually fill out a form they actually add to cart. They actually complete a transaction, which is equally problematic. Why do I need so many visits to the site before they did that? As a general rule of thumb, we like to see brands hovering in the like 1.4 to 1.6 ish range. So call it 1.5 on average. This brand’s doing excellent.
00:14:49:19 – 00:15:10:01
Ned
This is a really solid session per user metric. It’s not quite too low, not quite too high. In my experience. That’s kind of dead down the middle of the fairway. Another key thing to look at is engagement time. So over here, this brand with a 50.87% engagement rate, solid sessions per new user, decent growth year over year and session and user count 55 seconds.
00:15:10:03 – 00:15:29:09
Ned
It’s pretty low 55 seconds goes by awfully fast and keep in mind for those that complete utilitarian sides of the site like adding to cart, reviewing cart, entering information on a checkout, all of that contributes to this. So the reality is, is when we look at engagement time, we’re often associating that with browsing time, which it’s not true.
00:15:29:09 – 00:15:57:11
Ned
Browsing time is going to be less than this. So if you have a 55 second total average, that means your browsing time is somewhere probably in the 40s. 40s goes by real fast. Now, if you’re a single skew product with a very clear call to action and a very clear, unique selling proposition, hey, we are a product for this person to solve that problem at this price point, and it’s really easy to understand in rare circumstance it’s acceptable to have a low engagement time.
00:15:57:15 – 00:16:17:05
Ned
But if you’ve got multiple products, especially like maybe a fashion brand or any brand that has like an esthetic aspect to it, if you’ve got a brand with multiple products, right, or lines of products, and that’s a dead giveaway as to like basically shallow scroll that people are not browsing the site, they’re certainly not spending much time on any one page or certainly not reading very much.
00:16:17:05 – 00:16:37:00
Ned
So again, some telltale metrics there that should kind of be a red flag, so to speak. As to typical top of funnel new user behavior. Now getting into more of the meat of it, these are some of the most important metrics that you’re ever going to want to look at, which are into your funnel behaviors. So in this case, you’ve got a mobile and you’ve got a desktop that’s broken out here.
00:16:37:01 – 00:16:42:08
Ned
This is a very basic funnel. We go quite a bit more in depth on this. But what we’re trying to identify
00:16:42:08 – 00:16:58:08
Ned
is of the website chunked down into its incremental parts. Which of those parts is disproportionately lower or outperforming compared to one e-com in general to brands in your industry? And maybe three brands that are competitive that we have unique access to.
00:16:58:10 – 00:17:30:13
Ned
So as a general rule of thumb, right, general rule of thumb for a typical average order value products as an example. So we’re talking $60, $80, maybe low 100, right. Average order value products that are in the direct to consumer space, maybe CPG, maybe accessory things of that nature add to cart rates are, generally speaking, in a range between 12 and 18% fashion as an example, to give you an example, why might change will index higher, especially female fashion.
00:17:30:13 – 00:17:40:23
Ned
You’ll typically see add to cart rates 15 to 26%. And part of the reason for that is a lot of shoppers on fashion sites will use the Add to Cart button as a wish list,
00:17:40:23 – 00:17:50:19
Ned
and they’ll do that even if there is a wishlist feature we’ve noticed, by the way. So you’ve got to always measure yourself up against what is normal in your industry for your average order value.
00:17:51:00 – 00:18:14:00
Ned
If you’ve got an average order value, that’s like $700, you’re not going to have a 15% add to cart rate. You’re going to be more in the like 3 to 7% rate. But nonetheless, we’re always trying to baseline you to see where are you at. So starting with this let’s talk about mobile first. So view item. What this is basically telling us is of the traffic that landed on the website, who engaged what percentage of it actually saw a product view.
00:18:14:01 – 00:18:36:18
Ned
Now if the majority of your traffic lands on like a bestseller collection page or maybe the home page, this is a very telling metric as to how much progressed into a PDP. If the majority of your traffic lands on a PDP, you have the opposite problem because it’s going to inflate this number. It’s going to give you effectively, like a false positive queue, right where you’re going to look at that and be like, oh man, we do really well at navigation.
00:18:36:18 – 00:18:52:06
Ned
It’s like you don’t, it’s because you landed so much traffic on the actual product pages themselves. So again, there’s always nuances to this, but nonetheless, this brand actually does have traffic that lands on its homepage. 74.7% is excellent. That’s a really great research.
00:18:52:10 – 00:18:55:15
Ralph
I would have thought on socks that actually, but anyway. Yeah go ahead.
00:18:55:17 – 00:19:18:20
Ned
Yeah, that is a tremendous rate right there. Right. A lot of brands are 40, 50, 60%. That is tremendous. Mid 70. So I want to highlight what exceptional performance that is. Now note on desktop much weaker. So immediately there’s a telltale sign why. Why is desktop traffic weaker there. Is it because of a landing event. Is it the composition of traffic or is it the actual view that they have?
00:19:18:22 – 00:19:38:02
Ned
In this case? I can tell you, one of the things that this brand did is they had a best seller navigation. Right. Unlike the top most prominent bit of navigation on mobile, they didn’t include it on desktop. That was one of the telltale signs. I know it sounds simple right away that boosted desktop homepage navigation into product views.
00:19:38:04 – 00:19:57:07
Ned
So we’re finding clues here. That’s what I’m trying to get to is interesting. Do really well mobile not on desktop. What’s different. Well let’s compare them. Let’s look at mobile. Let’s look at desktop. Let’s get some people together. What are the differences between these two moving down funnel. Now we look at add to cart rate. And what super interesting here is you see some major shifts in that behavior right.
00:19:57:10 – 00:20:17:10
Ned
Add to cart rate on mobile 11.4%. That’s statistically low for the brand. The industry that this brands in that 12 to 18% marker is absolutely where they should be. So they’re not even at the lower end of that threshold. Right. So we know that the add to cart rate on mobile is a metric on fire that we need to focus on right now.
00:20:17:10 – 00:20:32:22
Ned
Desktop does considerably better. One of the things that we found with this brand is the actual education they had on desktop was in my opinion, like three x, the content they had on mobile, they had on desktop infographics, us first them charts. All this beautiful.
00:20:33:02 – 00:20:33:18
Ralph
Mobile was.
00:20:33:18 – 00:20:42:23
Ned
Way more condensed. It looked pretty, it looks minimalist, but it didn’t provide the education. And what do you know? It look at the differences in the add to cart rate.
00:20:42:23 – 00:20:44:18
Ralph
So is the sale it sounds.
00:20:44:18 – 00:21:01:10
Ned
Yeah. So you can already hypothesize you’re probably already saying in your head, well, I could probably fix that. It’s like pull some of the infographics, pull some of that richness of data, that content from desktop pie to mobile. Exactly. One of the first things we recommended. So this is a good example of the idea that we came up with is pretty elementary.
00:21:01:12 – 00:21:19:18
Ned
Move some of the assets you have from desktop into mobile. Why didn’t this brand figure this out for years before we came in? Because they didn’t look at it through the lens of an empirical experiment. It was designed well. It’s so minimalist. It’s so beautiful looking. It’s this and that. Yeah, but you’re losing like 50% of your potential add to cart rate at that step.
00:21:19:18 – 00:21:21:09
Ned
So always keep that in mind.
00:21:21:10 – 00:21:27:18
Ralph
So like this is a mobile first site. Like the portion of traffic I can’t quite read it on the screen.
00:21:27:18 – 00:21:43:20
Ned
Yeah I mean you could see it’s considerably more traffic on mobile right. So again that’s a good point to carry. But again look at the difference there in the two. I mean dramatic like it is true desktop generally will out convert mobile. So like for instance if this was a 13 and this was 11 I would not sit there and be like man desktop something better.
00:21:43:20 – 00:22:01:19
Ned
I’d say that’s a normal distribution, but like double the conversion rate, not normal. So that was a clue. That again led us to figuring it out. Idea that one right now next. And this is why I love showing this example because I’m showing you all these interesting things from the same brand based on two device types cart to checkout rate.
00:22:01:19 – 00:22:21:13
Ned
So this is basically identifying of the people are. And then this is saying what percentage of those people then clicked into checkout. So you get a little side card view. You review your order. What percentage. Hit the progress button into the checkout. Mobile 28.6 desktop 41.5. Both of those are low. So metric on fire once again for both device types.
00:22:21:15 – 00:22:44:17
Ned
Now it’s higher on desktop. But remember desktop typically converts better than mobile in most instances. And so in reality when you adjust for that, this would be more like a mobile 3528. So not a huge delta there. What we did in this case is we said foundationally it’s not a device type problem, but foundationally, what are we missing on the actual step here?
00:22:44:17 – 00:23:07:06
Ned
Right. What are we missing in the cart experience or what are we doing in the cart experience that’s causing people to balk? And one of the things is this brand had a auto triggered shipping insurance feature. So when you got to check out Add to Cart and you added your $90 product, all of a sudden you saw it was like 97 and it’s like, why did it go to 97?
00:23:07:06 – 00:23:19:02
Ned
You just told me on the last step it was 90 bots in on the cart. There was this little widget that automatically added, $7 in shipping insurance on both desktop and mobile. So again, what’s the idea?
00:23:19:06 – 00:23:20:20
Ralph
Keep the feature default.
00:23:20:20 – 00:23:46:19
Ned
To toggle off and let them toggle it on. Right? That’s not a mobile specific idea. That is a agnostic to device type idea, which is why we were able to grow the carts check rate on both of these with the same idea. So you just saw how we went through three different steps of the funnel, looked at it with totally different insight based on mobile desktop or or basically agnostic to device type three completely different ideas, all of which were work success there.
00:23:46:19 – 00:24:02:05
Ned
But the bottom line of the slide is basically do identify like where are we weak? Where do we need to focus on? And if you’ll notice, one thing I do not harp on here is the checkout the transaction rate. And the reason why is 70.9 and 79.7 is like really strong.
00:24:02:06 – 00:24:04:14
Ralph
Seemed pretty good, really really good.
00:24:04:19 – 00:24:23:08
Ned
So good that it makes me wonder are we priced too low? So when I see this it’s like you convert so well, it’s kind of like the classic negotiation tactic where you know you’re doing a deal and you propose the price, and then the seller basically says, okay, that’s fine. You’re like, damn, I went into low because, like, they should have haggled with me a little bit, right.
00:24:23:11 – 00:24:41:19
Ned
Same exact idea here. When you see rates are so good, that indicates that you might be leaving money on the table. Or maybe your audience is so price inelastic that they would justify a higher price point. So I would say that this is so good. It’s bad in a weird way, right? Because it’s like we might be losing some margin on the table.
00:24:41:21 – 00:24:48:11
Ned
Consider increasing prices. And again, that’s a big idea. We’d have to break down more. But that’s generally what I’m seeing here. When I see those rates.
00:24:48:13 – 00:25:10:12
Ralph
Right. What I love about this is there’s you’re taking the data unemotional. It’s not I like the data or I don’t like the data. Hey, our mobile site looks better and it’s cleaner than our desktop site, but that doesn’t really matter. Human emotion and opinion doesn’t matter when it comes to this. So you have the analytics insights.
00:25:10:12 – 00:25:33:07
Ralph
Then there’s a level of experience based upon similar industries, similar clients like two, three, 4000 of these things take have team have done here. Like there’s a breadth of experience which is so wide and then it’s a hypothesis and a theory based upon what you’re seeing. And it like the purchase thing, I would be like, oh, I wouldn’t even touch the purchase.
00:25:33:07 – 00:25:52:09
Ralph
But you’re like, oh, maybe we’ve got an inelastic place model, which basically means like we raise the price. It’s not going to affect your conversion rate any because you built up so much value. There’s so much like there’s layers of this that you sort of uncover, which is one of the cool things about when we were describing this, like this or analytics model.
00:25:52:11 – 00:26:03:16
Ralph
Yeah, because it’s based upon analytics. But then it’s also this level of experience, what you’ve seen in other industries and what you would expect based upon all these multi factors.
00:26:03:18 – 00:26:19:22
Ned
Yep. You nailed it. You know. And that’s why not to sound cliche, but there’s really no such thing as a test that loses. And either wins and you get the lift or you get some interesting learning by. Because like when you test you’re taking what’s called a null hypothesis, which is the base case on the site or the cart or wherever you’re testing.
00:26:19:22 – 00:26:38:21
Ned
And then you’re applying an alternative hypothesis. If the test loses, it basically says your alternative hypothesis was false to some or a total degree. That’s really cool, right? So you’re like, okay, so we know that’s not true. Now let’s try the next one. So again, I know it sounds a little, you know, cliche to say, but nonetheless, I mean you really never lose a CRO.
00:26:38:21 – 00:26:47:08
Ned
You’re either getting a ton of interesting learning and or invalidating hypotheses, or you’re getting literal revenue less. It’s, you know, obviously I’m partial, but it’s a win win.
00:26:47:13 – 00:26:50:22
Ralph
Yeah, yeah. Very cool. So a couple.
00:26:50:22 – 00:27:07:01
Ned
Other things that we look at here is just general consensus, right. So like you know and this is actually a different brand in this case I wanted to show this because there was a lot of discussion around merchandizing. Right. This is a women’s a women’s brand women’s fashions brand. There’s a lot of discussion around merchandizing and where data can really point to it.
00:27:07:01 – 00:27:32:09
Ned
So in this case you can start to see the like relational understanding of items viewed to add to cart rates. Right now it’s important to do this because a lot of times you can use a chart like this that makes traffic basically the agnostic variable, right? That you can remove it from the equation. Oftentimes you’ll get misleading add to cart rates on like product pages because this one product page we drove, you know, 30,000 TikTok landing events to it.
00:27:32:09 – 00:27:52:08
Ned
So it’s like, oh man. You add to cart rates really low. It’s like, yeah, but if you normalize for traffic, it actually might have one of the highest add to cart rates. So oftentimes we’re looking in building out charts like this to basically merchandise properly. I can’t tell you how many times I’ve worked for the brand where I’ll look at their collection page and I’m like, you’ve got your worst sellers at.
00:27:52:08 – 00:27:53:13
Ralph
The top of the collection.
00:27:53:13 – 00:27:58:09
Ned
Page, and your best sellers two scrolls down. If I literally just invert that, we’re going to.
00:27:58:09 – 00:27:59:00
Ralph
Make like.
00:27:59:00 – 00:28:19:12
Ned
5% more revenue just overnight just by doing. And it’s little things like that can make a big difference. So I use this slide to basically emphasize some really simple things can get done with data to tell you things like again, the relational understanding on add to cart rate to product view rate. And this is a great X-Y axis as an example within GA, by the way, to show that now this is another funnel.
00:28:19:12 – 00:28:37:15
Ned
But this one this is showing. Check out the transaction rate. So there’s a couple things here. One is remember I talked about how good that checkout rate was on that former brand. And I’d like 79%. Well now we need to break down to be like well let’s assume that number is 50% 60, 70. Whatever it is. The next question is well where on checkout are we losing them?
00:28:37:17 – 00:28:54:12
Ned
Because if they land on checkout and don’t even bother giving us their email, that’s a very different abandonment rate than people who land on checkout give you their email shipping info, type out all their credit card info, and then they get cold feet at the very last step. Two very different scenarios there, which require two very different approaches to solve it.
00:28:54:14 – 00:29:13:23
Ned
So as a general rule of thumb, if you see a brand that’s converting the 80 or 90% range right here, you, generally speaking, are on the let’s just say like either the audience is a little more price inelastic or you maybe nailed the price point or for whatever reason, at the bottom of funnel, people are not getting a lot of cold feet.
00:29:14:01 – 00:29:30:18
Ned
If you’re at like 40, 50, 60% here, you got the opposite problem, which is people want to buy it, they really want it. But they get to that last step and they’re like, I got to think about this longer. That’s too much money or that’s too big of a commitment or whatever it is. So maybe price justification tactics are going to be your winning formula there.
00:29:30:23 – 00:29:52:06
Ned
Now, on the contrary, if you see a brand has really bad conversion rates at the top of file, right, only two thirds of people even bother entering their email. Now remember, these are people who went through, reviewed your site, went through a collection page, probably went through a product page, read something, thought about it, selected their size or variant or color or whatever added to cart, reviewed cart, and then made it to checkout.
00:29:52:06 – 00:29:56:14
Ned
So for them to go, I know I’m just going to walk away is an odd one, right? That’s kind of a head scratcher.
00:29:56:16 – 00:29:56:22
Ralph
Yeah.
00:29:57:04 – 00:30:13:11
Ned
Oftentimes when we see bad rates here, it is indicative of an urgency problem. Meaning think about it for a second. If you’re on your mobile device, in your browsing you find a cool product. Browsing was fun. It’s fun. There’s no harm. There’s no foul you can add to cart. But when you get to checkout. I know this sounds crazy.
00:30:13:11 – 00:30:29:14
Ned
You actually have to put a little work in. You have to type out information or in your computer. You have to do it. That’s just enough friction to induce procrastination. So often what it is, it’s not that people don’t want the product, they’re just like, I’ll get to this later, and it lives as a tab that collects dust on their browser.
00:30:29:14 – 00:30:32:11
Ned
They go check emails, they go check slack. They do this on that.
00:30:32:13 – 00:30:35:19
Ralph
So how do you engineer urgency?
00:30:35:21 – 00:30:59:03
Ned
Well, like here’s a little tactic. We had one brand that consistently had this problem. They introduced a free gift. So if you ordered more than like 50 bucks they threw a free gift in. So what we did is on checkout. We said, hey, that free gift that’s today only. So we engineered scarcity. Now we made that the proverbial perception of losing the free gift was a greater motivator than the friction of entering your information.
00:30:59:03 – 00:31:10:10
Ned
Check out like that. We saw the checkout rate go up, so there’s an example of an idea that could work if you hypothetically see the very top of funnel on checkout having disproportionately low conversion rates.
00:31:10:12 – 00:31:32:21
Ralph
Like insights and then action. I mean obviously now you wanna I mean the previous graph here, all things being equal, I know this is a different client here, but all things being equal, you’re focusing in on the thing that really matters the most. And on this one right here on this client, was that the thing that you were that was that the first metric on fire that you identified, or was it secondary?
00:31:32:21 – 00:31:34:16
Ralph
I’m just sort of more curious.
00:31:34:18 – 00:31:51:02
Ned
Yeah. Yeah, I believe this one was primary, because if you do that just like kind of cumulative calculation or checkout rates pretty low, right? I mean they lose 33% and another 37% and another 20%. So like you know, there was a lot of room for growth on checkout. And like this is this is the idea that ended up working for them, right?
00:31:51:02 – 00:32:11:22
Ned
That that really unlocked it. But you could see how I did the thought process of how we got to that idea that I just walk you through is the key to the whole thing, right? That’s the idea behind it. And so the idea itself isn’t that crazy. It’s not even that novel. But you could see how if you took a design centric approach, the chances of you getting that one right are slim, right?
00:32:11:22 – 00:32:15:19
Ned
You’ve got to take a data centric approach. Hence why I’m going so much on data today.
00:32:15:19 – 00:32:37:11
Ralph
And this is so good. Like I said before, I mean, it’s the insights plus the data and the experience. All all sort of mashed together. And then through what you’ve had, what you’ve expected and what you’ve experienced in the past with similar types of clients. Obviously the industry price point, there’s so many factors here where the traffic is coming from, you know, is it coming from Google search?
00:32:37:11 – 00:32:57:09
Ralph
Is it coming from TikTok? Is it coming from meta, which is a whole other thing like intent based versus sort of interruption based, like where you’re sending the traffic. Is it a collection page? Is that the home page? Is it a PDP page like all of these factors are like entered into your decision making process when it comes to these metrics on fire.
00:32:57:14 – 00:33:02:02
Ralph
And then a decision and a test is designed around all of those factors?
00:33:02:05 – 00:33:09:22
Ned
Yeah, exactly right. You nailed it. Exactly. And that process is the key to the whole thing. Exactly. Right. As an example is sometimes brands will come.
00:33:09:22 – 00:33:11:08
Ralph
Like I remember there’s just.
00:33:11:08 – 00:33:25:20
Ned
Sites where I got invited to a, like a it was like a round robin tournament for Sierra. And they brought a bunch of CRO experts in, and they just gave you a website and they’d have like two people compete who had the best ideas. And I know this sounds a little dramatic, but I opted out of the whole thing because I’m like.
00:33:25:22 – 00:33:27:13
Ralph
That’s not how Sierra works.
00:33:27:13 – 00:33:44:23
Ned
Like, I can’t just look at us all to look at the design, because then it’s just my design opinion versus someone else. Like, that’s, I need to see the data, or else we’re just guessing at the end of the day. So just to really put an exclamation point on candidly how off base the industry often gets with this, you know, and so you’ve got, again, you preach this one, I think I know, but you kind of get the point.
00:33:45:03 – 00:33:52:20
Ralph
And it says a lot in your competitive nature to, to build up that. Yeah, yeah, sure. There is no way I can have an impact as because you’re looking at the wrong side.
00:33:52:22 – 00:34:12:07
Ned
Like I was like, this is just fundamentally false, you know? Yeah, yeah. So a couple other things here, not measurements. Right. So what I’m looking for here is oftentimes not a conversion rate when it’s a AOF win. So in this case most brands index more towards mobile. Most are going to drive more revenue from mobile. Most will have slightly lower conversion rates.
00:34:12:07 – 00:34:28:02
Ned
This is very normal to see. That’s not to say that both of these metrics should not be approved. They absolutely should. But at the end of the day it’s typically normal. You know, especially depending if you’ve got an AUV that’s in the hundreds of dollars you’re going to see conversion rate a bit lower on mobile. To me, this delta is totally acceptable.
00:34:28:04 – 00:34:45:11
Ned
Now, what is not acceptable is to see the AOF like $60 lower on mobile than desktop. Nowadays, there’s no reason why mobile should ever be underperforming on AOV compared to desktop. So while it’s true conversion rate has a little bit of.
00:34:45:11 – 00:34:46:00
Ralph
A.
00:34:46:02 – 00:35:06:05
Ned
Hall pass to be a bit lower than desktop, it is not the case for AOF. So I look at this slide in, the first thing I’m looking at is what is the delta. And is it comparative here. And if this doesn’t match here immediately I know we’ve got an issue there. So as an example, this brand I can kind of share did a phenomenal job with recommendations two sets.
00:35:06:05 – 00:35:23:11
Ned
It’s another brand that’s in the accessory and kind of fashion spray space right. Desktop had this beautiful like you were shopping for this and they’d be like complete the outfit, complete the SAT. And you can kind of see how people would buy an ensemble. Mobile really didn’t do that. They had that feature buried under a carrot. So like most people just didn’t even see it.
00:35:23:11 – 00:35:47:07
Ned
And even the ones who saw it had kind of had this random assortment of products. So that ended up being the hypothesis to be like, okay, well, we’ve learned something from desktop there. How can we apply that to mobile? Turns out to be kind of a winning variant there, where you can propose a higher AOV. So moral of the story is, while some metrics give you a give you a acceptance criteria to be lower, don’t fall into the trap that just because it’s mobile, you’re allowed to have a lower AOV.
00:35:47:07 – 00:36:07:08
Ned
Shouldn’t you really? Right now the one trade off to that would be for extremely high purchases. Right. So like as an example, I worked with a, a car brand for quite some time that everyone would know the name if I said it. The average order value is like $46,000, right? I mean, people are buying cars. In that case, the predominant behaviors.
00:36:07:08 – 00:36:29:18
Ned
People will spec the car in mobile and they’ll jump over to desktop. So they saw very little conversion rates so low it was almost statistically insignificant on mobile. All the conversion data happened on desktop, but all the browsing behavior and configuration happened on mobile. So in cases like that you can have a little bit of a oh no, it’s kind of an outlier, but generally speaking, again AOV should be equal on mobile and on desktop.
00:36:29:22 – 00:36:48:21
Ned
Now this is one of the last slides to go through here. Which is really interesting, which is demographic distribution modeling. So I’ve pitched you all sorts of things here about oh, we got to dive into data, but a lot of CRO gets blanket applied to all users. That’s a common mistake. The follow on question, a lot of the ideation I would provide, and a lot of the analysis is.
00:36:48:21 – 00:36:49:06
Ralph
To.
00:36:49:06 – 00:37:09:03
Ned
Whom do we apply these ideas to to maximize the impact. So one of the things that we’re looking at is demographic distribution model. Right. So in this case you’re going to look at traffic patterns by age brackets here. So like this is the 18 to 24 mark right here. This is this 17% is going to be 25 to 34 etc. etc. all the way up to the 65 up.
00:37:09:06 – 00:37:29:08
Ned
So it’s one thing to know what percentage of traffic is broken into these different demographic buckets. The next question is what percentage of transactions attribute to those same buckets, and are they even indexed? So as an example, you can look at the 25 to 34 year olds here. They’re about 17% of traffic but they’re actually only 11% of transactions.
00:37:29:08 – 00:37:50:22
Ned
So that is under indexed in terms of their performance. Right. Remember now on the flip side of that you can look at the 35 to 44 there 26% of traffic. And they’re 29% of transactions. And do not see that little orange sliver there. That’s the 18 to 24. So you may be looking at these three. Just note that this 7.2 corresponds to that dark orange, but nonetheless that 29%.
00:37:50:22 – 00:38:12:12
Ned
So there what Overindex. So the question becomes to whom do we apply a lot of these ideas to? And the answer is, well, probably the audience set that is most underperforming when it comes to transaction volume, right. Not all users are going to react the same. 65 year old Midwestern living, you know, woman, it may not respond the same as a 21 year old New York City living male.
00:38:12:12 – 00:38:30:19
Ned
They’re totally different demographics, right? So you’ve got to chop this down into demographic use as well in same thing when you get into like gender distributions as well. You know, in this case, I see females are dominant on this brand. But if you take a look at overall transaction volume, you’re going to see the 16% of males produces virtually no revenue.
00:38:30:19 – 00:38:55:10
Ned
So it’s like, do we want to even compress this down? Or maybe the question is, is there a way to convert these a little bit better? Right. Maybe they’re buying gifts. Depends on what it is. So long story short, here is you want to use demographic modeling to to help guide your CRO program. And very last thing here just before we wrap, just as a reminder to just hammer home to make sure everybody’s heard this a thousand times, there is a step by step process to CRO.
00:38:55:10 – 00:39:18:10
Ned
It is not just looking at design. You audit first, ideally identifying the metrics on fire, the metrics that matter, causal versus correlations, etc. based on the data like we walk through today, you idiot. Ideation is unbridled. It’s my idea. It’s your idea. It’s customers ideas. It’s key stakeholders. Random strangers, whatever. Get a whole ton of ideas. Then we prioritize and nominate.
00:39:18:10 – 00:39:35:19
Ned
We take 20 ideas. We narrow it down to the two that we think are going to absolutely move the needle. Then we execute, launch an AB test, multivariate test, whatever it is, and then you analyze and rinse and repeat. That’s the secret to it right there. Right. So that is the whole CRO loop and growth methodology all wrapped up.
00:39:35:21 – 00:39:37:00
Ned
And that is my last slide.
00:39:37:03 – 00:40:01:01
Ralph
And it never really ends I mean technically I mean this is ad infinitum. I mean, I think, you know, in a lot of cases, you since we’ve been working together, people are like, well, that’s good enough for me. I mean, all right, well, you guys have like increased my conversion rates in the, like, based upon my mix and everything else and all the insights that you have here by X percentage, it’s almost like it’s a never ending process.
00:40:01:04 – 00:40:16:08
Ned
It really is. I mean, think of some of the biggest brands in the world. Think of, you know, the Airbnbs of the world. I mean, today, y we’re recording this. They probably have a department of two dozen people running experiments to improve repeat rates, conversion rates, referral rates, viral coefficients, you name it. So yeah.
00:40:16:10 – 00:40:20:13
Ralph
I mean, a site like Amazon, I think is running a thousand split tests at any given moment.
00:40:20:18 – 00:40:21:20
Ned
Exactly. So there you.
00:40:21:20 – 00:40:25:00
Ralph
Go. That’s what they’re doing. It. Shouldn’t you be doing it as a business.
00:40:25:01 – 00:40:26:06
Ned
Right. Yep. Exactly.
00:40:26:10 – 00:40:46:01
Ralph
This is this is tremendous. I had so many questions. But the good thing is if we’ve got a third episode that’s going to come, you couldn’t go deeper into all of this. Obviously, if you want this for your business, Ned and his team are on standby to help you out and do this audit here. This is what you get in a condensed form in that initial audit.
00:40:46:01 – 00:41:16:01
Ralph
Like this is incredibly valuable. I remember when we first started working together, remember the demographic split on a client that we’re first started working on together? It was so skewed. I was like, oh my God. Like, I’ve I never would have understood that. That was just one thing and everything along the way. I mean, the cart abandoned rates like mobile versus desktop or the differential, your Alvey analysis, all of this stuff, like every little bit makes such a big difference.
00:41:16:03 – 00:41:38:08
Ralph
But it does start from this, this kind of basic but not really basic. This is really in-depth audit. You can get that over at tier 11.com/cro. So Ned looking forward to episode number three here. I’ve got pages of notes to ask you more questions. So maybe we’ll make that one even a little bit longer. But obviously great to have you on here.
00:41:38:08 – 00:41:55:08
Ralph
Perpetual traffic. It’s been way too long. And just for showing us really that the differential between like how you and your team do all this versus what the industry standard is and the industry norm. Yeah, insane to me. And that’s why you guys are the best CEOs in the planet. There’s no.
00:41:55:08 – 00:41:58:15
Ned
Question. Appreciate you having me on as always. So looking forward to the next episode.
00:41:58:17 – 00:42:20:12
Ralph
All right. Well, everything that we mentioned here will be over in the show notes over perpetual traffic.com. Make sure that you do watch listen to the first episode of Myself and Ned and looking forward to the third one. Make sure that you’re looking at your your podcast feeds whenever that comes through. And of course, you can watch this at perpetual traffic.com/youtube.
00:42:20:13 – 00:42:33:23
Ralph
And on behalf of Ned McPherson till next show, see you.
