How to Analyze Landing Pages in Less Than One Hour Using Google Analytics

(upbeat music) - Awesome, thank you everybody for joining me. This is one of my favorite topics because it revolves around research which I believe is one of the most important things in optimization and so today we're gonna look at how to analyze landing pages in one hour using Google Analytics. I said one hour, but most of what I'm going to show you here you can actually do in less time so it's like saying one hour is actually giving you a lot of time to do it. I would argue that some of the stuff I'm going to show you can basically do in like 10 minutes if you go through quickly.

And being able to do this quite quickly I think is important
because doing research is one of those areas that people seem to struggle with. I understand why. I used to struggle a lot with it too, but if you kind of look at an overall optimization process, this is kind of my simplified version. It's not too different from what most people show, but or what most people describe as the process, but one thing that I, a point I want to make is I think a lot of times, conducting experiments, running split tests for example is kind of what takes up most of the time and that's kind of where I used to spend most of my time as well, being excited about doing split tests.

Now that I've been doing it for 10 years,
this is what gets me fired up is conducting the research and I still love split testing. I think it's important and when I say conduct experiments, it doesn't have to necessarily mean split testing. It's especially experimenting with what you have learned and what you think is right, testing your hypothesis and so on, but the way I look at it now is that conducting research is the most important part in my process anyway since it's just my experience just because it makes everything a lot better and a lot easier.

It also makes all your experiments better
and it just helps you get insight and have a more beneficial process. So what I'm saying with conducting research upfront is basically you're investing time and understanding your target audience, understanding the situation a lot better. Sometimes you talk to marketers and they go like oh it seems like such a hassle. I'd rather just assume I'm right. The problem there is then you're relying on basically psychic abilities or gut feeling. I don't have psychic abilities. I don't trust my gut feeling so that's why I want to do research.

There's differing opinions on this.
Some people think that marketers have to have sixth sense to know this stuff. That's not the way I do my work so just prefacing with that. So the way I like to think of approaching an optimization process, project, whatever that is, landing pages or whatever it could be is like kind of putting a puzzle together. So you might have kind of an idea of what the image is gonna look like, what the final puzzle is gonna look like once you get all the pieces together and you might have some of the pieces of the puzzle right now.

So what we're doing is we're trying to find
the missing pieces, we're trying to put it all together. So it's detective work and obviously research consists of quantitative and qualitative research. So I would argue that both are very, very important.

They go hand in hand and they have to support each other
because they do fundamentally different things. Quantitative research helps you understand what and where. So for example, by going through Analytics, for me, quantitative research is mainly Analytics. So by going through Analytics, we can understand like stuff like what and where, what's going on and where. So for example, we are able to see that users are leaving the landing page without filling out the form. Ouch, that's a, now we've identified a program. Something's going wrong, but we don't know why.

That's where we turn to qualitative research
to get you know, the why. But today we're obviously going to focus on quantitative research, but my point is you put both together and when you have what, where and why, then you actually have a real hypothesis and you have something to start working on. So yup today, quantitative research obviously. It's gonna be a little bit simplified because I want to show you some quick Analytics tricks. One of the points being I want to show you how quickly you can do this and get awesome insight.

So my rough research process outline here basically

consists of three steps and it doesn't matter
if it's a full website or it's a landing page. It's the same approach. So first off, I'll do a walkthrough. I'll try to familiarize myself with the funnel. So if it's the landing page, I want to get through the whole funnel. I want to see the ad, I want to click on the ad, I want to land on the landing page and then I'll try to go through and do it. I call it a kind of empathetic walkthrough because I'm trying to understand the situation that the users are in. I'm trying to emphasize with the situation to understand kind of what they're going through and after that, I'll jump in and start doing some quantitative research, what and where and then I go through qualitative.

Often I will, depending on how much time I have,
I might do a little bit of quantitative first because for example if we see that you know, all the action is on mobile. That's where it's at. On mobile, that's where we see the most conversion, most users, most revenue, well then might as well not waste time right away on desktop. Also sometimes I'll have Analytics open while I'm doing my walkthrough so when I have questions, I can jump in and basically ask Analytics.

So that's kind of the way I think of Analytics also
is like my little conversion buddy. I can ask Analytics questions you know when there's stuff I don't understand or I need more insight. It's a practical way of thinking about it. So overall I'd say there's two different. Well we'll be going through a lot of the same stuff, but there's a little bit of a different approach depending on whether you know you're looking on insight on a specific landing page, you know which landing page you're gonna optimize and then you have to get a better understanding of that landing page and what goes on and then there's another kind of angle which is looking for landing pages to optimize if you're kind of like looking for opportunities.

Maybe you have a new client or you got a new job,
you can kind of do an overall analysis. We're gonna look at both. We'll start with this one when you kind of know which landing page you want to optimize. So I put together a custom landing page optimization report for you. As you can see, I'm very, very creative when it comes to naming my reports. Aagaard's custom landing page optimization report. Genius title. You have the URL there. So you don't necessarily have to get it now.

Wait afterwards.
I'll do a walkthrough of it now. The point with this one is I'm trying to make it as simple as possible. If you're an advanced Analytics user well I still think you might get a kick of this report. It kind of puts everything together in one place. Not everything, but it puts a lot of it in one place. If you're new to Analytics, this will kind of help you get through stuff quite quickly. Okie dokie. I'm just gonna show you, I'm gonna jump in and do a live walkthrough of it, but yeah I'm gonna do a live walkthrough of the report in Analytics.

For this whole webinar actually
I'm using a demo account Google Analytics to set it up so you can jump in and see real numbers and stuff without revealing all your client sensitive information. So before we jump in and do the live walkthrough of the report, I'm just gonna show you the breakdown here. So you'll see there a couple of tabs up there. So you have one landing page, device, source, second page, exit page, gender, age, device, and browser and you'll see that the metric groups here are based on sessions, bounce rate, transactions and ecommerce conversation rate.

So if you have ecommerce set up,
this will be the way it works out in the box when you download the report that I've shared the link with you. If you don't have ecommerce set up, you need to change the goals. So whatever goal is relevant for you to look at. I'd say look both at the number of completions of the goals and look at the conversion rate because you have to be a little bit careful with small sample sizes. So if you see a certain conversion rate, it makes a lot of sense to know what that is based on so you know if you have a decent sample size or what you're looking at is so small that it's not really meaningful.

If you're looking at stuff under,
well that's not always a good question, but if you're looking at something under 100 conversion type, be really careful and ideally you would want a lot more than that in every single sample. Not everybody has that luxury though. Just gonna go through now to show you the dimension fields down here real quick. So the first one, it starts with landing page. So you know which landing page you're looking for. You pick that landing page and then when you click through, you get an overview of device category and source medium and I'll show you that in more detail in just a second.

The next tab here is second page and exit page.
Well this one, it starts you off with device category, then you'll go to landing page and when you pick the landing page and click it, then you can go in and see the next page that people go to and where they exit. So I use this a lot because that's one of my main questions is what happens after people get to the landing page, where do they go, what do they do? So having the second page helps you get a better understanding of that, if there's a signal value in there. Does everybody go to pricing? Well then pricing's probably important.

Does everybody go, do a lot of users go to the home page?
Maybe they're looking for more information about you. Are they actually clicking the links you want them to click? And then also the exit page which helps you kind of understand where they end their journey. Gender and age, again, that'll start you off on device category. Again, these days it's so important to segment to device because there is a lot of difference between them. Then you go to landing page obviously, that's the one we're looking at and then you get into gender and age. So looking at gender at age I say is often important.

It gives you a better impression of
who you're talking to here, who you're marketing to and if you're a consultant for example, this can be really helpful when you start an optimization project, just having a little bit better idea, image in your mind of who you're trying to reach

and I've gotten some big surprises lately
with clients I've been working for where I had an assumption in my head about who was, for example buying on mobile and in one of the cases, I had an assumption it was like you know, a lot of young people and it actually turned it out in that case even the people buying it through mobile, most revenue was actually generated from women

of the age of 55 to 65 so that was like
a big surprise to me and it was very, very helpful because that also means that when I want to do, if I want to do you know, interviews with people in the right target audience or do visibility testing, then I have actually a really good idea of who I should ask so we can get an accurate understanding.

Device and browser, well this stuff is more exploratory.
Again, it helps you understand like which browsers are people using, what view is it if you're gonna do any Q&A testing, if you're gonna do visibility and so on, it's important to know like which view people have and also this helps you find potential bugs and errors. So I'm just gonna switch my screen real quick here so we can go through the live report.

Okay, so here we go.
So for example, let's say and again, this is Google's demo account so this is just an example

just to show you how to do this
and it'll make more sense once you start going through your own stuff or through your client's stuff. But let's look at, for example, this landing page here, an ecommerce conversion rate of 11%. That's really high, interesting. So basically you jump into it and then you have the next level here which gives you an idea of what device performance looks like. So here, it's clearly desktop where the actions at. You see we actually have a conversion rate here of 0% from mobile and tablet and also there's very, very little traffic coming through here.

So if I want to get cracking on some optimization
here pretty quickly, obviously since it's a long way to go on mobile and tablet so for me right now, this is signaling that desktop is where it's at and it's the most interesting one to look at. It doesn't necessarily have to be desktop. It depends on obviously on the use case, obviously on the website and the business case. I would say in many cases, when I looked at Analytics, we still see most action when it comes to purchase and stuff on desktop.

I've slightly been seeing more accounts
where mobile has taken over, but again, this gives you a much better understanding. So for example, if I were to do a walkthrough of these landing pages now to get a better idea of what the whole funnel looks like, I wouldn't start on mobile or tablet and start writing down a bunch of issues there, potential things to solve. I'd go straight for desktop because that's where 97% of the sessions are and that's where 100% of the conversions are. So let's jump into desktop. So now we have an idea of the conversion rate of the landing page.

That's important obviously so you know
kind of what you're trying to optimized what it's based on. You know a little bit more about devices, where the action is and what the performance looks like. And now I want to look at different, you know, sources. Where's traffic coming from to this landing page and how they're converting. So obviously it's interesting to look at the differences here. Again be careful when you're looking at small numbers here. Two conversions here, 14 sessions. Woohoo, we have a really high conversion rate, but this could change drastically with just one conversion so just be really careful.

This stuff up here is a little bit more chunky
and anyways we have a good idea that you know, the main traffic here is coming from, again, this is a demo account so don't, we're not going to read too much into what's here. What I just want to show you is how to use this, the process. So for example, we know that these two channels here, direct and this referral one here is where you know, the bulk of the action is at. Why is this important? Well it's important maybe because you could see a case where we have a bunch of traffic

coming from sources that don't convert,
maybe they shouldn't be there, maybe it's the wrong place. If you're supposed to only get traffic from one source through this landing page, it's pretty important then that you, so the landing page is made dedicated for one campaign from one source and there's other traffic keeping in there, which is hurting the conversion rate. Maybe it needs to clean that out. At least you have a better idea of what's going on now when you go through it. So let me show you a second page, exit page here.

I'll just go back to restart from the top here.
So for this one, I'm gonna start you off on device because again, there's a lot of difference between the performance here. This one gives you the overall overview of the website here of the traffic and again we're interested in desktop here. So we go to desktop. So now we've already segmented. We know there's a big difference on performance on devices so now we're gonna have a cleaner view.

So let's go into the same landing page we looked at before.
So what you're gonna see now is an overview of where people go, where users go after they land on the landing page. So not set is always gonna be there because obviously for bounce sessions, people who left the landing page, there is no second page. But otherwise, we'll see the rest here. Interesting here, we're seeing that people are going to sign in so they must be either logging on or trying to log in. It gives me important insight there.

So this looks like maybe returning users are,
there's a lot of returning users here for example, but again, knowing where people go for the second page gives you insight, it gives you deeper understanding of what they're interested in, what you know, might be some concerns and so on. Then you can click to, you know, click on any one of these and it'll show you then afterwards where people then exited from when they went to that page and again so you're piecing it together so already now, you know a lot more about the current state of affairs on the landing page.

You know device performance, you know what to look at there.
You know where people are going after the landing page. You know how they're exiting the website. So all of a sudden you're building, you know, you're getting more and more pieces of the puzzle and you're having a better understanding of what it looks like, what a real session looks like for users here. Gender and age will be the next tab here you can go through. So let's look at the conversion rate for male and female. It's almost the same here on this particular page. We have more males than females visiting.

The conversion rate is almost the same as you can see here.
So sometimes you see differences in the performance.

Sometimes you see huge differences actually
so that's important to know when you dig into it. Again it gives you just a little bit better understanding of the target audience and it's not necessarily, it's not necessarily the most important thing. It might not make a difference here, but at least it gives you a better understanding and in some cases, if you're specifically targeting a specific gender for example with your product, well then it's really important to know if that's actually going the way you want it to go. So if you look at, click in and look at male gender here, then it'll give you the next view here is a breakdown of age so again we can look at what the conversion rate looks like for different age groups here and again, this helps you understand your personas better.

So in this case, we're seeing that,
this example, I could've used a better one. We're seeing, you know, not huge sample sizes here so be really careful with this. Again, just showing an example, but here we're seeing, let's pretend we have more sessions here.

But you know, we're seeing you know,
the age group 25-34, that's where we have the highest conversion rate and you know, the lowest conversion rate we'll see from you know, 55-64. That's also where we're seeing the least sessions. So this gives you a better impression of who you're marketing to here and where there might be potential issues. Now the last one I'm gonna show you here is...

Device and browser.
So again let's start off on, why don't we start on this landing page now. We got the breakdown here of course. So the reason why it's important to break browser down by device category first and foremost is that will give you much more realistic idea about which kind of browsers people are using because they vary a lot on device. So it's important to slice it there first. Let's go through, let's look at desktop and then we're going to have operating system as the next level.

Again, it gives you a more granular look
and it's important to know, for example, you know Safari is only on Macintosh and so on so there are slight differences there and if you were just looking at browser without operating system, without device, well that will give you a very, very general view. So this gives you a much more granular view and a much better breakdown. So here we're seeing that oh interesting, there's actually a huge difference in conversion rate between Macintosh and Windows so what I'd be interested in here is I'd be interested in going through a Windows machine for example and try to understand if there's something wrong there, something buggy.

I wonder, you know, this gives me reason
to want to investigate because we're basically seeing almost the same amount of sessions. The conversion rate is 5.35 on Macintosh and it's only 0.82 on Windows. So I can dig in and try to get a better understanding here. So I funneled through Windows machine and then I start going through for example, I go through under Chrome and Firefox to try and understand if there's some bugs or something weird going on there.

And then obviously the next step here
will be your browser version. So in some cases, it's important to know what the browser version is. That will help you get really specific about doing Q&A for example on different devices.

Okay I'll jump back here to the presentation.

So with that custom report,
basically you can go that I think in 10 minutes. You can go through in less depending on how many times you've used it. So what I'm saying here, this is kind of just a sniper tactic I'd say. You can go in, you can find the landing page you want to look at when you go through these tabs and write down what you see, then you'll in no time have gained a lot of insight. You'll know the overall landing page performance, you'll know the overall device performance, you'll know the overall browser performance. You'll have stats on traffic, conversion rate, transactions and bounce rate.

You'll have insight on different sources
that are performing on that landing page. You'll know where people go after they hit the landing page and you'll know how they exit the website after they land on the landing page.

You'll have a good idea of conversion rate
performance across gender and age. So you'll have all of a sudden, a very clear idea of the conversion scenario. You'll also have maybe spotted potential bugs by going through different browsers on different devices.

Okay so now we've gone through
the custom landing page report and we have a better idea of how to get insight on specific landing page that you want to optimize. So let's look at, I'll basically go through a lot of the same things that I've showed you in the custom report. I'll just show you how to get that out of the standard reports in Google Analytics. So now we're kind of in a situation where we're looking for landing pages that we want to optimize. We're looking for inspiration for where, you know, where to conduct our optimization.

So I'm just gonna go through
some of the standard reports under audience, acquisition and behavior and I'm gonna show you how to get insight. So let's look at audience first. Well under audience, you go to demographics and then I will, one of the things I would look at as I mentioned before is age. So this will give you like the overall view of the website and how, what performance looks like here again. So yup, audience, demographics, age. It's just a few seconds to jump in there. The next one would be gender.

If you use a secondary dimension for example
on gender here like this, then you can get everything in one granular view and one thing for example that stands out to me here right away, what we're looking for here is basically outliers, things that look weird. So we're seeing a high conversion rate, the highest conversion rate for men in the age of 35 to 44 and then if we look at the next one under that, men in the age of 18 to 24, which almost gets the same amount of traffic, we're just seeing a much much lower conversion rate of 1.42.

So that to me stands out.
That seems interesting. That is reason to do some more research there or maybe we're just, maybe we should target the 18-24 year old better. Maybe we should start interviewing them or do some more research to better understand them or maybe we're actually just good at targeting people who are a little bit older. Anyway this is an outlier for me which is something we need to investigate. And again also giving you a better idea of what your kind of personas look like. You can go in and have a little look under Geo, location, which sometimes can be quite interesting especially if you're a consultant familiarizing yourself with a client's ecommerce platform for example, understanding where the countries are pretty important.

So one thing that stands out to me here for example is that
we're seeing most traffic from the United States

and then we've got India, UK, so on,
a lot of different countries coming in, but it's North America that has the highest conversion rate. That's basically where the action is at. United States and Canada. It stands out to me in that for example, the United Kingdom, we're not seeing any conversions there so again, reason to investigate a bit or at least it gives you an idea that the audience here, so we're looking at the highest converting segment that would then be, you know, young men from United States or Canada.

Again, I just want to say just to make it clear,
in this case, it turns out that the highest conversion rate was on men. I've seen many different cases as I mentioned before. There was a case where it turned out that it was women between the age of like 55-64 who were putting down the way most money. So in some cases, it can give you some good insight. The next one I just have a quick look here under behavior. Again under audience, looking at new versus returning.

So to me this one is quite interesting.
Now something stands out to me here. First of all, we have way more new users than we have returning. However, if we look at revenue on conversion rate, we see that the conversion rate is way higher for returning users and we also have way more revenue, even though we have much less traffic, it's making way more revenue based on only just about 20% of the traffic. So to me that stands out and I would do some more investigating there, try to understand why this is.

Are they logging in, is that why?
And also how can we get more returning users to come back because they're much, much more likely to convert here. Another thing it might mean is that it takes several visits for people to convert.

Under mobile, you can go into overview here
just to get some quick insight again on mobile performance. Important stuff to understand site-wide. Let's look at acquisition here real quick. So one of the things I'd look at here as one of the first thing is all traffic and then I'd look at source medium and I'll try to get a good idea of you know, different performance here. So one thing that stands out to me is that the second high volume of traffic comes from YouTube referral.

However we're seeing a pathetic
conversion rate of 0.01% here. That's not a lot. If you just compare it to direct for example, there's a big difference so that to me is kind of a dangerous signal like this is not good. If your client here for example is spending money on YouTube ads, it's not converting and it's burning money here. So we could jump in, just get a little bit understanding here. So what I've done here is I've gone into that one landing page, I've clicked it and just as a secondary dimension, I've adding landing page.

So now this gives me a view of where I've gotten the source
broken down on landing page and I can start understanding where traffic is hitting and what could be some potential issues here. Well now we have one main landing page here and it's not doing well. We have some drip traffic, they're going other places, but none of it is really converting. So what I'd do then is I'd go to that landing page and I'd start to figure out like what the hell's wrong? Is there a bug, what's going on? Is it just completely irrelevant, a completely irrelevant landing page as compared to what we saw in the ad or whatever it was that they clicked on YouTube.

Some of the danger signals,
some of the stuff I'm looking for would be, in a case like this where we'd see, for example, Facebook traffic here, we're getting you know, a good amount of traffic here. We're paying for it and we see a bounce rate of 91%. Yeah and we're seeing like two transactions. We're seeing a very low conversion rate of 0.02%. So this to me is like a monster, monster danger signal when we see something like this. People discuss bounce rate, what does it mean and is it a vanity metric.

It depends on how you use it,
but one thing for sure, if you're sending paid traffic to a landing page, you don't want a bounce rate of 90%. That means like almost all your users are just seeing that one page and then they're leaving again. That's all they do. So sometimes for a blog post or something like that, it's fine to have a high bounce rate. People got what they wanted, but if you want people to go further down the funnel yeah, a bounce rate of 91% is not good. So this to me tells me right away, we're losing money. We could make a big difference here and it might even be just a small, it might be a bug or something like that that's killing everything.

If we can unbug that, we might be able to recover
a lot of money really quickly. Last one we'll look at real quick here is behavior and I'm just gonna show you one report here really and that's under behavior, you go to site content and then you go to landing pages. So this is your overall landing page report. And again, I'm looking at things that stand out here. So for example, we have a landing page and the fifth on here, we're seeing a really high conversion rate of 13.39 and then we're seeing the YouTube one I showed before, or sorry, yes this is the YouTube stuff I showed before and we have a really really low conversion rate there.

So to me, these are two extremes
and also if you're looking at the amount of revenue here, you'll see the landing page on number two, it gets 20,000 sessions and it's made like 2,000 bucks and then you look at the one in position five, it's got 1,852 sessions, but it's made 82,000 bucks

so that's a huge difference so I wanna understand better
why is that one converting much better than the other one? Why is the other one doing so bad? It gives you an opportunity to jump in there. So basically now also you know which landing page you want to have a closer look at so you can basically just take this URL and go to your custom report that I built for you, you could pop it in there and then very quickly, you'll be able to go through the different tabs and get all the insight I showed you before. One thing I want to show you here quickly is when if you click on the landing page here in the landing page report, then the next screen, you get to have entrance paths.

This is a sneaky little report that not too many people use.
I built this into the custom report also. I just wanted to show you how you can get it from the standard reports and when you click entrance paths, this gives you the second page that people go to after the landing page and if you click that page, the second page will also show you the exit page. So for this one for example, we're seeing 44% of session are going to sign in. So that is, we also know that returning users are converting at a higher rate than new users.

So now we're starting to piece together, you know,
some pieces of the puzzle. We're saying aha, so maybe this is actually because we have a returning users on this page and we're seeing them on the sign in and then they convert higher. So again you're piecing together more and more bits and you get a better impression of what's really going on here. So sorry my voice.

So my point here is instead of just looking at
a landing page and going I wonder what's going on here is saying well the mobile revolution has happened so obviously you have to optimize mobile, you know just going on a limb and starting a split test or something or just making the landing page prettier is really, it's a very kind of superficial approach

and it's very much based on assuming
that what you're doing is right so just doing a little bit of exercises like this gives you a much, much better understanding. So all of a sudden you're like okay I know this is the device I have to focus on. I know that this is the landing page I have to focus on. I know that this is the browser that people are looking at. This is the one I have to focus on. Maybe I know that these other browsers are underperforming. I have to do more research to understand why. I know where people are going after the landing page. I know where they're exiting. I know which age I have to look at.

I know what gender and so on.
So all of a sudden, you have all this insight that just helps you make a lot better decisions. So again, I said time spend one hour, one hour tops.

You can do it quicker than that too
depending on which point of view and again, just a quick summery here, the insights you can get. Overall landing page performance, overall device performance, overall browsing performance, traffic, conversion rate, transactions, bounce rate, all that stuff is really important to know before you start optimizing and testing. You need to know what you're trying to make better before you can make it better and you have insight on different sources, on the second page, peak performance, exit page, gender, age and also you have a good idea of what potential bugs you might have fixed. One note on bugs.

I think in many cases here,
this isn't really seen as part of optimization, you know. A lot of people think it has to be a split test for example before there's any value in it. I say that's absolutely wrong. Part of your job as an optimizer is to find stuff like that. One of the points being you could spend a lot of time trying to optimize a landing page and not get anywhere because the problem might trigger down the tunnel. People can't check out for example or maybe there's a bug in the main mobile browser that people are using.

So you have to understand that, you have to unplug that
in order to kind of open the gates and then you can start seeing results from the landing page optimization you're doing. So you really need to have a much better deeper understanding of the whole funnel before it really makes sense to start optimizing and start running tests. Again, people have a tendency to say this takes too long, it's too complicated. I say you're investing time upfront and that'll save you a lot of time down the line because otherwise you're relying on gut feeling and guess what? Sometimes that works and it's great.

You know, you were right.
In the first case, you tested and it looks like it works. The problem is when you're not right. What do you do then? Well then you're left at just basically at zero. You're left to your own devices and you have to figure out oh I wonder why it didn't work when you have all this insight then even if the tests didn't work, but then you have very, very clear idea of why. You have a much more refined hypothesis and then also you can say okay, so this documented approach didn't work.

Let's do this instead.
Real quick, just want to go through the simplified kind of approach to research here. I do start with a walkthrough, familiarizing myself with it. I wanna see the ad, I wanna click the ad, I want to land on the landing page. I want to try to go through the whole thing. If it's ecommerce for example, I'm gonna go through the whole funnel. I'm gonna make notes. I'm not trying to be a marketing expert or seer while I'm doing that. I'm just trying to be a normal human being. I'm trying to understand where, do I get confused or do I feel pain in my brain or whatever.

Where do I get frustrated,
where do I see issues that are hard to get through? Now I jump in and I start doing quantitative research. I just showed you how quickly you can do that and then after that, then you would turn into qualitative research so all of this is really important. Today I only showed you a little bit of it and obviously this is a free webinar and I give you the custom report here that you can download and start using on your own website, but what I wanted today is obviously there's a much bigger process here and one of the reasons why we're doing this free webinar here which obviously stands alone, but it's also to make you aware of a landing page course for CXL Institute and we're kicking it off next week.

It's eight lessons over four weeks starting June 5th.
There's two URLs here. The shortened one will get you straight to the landing page here or otherwise you can go to the CXL Institute here and check it out. So what I'll be doing in these eight lessons is basically taking you through the whole process. So we'll be looking at understanding the whole landing page scenario, the whole landing page experience, the whole funnel. We'll be talking about the psychology, neuroscience, wire frame and copywriting, design, qualitative research, quantitative research and then we'll be putting all of it together so if you're interested in you know, learning a lot more about landing page optimization, the whole process, yeah I will invite you to take the course.

It's a live course so we'll be doing
live lessons for each one. Okay thank you, very very much for watching. I appreciate it and I think we might have a little bit of time for some Q&A here.

I think I got a question here.

Hmm, I'm not sure I quite understand this question.
Which method is better, advertise by category or make a landing page and try to optimize it? I actually don't understand the question here. I think you need both. I mean when you start doing an ad campaign, you'll obviously need a landing page from the beginning and then I would try to go through and try to get as much insight as possible as I was showing you now the more general stuff, not the custom report and get a much better idea of what's going on right now.

What does it look like and then from there,
I try to build the best possible landing page with the insight I have and then from there, I'd start optimizing and so researching, you keep on doing research basically forever. Never stop.

Yeah, sampling yes. Sampling is an issue, it's hell. I hate it. It is a problem. I don't have a good solution for it other than paying for Google Analytics. There's APIs obviously that can pull the data and try to avoid sampling. You can Google that. There's a bunch of different ones. I believe that Charles Meaden has one of the really good ones there.

Kern used to have a good API tool.
It'll make everything a bit more complicated. You can get the same data, but you can pull it right in the API and try to avoid sampling, but sampling is an issue and you have to be careful. When you're looking at data like that, then yeah just really look at how much the sampling is and if it's a 30% sampling rate, you have to be careful. You have to take it with a grain of salt, but on the other hand, what I say with some of the Analytics stuff here is sometimes you're trying to get signal, signal value so you don't have to see this as the Holy Grail and the eternal truth, but you're trying to get some signal values when you're going through it.

You're trying to understand
maybe just some ballpark numbers. How does Google know the gender? Okay yeah that's a good question. So for demographics, you have to be careful. Some of it you have to be careful with interests and so on, but Google pulls a lot of information from, for example being logged in to different accounts and so on so they have a pretty accurate representation of gender and age. Now we have GDPR so we'll see how long we'll be able to get that data, but we have it right now. You will get a recorded version of the webinar.

You'll get the slide deck too.
Why am I tracking sessions, why am I tracking sessions and not users? Okay that's a good question. Well because most of the stuff I've been showing you is session-based reports. When you look at landing pages and you look at ecommerce conversion rate, both of those are session-based reports. If you do a custom report with landing page numbers and you use users as a main metric, you have to be really really careful because then it's gonna give you a distorted view.

That's one of the things in Analytics
that you know can confuse people which is worth reading up on what is the difference between user sessions and page views. I would prefer if everything was based on users. That's one of the reasons why I like Kissmetrics because it's basically a user-based analytics program.

It gives you a whole, whole plethora of other things
that are frustrating and Google Analytics is frustrating in its own way so it's, we don't have perfect analytic tools yet, but obviously there's some use where it's better to use page or user data.

Yes, yeah, yeah. The presentation is shared. You got the URL in there so you can quickly get it and the report, yeah. The report is there. Okay yeah, which time span do you select when you do this kind of analysis? One month, one year? Well it depends on a couple of different things. It depends on how much traffic you have obviously and like you're saying, you're trying to avoid sampling so it has to be meaningful obviously. So I wouldn't just look at a couple of days. That's really dangerous.

Probably wouldn't look at a week.
I'd try to look at a month, but then again in some cases you wanna, like if you're looking at several months, you just want to make sure that what you're seeing makes sense. So you might want to do a little double check and see was this traffic consistent over the whole month I'm looking at or was there a peak? If there's like just this one campaign flip, then you have to be careful. Also if you're doing it a little bit more advanced in the sense that you're doing pre-calculations to figure out how long to run a split test of which landing pages there are actually traffic to and to work with consistently one to make sure there's not just this one little blip, you want to make sure that traffic's also going to be there going forward.

But it really does depend and in some cases,
you might on low-traffic website, you have to go to a much longer period to get you know data that's really meaningful. So it can become a bit tricky. So it really does depend.

Yeah and obviously like you said here,
avoid sampling and try to pick an average month obviously.

Revenue value position precision.
Depends on how you set it up. If you set it up, it could give you a good impression. If you see a discrepancy there. It's not the main metric I look at, but it's another one of those things that give you too. It kind of depends on the scenario and also your client Do you think it's better in order to report SEO campaigns to take this metric or is it better to report page views?

Yeah so it depends on what kind of report you're using.
So I would, one of the cool things about Google Analytics is that because of Google products, you can Google a lot of answers and there are so many guides out there and even Google's own documentation. So I think it depends on what you're looking at and also depends on what you're interested in seeing and it depends on you know whether it's a blog or an ecommerce website and it also depends on your profits and what you've agreed with your client. I would say in many cases users and sessions are the most valuable, but again I don't do a lot of SEO so I have to be careful with what I'm saying.

There's a moonshine in that jar.
Obviously, that's why I'm speaking so fast. Okay let's do just a couple more questions.

How to analyze landing page in one hour.
Do zero for 10 years, step two hm and profit. So yeah maybe he's making fun of me, maybe it's a critique that this is not very actionable because you have to do it for 10 years for any of this to make sense. I'd love to get some feedback on that. Are these metrics important for SEO too? Well as I said before, I'm not an SEO guy. I don't know a lot about it, but I'd say a lot of these are important as far as you know figuring out you know, you can use a lot of this stuff

as well for your SEO purposes if you want
to figure out which landing page does it actually make sense to drive traffic to, what kind of content, you can get a lot of inspiration from looking at some of the ad campaigns.

Can you show how you built that entrance path?
So when I showed you the out of the box landing page report, it's there. You just basically click the landing page and then you'll see an entrance path. You just click that. In the custom report, I recreated that. If you download the custom report and just click edit, it'll show you and it'll show you how I set it up there. Are there any good resources on how to use the behavior flow report? I would just Google it.

I know Craig Sullivan, my good friend and mentor,
he talks a lot about that so maybe you could, he's done a bunch of content on Medium so you could for example search Craig Sullivan GA Behavior Flow or something like that. You'll find something there.

Okay, thank you Paul.
I wasn't making fun of you, quite the opposite. Well thank you very much, that's very nice of you. I appreciate it. Okay so let's see.

Alright so we're almost done here.
There's some feedback from Anthony. I'm seeing great stuff straightaway with this report. Thanks. Awesome, thank you so much guys. Thank you very much for joining. Thank you very much for being part of this. You know, feel free to reach out to me and here's some of my contact information. I know this looks like an amateur email. I left the company I was working for not too long ago. This was going to be a temporary email, but now it ended up being my permanent one. Never mind that.

So please, you know, reach out to me
if you have any questions about this stuff. If you start using the report, and you see some good or bad results, please, I'd love to hear some feedback and one last time, check out the course if you want to learn more about this. Thank you very much. Have a fantastic weekend.

Michael Aagaard, Senior Conversion Optimizer, International Keynote Speaker & Speaker Coach will teach you how to get critical insight from Google Analytics in just one hour with 7 simple reports.

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About Michael Aagaard

Michael Aagaard has been a full-time CRO since 2008 and has helped companies all over the world improve their online businesses. He has worked with everything from SaaS to non-profit and has experience as an external consultant and as an in-house conversion optimizer.

Michael’s approach to CRO revolves around user research and consumer psychology. He is a sought-after international keynote speaker and is generally known as one of the most passionate and enthusiastic people in the industry.