Out of the box, Google Analytics lacks real insight and it's difficult to precisely identify bottlenecks and highlight where real growth opportunities lie in your web properties.
In my talk, I'm going to walk you through some must-have Google Analytics customisations you should add to your web properties, and precisely how I identified a conversion black hole that once fixed, increased revenue by £30k per day virtually overnight.
We'll be using e-commerce as a lens, but these are key lessons for any marketer who cares about conversions.
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Nominal intro. Right. First question. Can everybody hear me loud and clear? Yeah. Alright. One person says no. All right. Hearing aid, just a little bit. All right. Well, it's great to be here in Scotland. Of course, it's fantastic. But look, I'm going to start with a really difficult and uncomfortable question for everybody first.
For anyone who isn't black in the audience, if you'd be happy to be treated the way a black person or black people are treated in society today, can you do me a favor and please stand up? Okay. No one stands up. So my point I'm trying to make is being black is difficult at the moment.
It's been difficult for a long time. But to make this actually more positive, because I get that's pretty difficult, I love the fact, in fact, this is the most comfortable conference that I've attended and spoken at so far. Actually, the touring team, Brian, and everybody else has been fantastic in making me feel really quite welcome.
The diversity tickets has been fantastic. It's been phenomenal to see that happen. And on top of that as well, I had a really open conversation with Brian about diversity and being black and a speaker and everything else. It was great. So I'd just like to give a massive round of applause to Turing, to Brian, the entire team. I think it was great.
Thank you very much for doing that. And then I've got one more thing that I'll get to in a minute, but we've to talk about Google Analytics, of course. That's the important stuff. That's why we're here today. So who am I? Well, yeah, I'm Luke Carthy.
I had an incredible intro, so thank you very much. And I want to talk to you about Google Analytics. Now I'm an ecommerce consultant, and I want to share a story with you. But before I do that, I want to introduce you to a really special person.
This is my little girl. Her name is Ava, and she's soon to be four years old. It's her birthday soon. I'd love a massive favour if I can ask you to. Can you all just shout happy birthday Eva for me? And then I can send it to her, and it will absolutely make her day.
So yes, I appreciate. It's free labour, but I hope you're okay with that. After let me get my phone out first. That'd be important. Right. One sec. Right. Okay. After three if no one does it, I'm coming for you. I'm telling you. Right.
After three. One, two, three. Happy birthday, girl. You are. There's your little face. See? Right. Thank you very much. That's all the emotional stuff, Dan. We can get on to the stuff you came for. That was brilliant. Thank you. So the story. The I can't replicate I'm on the right slide, right? Yeah.
I can't replicate the issue, so I'm closing the ticket story. Now anyone who works with devs, in devs, has spoken with devs know the ticket is a thing, right? So here is your angry customer, aka Jeremy Corbyn, and he's pissed. He's so annoyed because he can't spend money.
He can't do it. He's finding it really difficult. He's got money in his account. He's ready to buy. There's no money. No, he's got money. He just can't spend it. I need to introduce you to two more people to complete this. So we have Dave and we have Lucille.
Now depending on how good these screens are, you might see some watermarks on it, and it's because I'm too tight to buy the licenses to these images, so I'll just copy them off Google. I'm so sorry. But anyway, back to the story. So who is Dave?
Well, Dave is a digital manager like many of us here today or many people that you work with. He uses Google Analytics on a daily basis and he's an enhanced e commerce wizard. It's what he does. It's what he loves to do. But there's a challenge for Dave because he uses out of the box Google Analytics, which so many of us do as people in the business, right?
So Dave has an issue in the sense of it's cool at telling Dave about the sales that his company has won and who he works with, but it's not great at telling Dave about the insights the sales have missed and precisely why. So we've all probably seen this report before.
If you work in e commerce or even if not, in funnels and that sort of thing in goals, this is familiar. And we spend ages looking at this ****, trying to work out what the hell it's trying to tell us. We see these massive falls off, and then we go down rabbit holes to try and understand and identify what the hell is going on.
So the problem is, Dave, these insights, these things, these indicators, they only give him information, tidbits, insights that don't give him solid proof. And that's a problem because I think I have a hunch I believe does not get prioritized. Now I want to introduce you to another person, Lucille.
She's also a digital manager. She uses GA frequently, but she's gone way beyond the out of the box configuration, right? She's doing things. So Lucille can get to that sweet, solid proof in Google Analytics really, really quickly and attach even more high resolution data to strengthen her findings.
This is what this is all about, which means Lucille has those killer stats straight away that the board simply can't ignore, right? She's a force to be reckoned with. She's brilliant. She does all this great stuff. So Lucille's able to get her tickets, her problems prioritized higher and closed faster.
She's saving the devs a huge amount of time and resources, and I've got to say, she's also pinpointing the exact issue, which is really, really good to see. So instead of looking at this and going down these rabbit holes, she's looking at stuff like this, error messages, which we capture in Google Analytics and attach some really cool information to them as well.
So going back to my story for a second, remember Jeremy Corbyn's face when he was pissed off? This is what Jeremy Corbyn was seeing when he was buying from a particular website. Payment failed error one thousand and seven. Please contact SalesOn. It's pointless.
He's ready to hand over his money. He spent half an hour adding stuff to his basket only to get to the last stage, and he's seen this. It's a problem. So when we took a look, we saw this in GA. This is what that error means.
One thousand seven, this is what this error means. The card number has failed our validity checks, blah, blah, blah, blah, It's invalid. Basically, incorrect card number. That's the problem. So check, retry, see what's going on. As a result of just simply changing the copy from payment failed, error one thousand and seven, to invalid card number, please check and retry, an immediate thirty thousand pounds a day uplift in sales just from changing something really quite small.
So the point I'm trying to make to you here is we're not trying to change the world. I mean that would be great if we could, but really it starts with small minute problems that could be really getting in the way of people converting, whether that's e commerce, whether it's SaaS, whatever it is that you consider a conversion, this is going to be informative.
So what I'm going to teach you and talk through today is how to build a really badass rig just like Lucille. First thing, let's talk about custom definitions and what they are and why they are so awesome. Now as a consultant, I obviously charge money to do stuff, and this is the stuff that I do that justifies why I'm a consultant and the fee that I charge.
It's powerful stuff. So what they allow you to do is send bespoke data to Google Analytics, the stuff that isn't collected by default or collect the default stuff in a different way. Now custom dimensions can be applied to almost any data set in Google Analytics, And here's an example.
Now I appreciate some of these are probably questionable in the era of GDPR, but this was a screenshot that was taken a handful of years ago. So don't come after me because we're not doing this anymore. But in a world where we were, this is already helpful to identify specific individuals or companies.
This was a B2B client of mine, and it really allowed us to help. This is actually the client where the GBP thirty thousand uplift came from. So can see this here, custom dimensions. Once you've got them built, you can access them as secondary dimensions in any of your reports, which is good to see.
You can also create custom reports as well. So if anyone is using this or even in Data Studio as well, if that's something you'd like to use, you can go away and do that. Now plenty of opportunities here. You can add them as the example that you can see there.
And I'm not going to do a tutorial in terms of showing you how to build those custom dimensions. We're going to be talking through what custom dimensions, definitions and metrics you can build. But I've got some links at the end of this that you can take, which will help you if that's something that's going be of interest to you.
I've only got half an hour, unfortunately. Capturing error messages in GA. So we've used this as an example, and this is really, really powerful. I want to explain to you why. First thing, identifying how many times every single error message fires that's visible to a user, the specific text, and precisely on what page it happened.
It's really powerful stuff. You can capture that with just that custom dimension. What errors are firing at the checkout and how many visitors are seeing them? So that's another use case where we can start to capture information. So if you've got any field validation issues, if you're in a situation where you've got abandonment and you're trying to understand why, it an error message?
Is it a notification? Is it unclear copy? Something should be shown that's not been shown. Are there that could be rewritten to improve UX or CRO? Right? So these are the small things that could be changed on a granular level to make a massive difference to conversion.
Now, what pages display the most errors? And this is how I like to start. And for me, in the world of e commerce, it's normally to check out, but of course, it could be anywhere. It could be your landing page. It could be your inquiry forms.
It could be anything. It could be your onboarding model, whatever that might be. But what pages display the most errors? And what errors are hurting conversion the most? So here's a custom report I built for a client using that error message custom dimension.
So you can see here, depending on how good your eyes are, we've got some error messages here, we've got hits, and we've got users. And the first error message that is seen in terms of the number of hits is, sorry, unrecognized username or password.
Have you forgotten your password? How many times as users, whether we're trying to log into something, whether it's Netflix or whatever, have we got that infuriation of having to go to the effort of resetting your password, remembering your email address just to go and buy something.
So my challenge to this client was just put checkout on, mate. Just switch guest checkout on because we have the proof. We can see it here. But what's really interesting here, actually, my slide's completely battered and messed up, but we're going to continue anyway.
I think they're in the wrong order. But capturing lost basket value in Google Analytics. So Google Analytics isn't great at reporting the sales. You've lost I've already said this slide. Yes. Something's kind of wrong, but we're going to freestyle it and make it work.
Where do we lose the most potential sales? This is interesting. Alright. Improv. Let's bring it out. So lost basket value. Let's explain exactly what that is. So lost basket value allows you to understand how many sales you're losing as a result of issues on the website, which is good to know.
So there might be a number of events. It could be the error message. It could be contact forms. But I want to quickly explain to you how the lost basket revenue metric works. So when a customer is adding items to a basket or going through a funnel, what you do is you increment the basket total as they go through.
So they add something for ten pounds Your lost basket value dimension updates to ten pounds If they decide to abandon or relieve that session or leave it, the loss basket value is set at ten pounds But if they make a purchase, it's set at zero.
What's going to happen at that point is every single event that happened up to that loss basket value beyond zero will be captured, and you can start to understand and attribute whether that error message was part of it and start to prove the value and the amount of money that you're losing in your particular business.
So where do we lose the most potential sales? That's the important thing about lost basket value and allows you to understand that. But what does slow website performance cost us and how much cash are we losing specifically to that error message? So let's show you.
So this particular error message here, error message, sorry, unrecognized username or password, have you forgotten your password? For one month, it cost them a potential one hundred and eighty seven thousand pounds Now if you take that to your board, you take that to your client, people start to pay attention.
It's gone from an intangible error to something that's now physically costing your client money, and that's what helps you to get this problem prioritized. All of a sudden, it's gone from not very important to why haven't we fixed it yet, right? And that's a great place to be.
So I've already explained this, so I'm going to move on to the next slide. So here's another thing that I think is really powerful if you're in the e commerce vertical, which is capturing product status in Google Analytics. And what do I mean by this?
So in the world of e commerce, of course, if you land on a product page, we want to understand whether the item is well stocked, poorly stocked, whether we've got some stock or not. That's what we're interested in. But we can start to answer questions like this.
Is zero stop the specific reason why sales were low for specific lines? So we've all been in there, whether you're in the world of e commerce or not. You sit down in these meetings. Can we understand why this particular item, product, virtual item, has decreased in sales?
Now what's really powerful to be able to do is to sit in those meetings and say, well, yes, it's because we don't have any stock. And it can be that simple rather than this whole rabbit hole of hypothesis as to why sales may have dropped.
Is it condition based? Is it an SEO situation? Is there a lack of traffic? Is it merchandising? Have we changed the home page? No. It's just not in stock. That's why we're not selling it. When an item has low stock, how does it impact conversion?
Right? Powerful question. Because normally what happens for the research I've done for my clients is low stock increases conversion because it's that sense of urgency, immediacy, especially right now where stock is a real challenge for a lot of people, a lot of people in business, right?
How does low stock impact conversion? So a small tip that you could take away from this potentially is if you, let's say, you have a low stock threshold of three units, switch it up to five, see what happens. Maybe you'll increase your conversion. Try it.
Small close test. Don't take this away and do it literally, but it's worked for a couple of clients in the past before. Right. Capturing promotional statuses in Google Analytics. This is really powerful as well. So how does a price reduction impact sales and conversion?
Does a three for two or onethree work better? Same discount when you think about it, but obviously a three for two, greater AOV, more items sold at a transaction or onethree off. What's more effective? You can measure that by capturing that as a custom dimension in Google Analytics and then storing it alongside all your other data.
But there are a few bad things about custom definitions, and that is once you set them up, they can't be deleted, which is a real pain in the ass, let me tell you. So you also only have a max of twenty of them, which isn't great.
So you've already got probably maybe five or six ideas. You're twenty five percent of the way through. There's a problem. So when you're here, right, you've got one left, ****** gonna get real. Well, the good news is when custom definitions get ugly, then events get really, really sexy.
Or maybe I'm just weird. I don't know. But either way, there's no limit on the number of events that you can have as far as I'm aware, at least. But there are nuanced differences between custom definitions and events. One of those is custom definitions will tell you the what, and events will tell you the when.
And that's how I like to kind of think of things. So to give you an example, if anyone wants to take a picture of this, it might be helpful. I'm not going to explain through all of these because we haven't got the time.
But these are some example dimensions, some example metrics, and then some example events. So an event could be when a purchase has happened, and a dimension is kind of what was it that they particularly purchased. So there's a bit of flexibility there to help you to stretch out that twenty limit that you have.
But there's no hard and fast rules. It's completely flexible and manual to your particular use cases. But events can also be used to power goals, and custom dimensions cannot. This may change. GA4 may bring a completely different nuance to this altogether, but in Universal Analytics, this is typically how it works.
Now there are some differences. Custom dimensions, you have your definition name and then your value for that particular, whether it's text or numeric. And then your events, you have, again, in Universal Analytics, your category, action, label, and your value. And they are kind of the key distinctions in terms of how you would build these things.
So we've already jumped through this slide, so I'm going to continue. But here's an example of an event that I've built for a client, which is logged in status and two weeks integrated. Now to walk you through this, logged in status is really important for me as a consultant because I want to understand when you add guest checkout, how many people are actually logging in to complete a purchase because that allows me to understand, is it worthwhile investing in wish lists?
Is it worthwhile investing in Logging experience. If only a third of people who are completing purchases are logging in, the answer is probably it's a lesser priority. Integrator for this client, if that ever goes offline, to be frank, we're ******, right? But no one's ever been able to prove it.
So the great thing about this is as soon as we get integrated as a status of no, I know straight away that it's costing the client money. All of a sudden, the devs say, we'll get to it, show them this, attribute it to the lost basket revenue, it's fixed by the end of the day.
Really important stuff. So here's an example. Fire an event when searches return no result. I particularly love this one. I think it's brilliant. So ao dot com, I just wanted to mess about, search for this, and see if anything came up. Of course, nothing did, but imagine how powerful this is in context.
Someone goes to AO, searches for a bunch of stuff that they're looking to buy, it's not there. Now we know for a fact that people convert a heck of a lot stronger when they use site search versus people that do not. So if you're finding opportunities for people that are searching for things and you don't have a product, don't have a service or a solution, there you go.
Right there. So you can find an event that looks just like this. Category site search, action, no results, label, search term. And then you have a very quick report of all the things that people are searching for that you don't have an answer for.
So I have a client who works in a space of network infrastructure, and a lot of people were searching for rack shelves. They built cabinets, they built rack units and everything else, but no rack shelves. So guess what? They had about, I don't know, eighty searches a week for rack shelves, but no results.
Very quickly, you build a product, you find a demand, and you build the supply. Nice and simple. So you can confidently answer questions like this. What items what are the items that customers are looking for that we simply don't sell? There's opportunities here to immediately potentially fix it.
Now here's a question for you. Does anyone know what this says? Everyone's scared. Everyone's so scared. It's not a race question. I promise. Right. Does anyone think there's an l in this? Aluwa. Alright. Cool. Cool. Cool. Cool. So for context, you're wrong. But for context, this is the world's second largest manufacturer of security cameras, if anyone cares.
Top tip. Or fact, you can bring up at a party, whatever. But the point is, there's no l in this. It's actually DAHUA. It's d a h u a. But my point here is permutation, how people interpret different things. So these are all the misspellings that we captured in GA as a result of people trying to get to this brand.
Right? We've got Dalla, Allawa, Dalla, and so on. They're all really important. This is how it's spelled. This is how you say it. It's a mess. It's a mess. And then we've got day one. Don't even get me started on this one. Anyway, moving on.
What misspellings are we not optimizing and how often are they searched? Just as we've shown you in that example. What non commerce queries are our customers searching for? Returns policy, how do I, questions, FAQs, Black Friday. It's coming. You know it's coming. Right.
You can take this further than just search too. Flag all empty categories, whether it's categories of content, whether it's your knowledge base, your resources, your products, whatever it is, flag empty categories. So here is The Home Depot. They have hundreds of these, hundreds of categories that are completely empty and devoid of products, which is really, really powerful when you think about it because if you've got lots of empty categories, whether it's due to seasonality, due to availability, stock, things moving around, merchandising teams, it's all there.
You can all switch things around and take care of it. Lastly, I just want to give a shout out to Nathan Aymory. He's probably not here, to be honest, if he is. We'll go for a beer, but I'm pretty sure he's not here.
But he has taken all of this presentation and built a really powerful Google Data Studio that tells him every single error message that fires on his site and how much money it's costing him. And as a result of that, I mean, I take my hat off to the guy. He's brilliant.
He's done better than what even I've done, so fantastic. But I just want you to take that as inspiration as to what you can do with custom definitions and custom dimensions in Google Analytics. And here it is. So here are the links. If anyone's interested and wants to take a picture, these are the resources that are going to help you out.
I'll let you do it. I'll let you do it. I'll give you a minute. Last but not least, be more Lucille. Actually, last thing I want to finish on as well, to be honest, I have a newsletter where I talk about a bunch of stuff from e commerce to just CRO and UX and all sorts of good stuff.
I don't have that hideous beard anymore, but the content is still great. That was my lockdown phase, so things have changed a little bit now. But I welcome you to subscribe if you're interested in what I talk about, ecommerce, growth, CRO. It's all there. But thank you very much.
