Aside from Facebook audiences, Dimitris Skiadas will take you through a specific example of how tweaking Google Analytics made one client $136,624.87 in 1 month, simply by analysing his store’s data & using them to target the best-converting Facebook audiences.
Targeting by geographical location, specific mobile devices & tagging FB ads were the ingredients to a massive increase in revenue and conversion rate.
Speech by Dimitris Skiadas | E-commerce Strategist
Dimitris Skiadas Speech Transcript
What’s up, Berlin! Everybody’s sleeping? Everybody’s sleeping?
Come on let me hear you!
I came all the way from — Yeah that’s what I like!
Oh, my mug looks pretty ugly over there.
Tweaking Google Analytics
Let me, take some time, tweaking google analytics for e-commerce.
Today I’m going to introduce you to a case study that’s really, really boring. So I have some nude pics for you guys and some nude pics for the girls.
I’m just kidding.
Anyway, who here does analytics? Who does e-commerce? Anyone?
Today I’m going to present a real case study. I worked with a client and how we made $136,600 something in 30 days only by tweaking analytics. We didn’t do anything else.
We just took the data. And we took advantage of them in order to scale his business even further.
Is everyone excited? Yay! Awesome.
My name is Dimitri Skiadas. This is a picture of me with Gary Vaynerchuk. And, I usually use his face over here in live presentations that I do because I need to keep reminding myself how grateful and lucky I am to be in this business.
Imagine this, right now, you could be in a really, really boring office having someone to shout over your head.
“Where are the sales? And, where the telephone? Blah blah blah.”
So we are really, really lucky.
I would like you to give yourself a round of applause for being right here. Give yourself a round of applause for being here.
Follow Your Dreams
Okay. Because you are following your dreams. And, all these kinds of things, you know, all the techniques, will change. Everything you know today will change.
This is one of the things that I learned from Gary. This is why I’m saying that only your mindset will remain.
We have only one life to live so make sure you make the most out of it.
Who is Dimitris Skiadas
Okay, so I’m Greek, born and raised in Greece.
Any Greeks in the house? Just 2 people over there? Okay, we’re a small country.
I’ve been an e-commerce strategist since 2010, a Google Analytics expert, a trainer and public speaker.
Public speaker? I’ve done maybe 3 or 4 public speaking but I like the title.
Anyway, all jokes aside, what you should really care about if you’re into e-commerce and what you should know about me is that I’ve already helped more than 50 plus owners, one-on-one, to scale their e-commerce businesses to 7-8 figures.
So, I know what I’m talking about.
I have no idea about affiliate marketing, don’t ask me anything. But if you’re all about e-commerce, I’m your guy.
Who loves Google Analytics? Anyone? Oh, you liars. Nobody loves Google Analytics.
All we care about is the money, right?
I’ll show you today a way how to make money inside Google Analytics because there is money to be made.
I know this is a bold statement but I can tell you right now that you can scale your business to millions only by using Google Analytics, and some luck.
Case Study: Shopify Store Selling Beauty Products For Women
So, what is the case? There’s a Shopify store that I used to work with that started in October 2016.
He was selling beauty products, and I’m really, really sure that you must know the one product. It was this black mask. It really brought 80% of the total revenue, it came from that one product.
There were 2 guys that were already doing a good job. The average monthly revenue was about $60,000 but they couldn’t scale even further.
Everything that they tried, you know, lookalike Facebook audience, uploading custom Facebook audience, whatever they tried didn’t end well.
What we did is that we took a look at their analytics and decided to make some strategic moves on how to move even further scaling.
The partnership, unfortunately, didn’t end really well, so we didn’t conquer the world. And I really, really mean this. I really, really believe that if you work, if you know your numbers, you really, really have a serious business, and you know what you are doing.
Optimising Store For Speed
This is what we did. Number one, optimising the store for speed.
Okay, I can’t even stress how important it is to optimise your store for speed because 1 out of 4 users, like 25% of your users, will abandon your web page that takes more than 4 seconds.
4, 3, 2, 1, boom. Gone.
So, what we did is we used Google Analytics, of course. So we went ahead and saw how much was the average loading time of the site.
And, we used a tool called PageSpeed Insights to improve what I’m about to show you. So, that was the average time, like 8 seconds, it was a lot.
We realised that 40%, 45%, I don’t remember the numbers correctly, but I think 45% of the users just bounced immediately.
If you’re using analytics, this is the path in Google Analytics you have to go to.
Behaviour, Site Speed, and Overview.
And, this is the Page Speed Insights tool. I know that some of them are in Greek. I didn’t know how to change the language.
Anyway, but what you do is, here I took an example. I took amazon.com, here where it says analysis, it means to analyse.
You see that Amazon, I don’t know how to explain that, but Amazon seems like a really poor experience in mobile, so 62%. And here you can see that it tells you exactly where and what you need to optimise.
The same thing happens with desktop computers. You see 55% and you see it tells you that you need to optimise your images CSS and all that kind of stuff.
I actually have no idea how to do that.
What we did is we hired the programmer and the page load time from 8 seconds became 2 seconds.
That was super important. Because right now, 25% of the traffic that you’re sending is gone, it’s completely wasted.
Tagging and Tracking Facebook Ads
Number two, tagging and tracking our Facebook ads, which was our main traffic source.
I can sense that in your head right now, “What the hell is tagging? What the hell is tagging?”
Let me give you an example. Here let’s say that I have mystore.com and I’m selling some yoga pants.
All the things that you see right there, the UTM source, UTM medium, all these UTM codes that you see right there is that we show to analytics where does our traffic come from.
The source is always gonna be Facebook. The medium is always gonna be CPC because we know that it’s paid advertising.
The content, let’s say that you have a specific ad set, and don’t worry if you don’t get it right at once, it’s a little bit difficult of a concept but it’s super important and that’s why I decided to include that.
Let’s say you have a specific ad set that you’re targeting. Male, 25 to 34. You’re targeting them on mobile.
And let’s say that you have a website conversion ad and let’s say that you’re optimising for Add to Cart.
The campaign is yoga pants.
So what you will do is that you will take on every ad set that you make, and you will take the whole URL, but I will show you how to do it almost automatically.
You will insert it as, instead of your normal URL, mystore.com/yogapants, you will take this whole thing.
What this thing will do is it will magically appear on the analytics.
GA URL Builder
So what we did, the tool that you used Google Analytics.
And we have a tool called the Google Analytics URL builder, which is a Chrome extension and does all the thing, automatically.
What you do is you have in the URL to share, mystore.com/yogapants.
Source, Facebook, medium, CPC, content whatever that is or whatever the naming that makes sense for you.
And, here on the final URL, you take it and it’s ready to use.
I know it sucks, I know. I’ve done it hundreds of thousands of times and all hundreds of thousands of times it sucked.
But it’s really important to know your numbers and to scale properly.
GA Path: Acquisition – Campaigns – All campaigns
In order to find the path inside Google Analytics, the GA path is Acquisition, Campaigns, All campaigns.
Just remember, the slides right now it doesn’t make too much sense but when you are inside analytics, you will remember what the Greek guy said.
Here, this is the face mask, you can see the total of the sessions. This was one in less than 30 days.
So you see, if I click, I have everything the source, medium, Facebook and you see videowc, videoppe. Some things they didn’t listen to me exactly, so they did it on their own way but still it didn’t matter because if you click on the very first Facebook videowc, which made $78,000, and you go into a secondary dimension, ad content, it will bring you all the assets from Facebook.
You can see exactly see that gay men, US, age 18-35, brought in the biggest revenue.
So we had no idea because we were advertising only to women at first but then we realised by trying some gay interests, we realised that it was the best-selling Facebook audience.
Everyone excited by what I’m saying? Or shall I go could drink some beer?
Yeah okay. Pretty much excited.
Scaling Based on the Location of User
Okay, so scaling based on the location of the user.
Most of the people, what they do, they target the United States, the whole United States, that’s it.
But you’re losing so much traffic. You’re losing so much, so many conversions.
GA Path: Audience – Geo – Location
Because if you go inside Google Analytics, and you see audience, geo, location, you will see that right here, the United States was the majority of the traffic. We had a majority of the revenue and we had the biggest, not the biggest conversion rate but we have like 3% conversion rate.
But what do you know?
If you go to Australia, for example, which is only less than 10,000 sessions, you see that the conversion rate is 6%.
If you want to take it a step further, you have to go, you can click, for example, in the United States, you can see specific states at this time.
So you can see, for example, that Michigan, it doesn’t convert that well compared to California for example.
Or you know exactly, which are the specific states that convert the best. So you can go ahead and exclude those ones that don’t work or remove them to take onto another ad set.
If you want to take it in a step further, you can even go and have specific cities. Because this is what happens, we know, okay, United States, let’s target California.
But California can be, I don’t know how many but like 10-15 million people.
All of them are not the same. And all of them, all people in California, women 35-54 are not the same.
So, use Google Analytics although they’re fucking boring, I’m sorry about swearing. Freaking boring.
But use them in order to identify better your audience.
So what we did is it took a lot of work, but it was really, really worth it because we were able to double the revenue that we were making only by using analytics.
We didn’t raise the budget. We didn’t do anything more than that.
Scaling Based on Mobile/Desktop Conversion Rate
Number four, scaling based on mobile and desktop conversion rate.
This is really, really big, but I think you’re gonna like it even better than number five. We all know that we are on mobile, right.
It’s always in our hand. We’re always on mobile and all that kind of stuff but still desktop work, guys. Desktop works and the stuff works really, really well.
Why? Does anyone know why it works? No one knows.
Okay, I’ll tell you.
GA Path: Audience – Mobile – Overview
So first things first, you have to go inside the Google Analytics path, Audience, Mobile, Overview.
You can see right here that mobile is 200,000 sessions and has a very, very, good revenue, $122,000. And a really good conversion rate.
But do you see what I noticed?
On the other session duration, people spend double the time, when they are on the desktop, and people see more pages per session.
And people bounce even less when they are on the desktop and they have a bigger conversion rate.
Because when you are on the desktop, you have the ability to sit somewhere straight. Sit somewhere straight and realise that you don’t have so many distractions.
So when you are on mobile, you can go, “Oh someone called me, something happened.” And I get off and do what I was doing, so I lost the conversion.
But when you’re on the desktop, you have a bigger screen. Usually you are in the office and you’re not working, obviously. You are buying some stuff or you are either at home.
So you spend more time.
The more time you spend on the desktop, then the more time people spend on your site on the desktop, the more money you will make.
Okay, and here, you see if you get the analogy, the same analogy of desktop sessions, compared to mobile, you will see that you would make way more money on the desktop, rather than mobile.
I’m not saying that “Okay, go ahead and neglect mobile”
But I’m just saying know your numbers. And, as I say here, yes mobile is king but the desktop is converting way better.
Scaling Based On Specific Mobile Devices
And the last thing for today, scaling based on specific mobile devices.
I might know that in affiliate marketing you have the ability to scale on specific mobile devices.
Here, that was a game-changer for us because we have the ability to target specific mobile devices. And whatever you know is shit.
Whatever you know, doesn’t have to do anything with whatever people care about, people know about you, and the actual data that you need to use in order to make more conversions.
So forget what you know and go and focus on what analytics has to tell you.
GA Path: Audience – Mobile – Devices
If you go the analytics path: the audience, mobile, devices.
You see here that we have the ability to know exactly which device people made the conversion.
What we did is we spend a lot of time because you see right here, the iPhone is king, it’s converting really, really, really well.
But if you can see on number 10, Samsung Galaxy S7, it has a much bigger conversion rate and converts way better.
Okay, don’t get fooled.
The conversion rate only doesn’t say one thing. Okay, you have to see the analogy of how much traffic you’re sending. And always, always, you need to test. Always.
I had another customer where we made some similar numbers. We made, I think around the $100,000 in 3 months, pure profit.
He was selling in the kitchen niche. Some kitchen accessories. And we, in our minds, we had, you know, iPhone.
Everybody has an iPhone, iPhone7 works, iPhone 6-plus works, bigger screen and stuff like that. But on the age range that we were talking, because he was selling stuff on the actual age range for 45 and above. They were not iPhone users.
All of them were Android users. And, all of them were not like Samsung Galaxy 7, the latest mobile version. They were having some really, previous versions of really bad smartphones and stuff like that.
So when we took the time to analyse the whole data, we realised that we need to target only on iPhone.
So the iPhone is king but Android is the prince.
That’s all folks. Thank you very much.