If you’re ready to harness the power of numbers to optimize your Etsy shop but haven’t installed Google Analytics yet, don’t wait any longer!
Here are my instructions for connecting Google Analytics the right way, with up-to-date steps and screenshots.
If you’ve hung around here for a while, you’ll have heard a little about UTM Campaign Tags. They are the magic ingredient for making sure that visits from Instagram, Pinterest and anywhere else show up in your Google Analytics reports correctly.
Why doesn’t this happen right in the first place??
To know where a visitor came from, Google Analytics has to listen in to the conversation happening between the visitor’s browser and your website. Often this conversation includes information about the last page the visitor looked at (their traffic source).
This is called “referral” information.
But sometimes, for a whole bunch of technical reasons, it doesn’t have this information or it’s wrong. In many of these cases, the visit will be attributed as “direct” traffic – the catch-all black hole bucket of mysterious visits! – and you’ll never know if your marketing actually worked.
Campaign tags let us control all the information about the source of the visit and leave nothing to chance.
Keep reading to find out how and where to use campaign tags for marketing your handmade shop!
Before you start creating or testing things with Filters in Google Analytics, it’s important to take some steps to keep your data safe.
What’s the danger?
Whenever you make changes to your GA settings for things like Goals, Filters, Content Groupings etc. — all the things I describe in my articles — the changes to your data are permanent. You need a backup without any of these changes, just in case you get something wrong…
Like accidentally creating a filter that removes ALL your traffic and you don’t notice for a week… right during a big ad campaign!
A Testing area takes it one step further to let you test out these settings first, then apply them to your main set of data only when you’re sure they’re working correctly. It’s up to you to decide how risky you think a change is and whether you should test it out first.
How do we do this in Google Analytics?
In Analytics, you can have multiple ways of viewing the same data. These are called, appropriately, Views.
In this guide, we’ll create a backup “Raw Data” view to preserve everything with the default settings, and a “Test” view for trialing more complicated Filters before applying them to your main View (normally called “All Web Site Data”).
IMPORTANT: These instructions are for Universal Analytics. Google Analytics 4 comes with a built-in method for testing filters without needing to maintain separate Views. (In fact, the concept of “Views” no longer exists!)
The website had been live for a month and it was all going downhill.
It didn’t start out like this. There were hundreds of hours poured into making everything just right and carefully crafted campaigns sending visitors every day. The first reports showed good revenue and a frankly fantastic sales conversion rate of 3%.
But the next time I looked, it was 2%. Then 1.5%. What was going wrong?
Well, nothing. It was exactly what I expected. But to a stressed-out business owner, these numbers looked terrifying. The site is failing!
Why would two people interpret such obviously bad results so differently?
If you ever find yourself on a dark, empty road and see a lone car far ahead indicate to change lanes, you might think, “Why are they bothering? I bet they even checked their blind spot…”
Well that person might be me. And I did check my blind spot.
I’m just the kind of person who does things the same way, every time.
So if you’re anything like me, I can only assume that you’ve been super diligent in using your Test View to trial changes in Google Analytics.
But what about when you’re confident everything’s working? Everything took so long to set up the first time… surely you don’t need to go through it all again?!
Nope, you don’t!
(Ok, there are a couple of tiny things you’ll need to do again, but bear with me because there’s still an easy way to do it.)
IMPORTANT: These instructions are for Universal Analytics. Google Analytics 4 comes with a new way for testing filters so you no longer need to move them between Views.
I think I’m lucky. I get to talk to people about digital analytics almost every day. (Hey, it’s fun for me, ok?)
But over the years I’ve noticed something a bit silly.
Everyone’s always talking about how to measure more stuff and see more reports.
They need to capture every movement of every visitor.
They want to dip their fingers into a swirling ocean of numbers.
They’re desperate for a veritable avalanche of interactive charts straight off the set of Minority Report.
And it’s all a complete waste of time if you don’t know how to take the next step.
The most important work you will do in Analytics isn’t setting up traffic attribution or installing dashboards. It’s actually analysing your data.
And wow, can that be a daunting prospect! Where on earth do you start? What should you look at first? How do you know when something is important and what can you even do about it??
Luckily, there’s a simple place to start and it’s called segmentation. It’s the bread and butter of analysis, is super easy to learn and will make finding those important insights so much easier.
We all know it.
A high bounce rate is bad! Right?
Well, that depends. On a lot, actually.
Let’s have a look at what a bounce rate really is and what a “bounce” means for different parts of your online shop.
If you’re here, you’ve probably noticed something weird going on in your Google Analytics reports. And if you haven’t noticed anything weird, follow along and you might get a surprise.
Analytics can usually tell you, very precisely, where your visitors came from, both geographically and on the web. As you’ll find out in future posts, that’s tricky to get right when you run an Etsy shop, but there’s one problem that almost every site has these days: referral spam.
“Referral spam” is when useless, fake or malicious websites show up as having sent traffic to your site. They haven’t. At least not real people visitors.