The move to Google Analytics 4 has been tough – especially for those who used Google Analytics for Etsy shops. The upgrade was last-minute and now we have a whole new system to learn and understand how to interpret for the particular ways Etsy shop visitor data gets tracked. The Google Analytics 4 interface is (more…)
Read moreLeft it to the last minute to save your Etsy shop’s old Google Analytics data?
If you’re here, then yes: you have. The countdown is on to 1 July 2024 when all our Universal Analytics data will be deleted!
Transmission from July 2024…
It happened. It’s done. It’s gone.
If you got some backup data, fantastic! If you used my backup tool for Etsy, grab the Looker Studio Dashboard to explore it.
If you missed the window, don’t worry. Let’s look forward and make sure your shop is connected to Google Analytics 4 instead.
Pinterest is a wonderful and fun tool for collecting inspiration and aspiration… so it only makes sense that it’s also a fantastic marketing channel for your handmade stores! But how much traffic does it generate?
Find out how to measure your Pinterest visitors more reliably and control how they appear in your Google Analytics reports.
If you’re ready to harness the power of numbers to optimize your Etsy shop but haven’t installed (or upgraded) Google Analytics yet, don’t wait any longer!
Here are the complete, accurate instructions for connecting Google Analytics 4 with an Etsy shop.
You will learn:
- What login to use for Google Analytics
- Whether to create a new Google Analytics Account or use one you already have
- All the most effective, up-to-date settings to apply inside Google Analytics
- How to link your new Google Analytics tracking number to Etsy
- How to test everything is working
- What to do next to start looking at your visitor numbers and behaviour!
⚠️ You need to follow these instructions even if your Google Analytics 4 Property was created automatically and you had the old GA version (Universal Analytics) connected to Etsy.
Read moreWe all know it:
A high bounce rate is bad! Right??
Well, that depends. On a lot, actually.
And even if you decide you need to “get your bounce rate down”, you first need to have a deeper understanding of what causes bounces than just “bounce = bad”.
Let’s have a look at what a bounce rate really is and what a “bounce” means for different parts of your online shop.
Read more⚠️ IMPORTANT!
These instructions are for GA Universal Analytics and are no longer applicable. Etsy now supports GA4.
The out-of-date article below is available to read if interested. If the topic is still relevant in GA4, it might be updated in the future.
POP QUIZ: Can Google Analytics answer this question?
“How do people find my Etsy store?”
At first, Google Analytics looks like it has all the answers! There in your reports, you see: direct traffic, referrals, a few from Facebook and other social media… Isn’t that how they got there?
ANSWER: Nope! Not unless you follow the instructions in this guide.
Google “etsy traffic sources” and you’ll find this little Help article from Etsy. In that article it says this:
“Google Analytics shows how people found Etsy.”
So, what’s the difference?
Well, that means that any of the traffic sources you see in Google Analytics could show how that person found the Etsy home page or an entirely different shop before they navigated to yours within Etsy. Half your so-called social media traffic could be from other people’s marketing! (And not in a good way…)
Even worse, Google Analytics doesn’t show you how people found your shop within Etsy, which makes up the bulk of your traffic. Etsy search, clicks from favorites or recently viewed, promoted listings: all hidden.
That kinda sucks.
You could just analyse your traffic sources in Shop Stats, but let’s fix it in Google Analytics instead.
This guide explains how to use channel definitions and filters to make traffic sources a whole lot more accurate!
A long time ago, when I worked in retail, I envied the prim, organised merchandisers whose sole responsibility was (as far as I could tell from behind the counter) to fluff around with enticing displays of gifts and stationery.
I know I’m not the only one!
Now as Etsy sellers, we get to “merchandise” our own online shops every day.
Check how our listing thumbnails look all together in the catalogue.
Pour over a new product page to make sure every detail is perfect.
Go through our shop policies with a fine tooth comb to make sure we aren’t accidentally committing to replacing unwanted items with a lifetime supply of Starbucks…
And I know—because I’ve spent my fair share of time there—that we do a lot of this “fluffing around” in our public shop front. You know – the exact same view that our buyers see.
The pages of our shop where our Google Analytics code runs. Those pages.
Oh… I think we have a little problem to fix.
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 mystery 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.
See? Magic!
Keep reading to find out how and where to use campaign tags for marketing your handmade shop!
This article has been updated for Google Analytics 4. (You don’t need to change your tagged links!)
Read moreOUT OF DATE: These instructions were originally provided for Universal Analytics. This version of Google Analytics is no longer available.
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!)
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!
Oops…
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”).
Read moreThe 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?
Read more