Black Friday is fast approaching. The day of the year where people go wild and spend loads of money in stores and online shops. As an owner of an online business, you want people to spend their money at your store. So you want to draw a lot of visitors to your site and seduce them with an awesome discount. But how do you know if your Black Friday campaign was a success? Which steps do you need to take to make sure you can measure that success in Google Analytics? Read this post to find out!
Black Friday extras
You’re probably going to do something special during BFCM weekend. Something extra, more than the usual. You might publish more posts on Facebook, Twitter, Instagram and so on. Perhaps you’re dedicating a special newsletter to the Black Friday sale; you might even send out an extra one. What about your website? Will you add a banner throughout the website? Add a countdown clock? A pop-up? Write down all the things you’re planning to do during Black Friday and Cyber Monday and think about how you’re going to measure them.
1. Measurement plan
In comes the measurement plan. It’s vital to know if you can measure the things you’d like to measure and if you have the data to compare it with. If you already have a measurement plan, grab it and refine it. If not, get some piece of paper and a pen and write down the following:
Your business objective for this Black Friday sale
Once you’ve clarified the above, you need to have an implementation plan so that everything you want to track, is implemented. You might need to ask a developer for certain things. But please keep in mind, measuring something is way, way better than measuring nothing. So if you find this a bit scary, don’t set the bar too high for yourself and measure the things that are easy for you to do.
2. Check your eCommerce tracking
If you own an online shop, you want to gather eCommerce data. Check if you have information about your eCommerce Conversion Rate, the shopping behavior, product performance and revenue.
If you do not see this kind of data in Google Analytics, you might need to implement eCommerce tracking. For more information, read this guide about enhanced eCommerce tracking. Knowing what the shopping behavior, checkout behavior and so on is before Black Friday, gives you the opportunity to compare this data with the data you’re collecting during Black Friday. And that gives you insight into whether or not your Black Friday campaign has been successful.
3. Check goals and funnels
To be able to analyze your visitor’s behavior on your site even more, you can implement goals. You can set a goal for every time someone pressed the ‘add-to-cart’ button. Having a goal with a funnel for your checkout process is also vital. It calculates a goal conversion rate for the entire checkout and shows where people drop off in the funnel. During Black Friday, having this data will allow you to check for technical issues. If you see a sudden drop in the conversion rate or drop-offs, that’s a sign that tells you to dig in further. Check if payment options are working or if you have downtime.
Implement BFCM events in Google Analytics
If you decide to add banners and/or pop-ups or other elements on your websites where people can click on, don’t forget to implement events. Add goals to those events so you can analyze them in Google Analytics. You do want to know if people actually click on them, right? Adding events take in a bit of extra work. Luckily, Google Tag Manager makes implementing events a lot easier. There are a lot of tutorials on the world wide web that show you how to create events. One of my favorites is the video tutorial by Measureschool.
4. Special BFCM UTM tags
To identify all your Black Friday efforts on other sources such as social media and in your newsletters, you can’t live without the proper UTM tags. Using these UTM tags consistently throughout the entire Black Friday sale is key to effectively analyze the success of all your marketing efforts on other websites than yours. A couple of examples:
As you can see, I used blackfriday as the campaign UTM tag. Use the utm_campaign=blackfriday tag on all sources you’re using that point to your website and have a BlackFriday sales purpose. During and after the sale you can get insights from Google Analytics to see if people from the Black Friday campaign bought anything.
Keep an eye on this campaign during the sale, if it’s not going according to plan, it will allow you to optimize your efforts during the sale. For example: put more money in ads on channels that lead to more sales. You can do a lot of cool things with this campaign; I described all of this in a post I wrote about custom campaigns.
5. Check Google Analytics stats during Black Friday
Google Analytics is great for keeping track if the sale is going right. You can check on a lot of things. Keep an eye on real-time stats, if you see a sudden drop in the number of users on your site, perhaps your site’s down or down in a specific country. You can also check your cart URL and checkout URL in the real-time analysis. If you see a lot of folks there, but no sales coming in, your checkout might not be working. If you just sent out a newsletter, and you see no-one coming to your site from a newsletter, perhaps you’ve added a broken link. The real-time functionality in Google Analytics is your friend here.
If you want to know if your Black Friday sale has been a success and want to know what made it into a success, you need data to compare the data you’re collecting during the sale with. Make sure you’re currently tracking all the data you need that makes you able to analyze your visitor’s behavior on your site. Start with writing down a measurement and implementation plan and check if all tracking is in place. After the sale is over, compare the data of the BFCM sale with your prior data and check what worked and what didn’t work so you’ll know what to do next time! You don’t have much time, so get crackin’! Happy analyzing!
I often get a request from our Blog team about one of their pages. Sometimes they want to know if the page has gotten more pageviews or they notice something weird and they want me to find out what’s going on. And this time they wanted more insight in the performance of one particular page. I want to share with you how I deal with this request.
So the other day I got a request to check the performance of our Blog homepage. We want to optimize that page so it fits better with the need of our audience. If you have an idea about that, you can leave your feedback in the comments section below this post.
Page level analysis
The first thing I had a look at is how ‘popular’ the page is and if it’s worth the effort to spend time and resources on this page. I went to the All pages report in Google Analytics, which you can find under Behavior –> Site content and did a cmd+F or ctrl+F search for the page https://yoast.com/seo-blog/. If you can’t find the page you’re looking for; it’s because it probably isn’t within the first ten results. So you need to expand your table first; you can do this on the right bottom of the table.
I notice it’s at position 32 if you look at the number of pageviews, which is a reasonably high position and thus worthy of further investigation. I also notice that in 6,327 of the cases it’s an entrance page, this means it’s in 35,3% of the cases the first page of the session (6,327 / 17,931 * 100).
You can also search for a specific post in the search bar to see just the metrics of that page but sometimes other pages show up as well.
If the page is in blue letters, it means you can specify even further when clicking on it because it’s a link. Or you can use regex; regex stands for “regular expression”. Lunametrics made this fun regex guide that shows you how you can use regex in Google Analytics. It may sound a bit scary, but if you know the basics, it’s quite doable and will make your Google Analytics life a whole lot easier. Here’s how a regex would look if I just wanted the SEO blog homepage:
But in this case, you can just as well click on the page to see just the metrics of that page. Try to understand what the metrics are saying and how it compares to the site’s average. In this case, for a page that’s built to guide people to blog posts of their interests, a bounce rate of 50.48% is fairly high. That means that in half of the cases, people didn’t do anything on that page! That’s not what the page is designed for.
I was also curious to see if this page gets a lot of mobile traffic, so I added a secondary dimension with the Device category. I then checked what the metrics told me.
About 10% of the page views come from a mobile device. You can see it has a higher bounce rate so checking the mobile experience is a good idea.
And, I was curious to see how the page developed over time, so I added a wider timeframe to check if I saw something unusual. You can adjust the graph you’re seeing. Perhaps you’re interested if Bounce rate declined or not. You can select this metric and you’ll see the trend of the bounce rate of that page.
Session level analysis
I then looked at this page from a page level. But, I had more questions about this page. If people are entering our site through this page, where are they coming from? So, I had a look from a session level perspective. I went to landing pages and did the same search as in the All pages report.
It’s at position 65 and obviously has 6,327 sessions since we saw that in the All pages report at entrances. I once again looked at the metrics and tried to understand what they’re telling me. The number of pages per session, the bounce rate and the number of ‘new’ users. And I had a look at conversions.
I then dove in further, clicked on the page and added a secondary dimension: medium, so I could quickly see where traffic is coming from. I noticed that we have a lot of traffic that we don’t know the source of. So that’s something to explore further. In second position comes our plugin and third is organic search traffic. Which is interesting to see because I’m curious with what keywords people end up on that page and if we rank properly on that keyword or keyphrase. With that information, we can improve the SEO of that page even further.
Again, I had a look at bounce rates, pages per session, number of new users and possible conversions. Thinking about if the page is doing what it’s supposed to do.
You now see the queries and position of that page. Take a look at the metrics and try to understand what’s going on. It’s especially interesting if you have a lot of impressions but a low clickthrough rate (CTR).
What can we learn from this analysis? For one is that it’s worth the while to put some time and effort into this page. I learned that we can optimize the SEO of that page even further and that we can put some more effort into ranking for the keyword SEO blog.
I also noticed that it’s quite a popular page, but the bounce rate is too high for my taste. Especially when the goal of the page is to guide people to a blog post of their interest. So, there needs to be interaction with this page. We need to find out what people expect to find on this page. So, therefore, extra information is needed. That’s why we added a simple poll on this page, using Hotjar. We also created a heatmap with this tool to get a better understanding of how people behave on the page.
Combining data gives you a far more holistic view and will make sure you can draw more reliable conclusions. Data we can use to optimize the blog homepage even further. The perfect dataset doesn’t exist but we can try to get as far near perfection as possible.
When working with Google Analytics, you do not always want to stick with just a secondary dimension. Sometimes, you also want a third and fourth dimension. But in Google Analytics’s standard reports, that’s not possible. And the custom reports you can create in Google Analytics are very satisfying to look at. Maybe it’s my perfectionism talking, maybe not. But if I want to create a report, I want it to look nice. Luckily, there’s this tool called Google Data Studio. And oh my, I love it!
What’s Google Data Studio?
If I’d had to explain what it is: Google Data Studio is a tool in which you can visualize your data. You can connect all types of data to Google Data Studio, like Google Sheets, you can upload CSV files and…..drumroll Google Analytics! And it connects really really easy with Google Analytics.
You can create all sorts of reports with nice graphs, charts, and tables, bringing your data to life. I’m not thoroughly going to cover every aspect of Google Data Studio, you can use Google for that. But my goal for this post is that you’re going to give Google Data Studio a try and create a nice report with more than two dimensions!
Connect Google Analytics to Google Data Studio
In order to get Google Analytics data in Google Data Studio, you need to make a connection between the two. The only requirement is that you have a Google Analytics account and a Google Data Studio account. Since they’re both Google products, this connection is easy to set up. And therefore shouldn’t hold you back from trying Google Data Studio. The steps are explained in this post about connecting your Google Analytics account.
Recreate the Source/Medium report in Google Data Studio
When I first tried Google Data Studio, I was surprised how intuitively this tool was. The first thing I did to get more familiar with the data tool was to recreate one of my favorite reports in Google Analytics: the Source / Medium report. You start with adding a chart, in this case, a table.
It automatically adds Source and Sessions. Cool thing is that the distinction between dimensions and metrics is immediately visible. The dimensions are green, the metrics are blue. It’s very cool to see the wide range of dimensions and metrics Google Analytics has to offer.
If you click on ‘Source’ you can replace that dimension by scrolling through the dimensions or if you already know the name of the dimension, by typing the name in the search field. The same goes for metrics. To recreate the Source / Medium report, we need to add a couple of metrics.
Since we have an online shop, I’m adding the Ecommerce metrics to my report:
And there you go! You’ve just recreated the Source / Medium report in Google Data Studio. And this is exciting already of course because you just witnessed for yourself how easy it can be. But now, we’re going to add some cool to this report.
Customize that report
If you use UTM tagging and use campaign, content and term tags, you can add all of these in a report! Give it a try. Your first reaction might be that it would be awesome to have all that information in one table. But you’ll quickly see that your report becomes too cluttered and obscure.
If you want data to speak for itself then reports must be readable. So adding a lot of dimensions to your reports is not something you want. Think about on what levels you want to see your data. If you want to see just your traffic from search engines there’s no need to see data from other traffic sources right?
In which cases would you like to see more than two dimensions? I love the combination of Source and Landing page. And even more so the combination of Source, Landing page and Campaign to check how my marketing campaigns are doing. Other dimensions that are insightful is Device category, Source and Landing page. Or Region, Source and Landing page. Or if you’re more international, like us, Country, Source and Landing page.
Add some fun
Google Data Studio offers filters that easily allow you to specify your data even further. And I’m a fan of specifying your data because it gives you so much more context. You can add Source as a filter, Medium, Campaign, Country, you name it, you can filter it. Make sure it makes sense though. For me, this is such an awesome feature of Google Data Studio!
You can also add a date range filter, which allows you to adjust the date range to your own likings. This makes sure that your dashboard isn’t just a one-time thing, but a dynamic dashboard you can use at all times.
The first thing I always do when I create a report is adding the date range filter. And I really sit down and think about what kind of filters I want. I sometimes even draw out the report I’d like to see by hand on a piece of paper and then create it in Google Data Studio.
There are some cool features that you can add in the table itself. For instance, you can add heatmaps to your columns so that you can easily spot rows that stand out from others.
You can even compare date ranges so you can see if you’ve gotten, for example, more sessions from a particular source. And you can give it all the colors and fonts you want, keep the readability in mind though!
Starting with Google Data Studio is not as hard as you might think. And for me, it allows me to have more fun with Google Analytics data. If you catch yourself spending time on building the same reports, or adding the same secondary dimensions over and over again, it might be a good idea to just as well create that report in Google Data Studio. It will save you time and the cool thing is that you can share your report with others.
UTM tags are parameters you can add to links that point to your website that send extra information to Google Analytics. Perhaps you’ve clicked on a link from a newsletter and saw all bunch of weird stuff in the URL.
These things are UTM tags. And people use them to track their marketing efforts so that they can analyze that effort in Google Analytics.
Why should you use UTM tags?
Google Analytics recognizes a lot of traffic and places traffic in buckets. If you explore the source/medium report, you can see how Google Analytics sees this traffic and where it ends up. If you’re wondering how Google Analytics sees traffic from Facebook or your newsletter, grab your mobile phone, make sure you’re on 2G/3G/4G/5G and visit Facebook or your newsletter and click on a link that points to your website. At the same time, check your Real-Time traffic sources report and see if you show up there and how you show up. If you see that Google Analytics recognizes you as direct / none, then Google Analytics doesn’t know where you came from.
Let’s say you have a lovely newsletter. Its content is awesome, there are links to your site. There are upsell buttons, images that link to your site. You’ve got the whole shebang! You’ve put a lot of effort into these emails because you’ve heard that they can really help your business. And you’d like to see if you get any traffic from your newsletters, if your readers buy anything, and you’d like to see which types of content they find interesting and what not. So you go to the place that can help you with these types of questions: Google Analytics! And you’re searching and searching, but you can’t find anything. You know why you can’t find them? The links in your emails weren’t tagged and all that traffic ended up in a bucket called direct / none.
That’s where UTM tags come in. With UTM tags you add extra information about what types of things your audience clicked on from sources that don’t automatically add this type of information. All those items like image clicks, button clicks in your newsletter can be tracked by using UTM tags.
If you don’t tag your emails, your PDF’s and your social efforts, you have no way of knowing what to optimize. Or how to optimize. You wouldn’t have a clue on what works for your business and what doesn’t work.
What UTM tags are there?
You can use 5 UTM parameters to define your traffic more precisely. Let’s go over them one by one.
Open up the Medium report in Google Analytics and see what comes up. Google Analytics recognizes certain mediums by itself, like: organic, referral, cpc. It can recognize email but this doesn’t have to mean it can recognize traffic from your email campaigns. Google support defines medium as: “The advertising or marketing medium”. For me medium is an umbrella term, it’s a general bucket where a lot of things can belong to.
Source is a bit more specific, you can see what I mean when you just look at the Source report in Google Analytics. Here you’ll see types of search engines, websites that are referrers, social media platforms and so on. Google support defines source as: “Identify the advertiser, site, publication, etc. that is sending traffic to your property”. It all comes together when you look at the source/medium report. Here you’ll see which source belongs to which medium. The UTM tag Source is mandatory when tagging your links.
You’re most probably only going to see data in the Campaign report in Google Analytics if you have AdWords campaigns or using UTM tags for campaigns. Google support defines the Campaign tag as: “The individual campaign name, slogan, promo code, etc. for a product”.
Term and Content
There isn’t a standard report in Google Analytics for the Term tag and the Content tag. It’s only possible if you add one of these as a secondary dimension or if you create a custom report. Just like the Campaign tag, you’re only seeing data for these two tags if you used that in UTM tags. Google support’s definition of the UTM Term tag is: “Identify paid search keywords”. That’s specifically for AdWords but later on you’ll learn that you can use the Term tag for anything you’d like. Google support defines the Content tag as: “Used to differentiate similar content, or links within the same ad”.
Channels to use UTM tags for
There are marketing channels where UTM tags come in very handy. Always tag your email marketing efforts. If you use PDFs that people can download or are send to people as an incentive and that PDF contains links to your site, UTM tag those links. That way you can see if people are actually coming to your website using that PDF. And if there are upsells or other conversion goals, like a make an appointment button, you can check in Google Analytics if your PDFs are converting or not. Google Analytics can recognize traffic from Facebook and Twitter and such but you can only analyze that traffic on a source/medium level. And apart from that, you don’t know if you’ve gotten traffic from other people sharing links to your site on a social platform. If you want more information about your social media efforts, use UTM tags.
How to set up a UTM protocol?
This is actually the hard part. You need to think about a constructive, sustainable UTM protocol you can use for your channels which can be scalable. You must think about a strategy that can deal with change because you never know where your business is headed. Important to know is that Medium and Source are related to each other, all other tags don’t necessarily have to be related to each other. Each step adds more information to your data. It’s a way of classifying your traffic.
The Medium UTM tag is the most general UTM tag of them all. This is a big bucket of data that is collected by the same medium. And since we’re talking about ways that drive traffic to your site, we’re going to use an analogy to make things more clear. You can see UTM tags as if it was a way of transportation. A medium can be a car, a plane, a boat and so on. And I can compare mediums to know which type of transportation is working for my website at the moment.
Source is a smaller bucket, but still a pretty large one. The source is related to the medium. If we take the analogy of a car, a source can be the brand of the car. By looking at the source, we know if we can better spend money on trying to get more traffic from brand X or on brand Y.
We’re narrowing our data with campaigns. We don’t only want to know which brand of car drives more traffic and converts better but also which type of car is most successful. If Yoast was a car brand (that would be awesome), we want to know if Yoast sedans convert better than Yoast SUVs.
And because we can, we send more information about our data to Google Analytics. By adding a content and term UTM tag. We can distinguish purple and green Yoast cars with the content UTM tag. And we can add more information like green gear change Yoast SUVs and compare that to automatic green Yoast SUVs. Gear change information can be send with the UTM term tag. See how much information about one specific type of traffic I can gather just by using UTM tags?
As I hope this example tells you, is that you can use UTM tags to give you more information about your data. The challenge is to think of especially mediums and sources that last. Thinking about on which level you want to see data and compare data can be quite the challenge. What kind of information do you need to improve your marketing further?
When I was setting up a UTM protocol for Yoast, I was dying to see some examples I could use for Yoast. But the frustrating thing was that each of the sources I consulted saying different things. And I understand why; it’s about what works for you as an analyst and what works for your business. Here’s how WE use UTM tagging for our emails.
We have different types of email, for instance our standard newsletter that contains our latest updates. And we have Sales emails that we only send to our subscribers when we have a sale. They both belong to the same medium which is email. And I’m using source to distinguish the type of email. For our standard newsletter I use the date on which the newsletter is send on. But if you’re more interested in the day of the week or the time you send the newsletter, use that as a campaign. It all depends on what kind of information you’d like to see in Google Analytics. We could also add term and content tags for our regular newsletter but decided we don’t need to see more specific data.
For our Sales email we use the name of our sale for the UTM campaign tag. The cool thing is that if you use that campaign tag for everything you’re doing to promote your sale, like Facebook posts, you can later on analyze which marketing channel worked best during the sale.
We use the UTM content tag to distinguish buttons from text links so we can figure out if people are more inclined to click on a button or on a text link later on. If you have more than one button, you can use content tags like: button-1, button-2 etc. etc.
We use the UTM term tag to identify the page the link points to. This last one isn’t really necessary because you can also tell this by looking at the landing page in combination with the campaign. But of course, you can add other information in the UTM term tag like the color of the button or the category the page of the link belongs to.
But in the end, it’s all about what YOU, as an analyst, would like to see in Google Analytics! It’s about gathering information about the behavior of your audience, about how to get more insight into your audience.
How to create a UTM protocol yourself
Write down all your marketing efforts on a piece of (digital) paper. What are you doing with email? What types of email do you have? And what kind of things are you doing on social? And perhaps other channels. Are you running campaigns? Map it all out. And then just write down possible UTM tags for all of them and check if it’s useful for you or not. Keep trying different ways of UTM tagging till you finally have a structure that works! And try to visualize how it will look in Google Analytics. So get familiar with the source/medium and campaign report.
There are Google Sheets out there that help you, like this one from Annie Cushing:
When you’re done creating the UTM protocol it’s vital that everyone in your team that has to deal with UTM tagging is aware of this protocol. And of course, it’s very important that everyone uses it in a consistent manner.
How to find UTM tags in Google Analytics?
All this time we’ve been talking about UTM tags, we’re talking about traffic sources. If you want to know how to find each tag in Google Analytics, you need to be in the Acquisition section.
The utm_medium corresponds with the Medium variable in Google Analytics. And utm_source corresponds with the Source variable. If you click on ‘Source’ right above the table, you only see the Source. And if you want a more general view, click on Medium.
In the Acquisition section you can find an item called ‘Campaigns’. Here you can find your data about the utm_campaign tag.
If you want to find the utm_content and utm_term tag, you need to do a small extra effort. You can only see these if you add a Secondary dimension in the standard reports in Google Analytics:
In Google Analytics the utm_content is called ‘Ad Content’. The utm_term is called ‘Keyword’ and you can add these variables as a secondary dimension to your reports. If you want all of your UTM tags in one report, you need to create a custom report.
UTM tag don’ts
1. Use UTM tags on your site for internal links
There’s no need to add UTM tags on links that are on your site. If you do use tags on internal links, you’ll overwrite the original source of your traffic. So for instance, if someone from a paid Facebook post comes to your site and clicks on a link in the menu that’s UTM tagged and buys a product, there’s no way of knowing that your paid Facebook ad was the source that lead to a conversion.
2. Using Campaign tags that are too general
Tags that are completely the same, end up in the same bucket in Google Analytics. If you’re using a campaign that is specifically for email, but someone else in your team is using the same campaign for a completely different thing on social, these will end up in the same bucket. But they’re both completely different things! You don’t want to draw the wrong conclusions so you want to be sure that you’re not mistakenly receiving data from a different campaign with the same name. For sales campaigns I suggest to add a date. For channel specific campaigns, add something that relates to the source, like utm_campaign=fb-daily-post.
3. Not consistently using UTM tags
Every time you misspell a tag or use an uppercase tag instead of a lowercase tag, a new tag is created. Why is that a bad thing? Well because of this:
Rows 5 and 6 are examples of tagging gone wrong and as you can see, traffic from these UTM tags get a separate row. But it’s traffic that belongs to row 1, the sales/email source. Now these numbers are small but what if that number is bigger?
4. Not using the utm_source tag
This one is mandatory. And if you want to be completely safe, use the Medium, Source and Campaign tags to avoid tracking errors.
5. Tagging guest posts
If websites have links that point to your site, they’ll be easy to recognize in the referral section in Google Analytics. The same goes for if you write a guest post for someone’s website. You can see this traffic in your referral report.
6. Create too specific Medium tags
As said before, you want your Medium tag to be as general as possible. If you create too specific Medium tags then you’re missing the meta view of all efforts that belong to that medium. You don’t want utm_medium=facebook because how can you measure all of your social media efforts in Google Analytics?
7. Using sensitive information in tags
You don’t want to share business sensitive information in your UTM tags, information you don’t like others to know. Because with UTM tags, that’s publicly visible. The same goes for personal information, don’t store data which can be traced back to a specific person.
8. Use tags that aren’t recognizable in Google Analytics
If you don’t know what it means just by looking at it, it’s not very suitable as a tag. You make your life a whole lot easier if you can tell what it is without having to go to the link. It really helps you to analyze your Google Analytics data.
You’ve probably heard us talk a lot about structured data, Schema.org and JSON-LD. Schema structured data on your site can result in highlighted search results. In this article, we’ll show you how to implement structured data using the JSON-LD Schema.org markup on the pages of your site. Here, we’ll take a closer look at how to implement structured data with Google Tag Manager.
Google Tag Manager is a tool that can take your marketing to the next level without the need of a developer. It’s a tool that can easily add scripts or pieces of code to a page. There are several advantages to using Tag Manager to implement structured data.
For one, you can generate tags, triggers, and variables, which means that you can apply the same code again and again on different pages. For instance, if you have loads of recipes, you can create a tag with the variable “preparation time”, so the preparation time of every recipe will be taken from a recipe page. This means you won’t have to add the preparation time manually to the code of every single page. In the end, this will save you a lot of work.
In addition, Tag Manager features a preview mode, which allows you to check whether you successfully implemented your data immediately. Read the post Google Tag Manager: An Introduction to get started.
How Google Tag Manager works
First, you need to know about three important elements: Variables, Triggers and Tags. You can find these elements on the left-hand side of your workspace. A workspace is a place where you work on creating and adding pieces of code to your pages.
A tag is a piece of code that can be fired on a page of your website. You can put many things in a tag. For instance, you can add the Google Analytics tracking code in a tag. This tag will enable Google Analytics to track your website. Similarly, you can put your structured data code in a tag. In other words: a tag contains information as to what you want to add to a page.
Tags only work when there’s a trigger attached. You need a way of telling Google Tag Manager under which condition a tag must be used, or fired, as we call it. If you have a structured data tag, the trigger tells Tag Manager on which pages to fire that tag. This is because it’s possible that not all your pages need a recipe structured data markup, for instance. Simply put, a trigger tells Tag Manager: “Please fire this tag on these pages, but not on these pages”.
Variables serve two functions. Firstly, triggers need variables to know whether or not to fire. Suppose Tag Manager runs on your page. If the value of the variable meets the conditions you set, the trigger will fire. This, in turn, allows the tag to work. Secondly, the variable provides Google Tag Manager with variable information. This means that the information can be different in different contexts. A Date Published, for example, will be different for every eBook you publish. If the trigger fires, Google Tag Manager will then fetch the specific value from the specific page it visits.
An example of a variable is the URL of a page, but you can use any element of a page as a variable. It could be an ‘Add to cart’ button, or the H1 of a page, for example. The most commonly used variables are predefined in Google Tag Manager. But things like buttons or the H1 are variables you have to define yourself. With variables, you can edit your code in such a way that it will take elements from the current page to use in a tag.
Adding JSON-LD to your site step by step
We’re going to guide you through implementing structured data on your pages. We’ll take the Schema.org type Course as an example. As stated, we’ll use JSON-LD markup. There are five steps to take:
"name": "Site structure training",
"description": "Learn how to create site structure for your site that makes Google understand your site and makes visitors go where they need to be",
After you’ve created your markup, you have to get it ready for Google Tag Manager with Yoast’s JSON-LD Script Helper tool. Paste your code and hit Submit. The tool will create a piece of code you can use in Google Tag Manager. Copy it. You’ll need it for your new tag.
Step 2: Creating tags in Tag Manager
You’re ready to make your tags and triggers. Follow the steps below:
Make a new tag and give it a name (Site structure training, for instance)
Click Tag Configuration and choose tag type: Custom HTML
Paste code from the script helper tool
Check Support document.write
Step 3: Creating triggers
You need to add a trigger, so it knows when to fire the tag. You can do this on the same screen you see in the screenshot above, or directly from the Triggers screen in the Workspace. Click on the Triggering space in your new tag and choose the correct Page View. Hit Save. Your snippet is now implemented as is (see below for working with variables).
If there are no triggers yet, you can add them on the same screen. If you want a trigger to a specific page, you can copy the relevant piece of the URL and add it to a new trigger. So if you only want to trigger a tag on this page: https://yoast.com/academy/course/site-structure-training/, you need to copy the part /academy/course/site-structure-training/.
Hit the New or + button to add a new trigger. Give it a name and click on Trigger Configuration. Choose Page View from the list of trigger types and click on Some Page Views. You can now choose when the tag should trigger and which conditions should be met before it’s possible. In our case, we want to trigger the tag on https://yoast.com/academy/course/site-structure-training/. That’s why we’ll choose Page Path and Equals from the dropdown, and paste the URL into the empty box.
Step 4: Creating variables
Variables make it much easier to implement the same structured data on many different sites. The variables can be found on the left-hand side of the workspace as well. You’ll see all predefined variables. There’s also an option for user-defined variables. To create a variable, click on New. After that, take the following steps:
Name the variable
Click on Variable Configuration
Choose Variable type
In this example: DOM Element
The fourth step depends on the type of tag or trigger you want to create. In this example, we’ll use a DOM Element. A DOM Element is a piece of your page, like a DIV, HTML and BODY. In this example, the DOM Element is the H1, which is the most important heading of the page.
Once you’ve clicked on the DOM Element, you need to choose which method you want to use to select a page element with. In this case, we’ll use a CSS Selector. By simply entering h1 into the Element Selector, you’ve created a variable that takes the H1 of a page.
If you want to use the meta description of a page, enter meta[name=”description”] and that variable will add the meta description of your pages.
Once you’ve created these variables, you can use them in your tags.
As you can see, you can use the H1 variable for the “name” and Meta description variable for the “description”. Now, the Course Schema.org markup sends the right name and description to Google.
Variables make this method of implementing structured data flexible and scalable. This way, you produce code that can be used in many places, without having to add it manually or change it for every instance. You only have to set up the tags once.
You’re ready to test your code. Tag Manager has a Preview mode that lets you test code before you publish it on a live site. Go to your Workspace to activate that mode.
In your browser, go to the page you’re implementing structured data on and refresh. You’ll see the Preview tab appear and this should show you the tags that fired. If you want to know more, you can go to the Window Loaded screen to see if your variables were executed properly. If all is well, your H1 variable should now show the same value that’s visible on the site (the title). Always test your code before publishing!
If all the information displayed on this screen is correct, you can publish your tag. If there are still some flaws, go through the steps again.
To publish your tag, hit the Submit button you see at the top right. Give your version a descriptive name and press Publish. Once you’ve published your structured data tag, go to the Structured Data Testing Tool and enter the URL of the page that should now contain structured data. With this tool you can check if the structured data is implemented correctly:
See no errors and warnings? Well done! If you do see errors, dive in more deeply and read what Google has to say about it.
Perhaps you’ve heard about it: Google Tag Manager. Google introduced this tool 5 years ago, a tool that would make marketers less dependent on developers and that would, therefore, speed up your marketing process. Google Tag Manager has evolved over the years becoming a more complete and easy to use tool. Here I want to explain why you should sign up today, if you aren’t using Google Tag Manager already.
What is Google Tag Manager?
Running every tag from Google Tag Manager has two big advantages. First of all, you’ll have an overview of the tags you’ve added. Secondly, you’re in full control of measuring the effects of your marketing efforts.
What can you use it for?
Google Analytics and Tag Manager
One of the most used tags that’s managed in Google Tag Manager is the Google Analytics tag. Not only can you add the Google Analytics tracking code. You can use Google Tag Manager to create, for instance, custom dimensions, events or content grouping. This means that you can track if people click on your buttons, if they scroll down to a certain point on your page, if they watch your videos and so on. All the cool things you can do with Google Analytics events, can now be managed in Google Tag Manager. And you won’t need a developer for it!
Other third party tools
Google Tag Manager supports a lot of third party tags, like: Adwords, Adobe Analytics, Bing ads, Hotjar, Crazyegg and so on. You can find the complete list on the Google Google Tag Manager support forum. You can use Hotjar tags to finally get those heatmaps – a visual representation of where people click on your site – you wanted to have. Or run surveys and A/B tests on your site. Getting data like that can help you bring your conversion rate to the next level.
Google Tag Manager and structured data
But there’s more! You can also use Google Tag Manager to implement structured data on your site. Structured data is extra information you add to your page in a specific format. Google can show this information in the search results, which makes it more likely people click on your result and engage with your page.
At the moment, we’re working on a new and practical course about structured data. In this course, you’ll learn how structured data works and how to implement it with Google Tag Manager yourself. Don’t miss the launch and keep an eye on our newsletter!
Where to find Google Tag Manager?
Google is ubiquitous with its tools. If you visit: google.com/analytics/ you can see all tools Google has developed to help you with your marketing strategy. In addition to Google Analytics, there are tools to help you boost conversion or perform customer surveys. And, of course, there’s Google Tag Manager. You can sign up for free! Wait! Free, you say? Yes, free!! So what’s stopping you?
After you’ve signed up, you can create an account for your website, your iOS or Android app or your AMP pages:
Just provide the URL of your site as the container name and then select web – if you want to implement it on your website. After you’ve created this container, Google Tag Manager will ask you to add a piece of code in the <head> and <body> of the page. I promise, this is one of the few things you might need a developer for, when it comes to using Google Tag Manager.
Luckily, if you’re using WordPress, you can easily add the Google Tag Manager code using a plugin called DuracellTomi’s Google Tag Manager for WordPress. Please note that you only have to use the GTM-XXXX code.
If you’re using another CMS, please check out the quick install guide for more information on how to get started.
After you’ve inserted the Google Tag Manager code to your pages, you’re ready to create your own tags. This can be done in a so called workspace that looks like this:
So now you’re all set up and ready to add those tags to your site.
We’ll be doing more posts on Google Tag Manager soon. Explaining the practical side of things like how to create variables, triggers and tags, and how to implement structured data with it. We’ll also help you understand how to combine Google Tag Manager with Google Analytics to use it to its full extent. So stay tuned!
“I came, I puked, I left” is a very famous definition of the bounce rate by Avinash Kaushik. But what does it mean exactly? When does a visitor bounce? Is it purely a visitor that hits the back button or is there more to it? And what can you tell by looking at the bounce rate of a webpage? In this post, I want to show you what it is, what it means and how you can improve your bounce rate.
Bounce rate is a metric that measures the percentage of people who land on your website, and do completely nothing on the page they entered. So they don’t click on a menu item, a ‘read more’ link, or any other internal links on the page. This means that the Google Analytics server doesn’t receive a trigger from the visitor. A user bounces when there has been no engagement with the landing page and the visit ends with a single-page visit. You can use bounce rate as a metric that indicates the quality of a webpage and/or the “quality” of your audience. By quality of your audience I mean whether the audience fits the purpose of your site.
How does Google Analytics calculate bounce rate?
According to Google bounce rate is calculated in the following way:
Bounce rate is single-page sessions divided by all sessions, or the percentage of all sessions on your site in which users viewed only a single page and triggered only a single request to the Analytics server.
In other words, it collects all sessions where a visitor only visited one page and divides it by all sessions.
Having a high bounce rate can mean three things:
1. The quality of the page is low. There’s nothing inviting to engage with.
2. Your audience doesn’t match the purpose of the page, as they won’t engage with your page.
3. Visitors have found the information that they were looking for.
I’ll get back to the meaning of bounce rate further below.
Bounce rate and SEO
In this post, I’m talking about bounce rate in Google Analytics. There’s been a lot of discussion about whether bounce rate is an SEO ranking factor. I can hardly imagine that Google takes Google Analytics’ data as a ranking factor, because if Google Analytics isn’t implemented correctly, then the data isn’t reliable. Moreover, you can easily manipulate the bounce rate.
Luckily, several Googlers say the same thing: Google doesn’t use Google Analytics’ data in their search algorithm. But, of course, you need to make sure that when people come from a search engine to your site, they don’t bounce back to the search results, since that kind of bouncing probably is a ranking factor. It might be measured in a different way than the bounce rate we see in Google Analytics, though.
From a holistic SEO perspective, you need to optimize every aspect of your site. So, looking closely at your bounce rate can help you optimize your website even further, which contributes to your SEO.
How to interpret bounce rates?
The height of your bounce rate and whether that’s a good or a bad thing, really depends on the purpose of the page. If the purpose of the page is purely to inform, then a high bounce rate isn’t a bad thing per se. Of course, you’d like people to read more articles on your website, subscribe to your newsletter and so on. But when they’ve only visited a page to, for instance, read a post or find an address, then it isn’t surprising that they close the tab after they’re done reading. Mind you, even in this case, there’s no trigger sent to the Google Analytics server, so it’s a bounce.
A clever thing to do, when you own a blog, is creating a segment that only contains ‘New visitors’. If the bounce rate amongst new visitors is high, think about how you could improve their engagement with your site. Because you do want new visitors to engage with your site.
If the purpose of a page is to actively engage with your site, then a high bounce rate is a bad thing. Let’s say you have a page that has one goal: get visitors to subscribe to your newsletter. If that page has a high bounce rate, then you might need to optimize the page itself. By adding a clear call-to-action, a ‘Subscribe to our newsletter’ button, for instance, you could lower that bounce rate.
But there can be other causes for a high bounce rate on a newsletter subscription page. In case you’ve lured visitors in under false pretenses, you shouldn’t be surprised when these visitors don’t engage with your page. They probably expected something else when landing on your subscription page. On the other hand, if you’ve been very clear from the start about what visitors could expect on the subscription page, a low bounce rate could say something about the quality of the visitors – they could be very motivated to get the newsletter – and not necessarily about the quality of the page.
Bounce rate and conversion
If you look at bounce rate from a conversion perspective, then bounce rate can be used as a metric to measure success. For instance, let’s say you’ve changed the design of your page hoping that it will convert better, then make sure to keep an eye on the bounce rate of that page. If you’re seeing an increase in bounces, the change in design you’ve made might have been the wrong change and it could explain the low conversion rate you have.
You could also check the bounce rate of your most popular pages. Which pages have a low and which pages have a high bounce rate? Compare the two, then learn from the pages with low bounce rates.
Another way of looking at your bounce rate, is from a traffic sources perspective. Which traffic sources lead to a high or a low bounce rate? Your newsletter for instance? Or a referral website that sends a lot of traffic? Can you figure out what causes this bounce rate? And if you’re running an AdWords campaign, you should keep an eye on the bounce rate of that traffic source as well.
Be careful with drawing conclusions though…
We’ve seen loads of clients with a bounce rate that was unnaturally low. In that case, all alarm bells should go off, especially if you don’t expect low bounce rates. Because that probably means that Google Analytics isn’t implemented correctly. There are several things that influence bounce rate, because they send a trigger to the Google Analytics server and Google Analytics falsely recognizes it as an engagement. Usually, an unnaturally low bounce rate is caused by an event that triggers the Google Analytics server. Think of pop-ups, auto-play of videos or an event you’ve implemented that fires after 1 second.
Of course, if you’ve created an event that tracks scrolling counts, then having a low bounce rate is a good thing. It shows that people actually scroll down the page and read your content.
How to lower high bounce rates?
The only way of lowering your bounce rate is by amping up the engagement on your page. In my opinion, there are two ways of looking at bounce rate. From a traffic perspective and from a page perspective.
If certain traffic sources have high bounce rates, then you need to look at the expectations of the visitors coming to your site from those sources. Let’s say you’re running an ad on another website, and most people coming to your site via that ad bounce, then you’re not making their wish come true. You’re not living up to their expectations. Review the ad you’re running and see if it matches the page you’re showing. If not, make sure the page is a logical follow-up of the ad or vice versa.
If your page lives up to the expectations of your visitors, and the page still has a high bounce rate, then you have to look at the page itself. How’s the usability of the page? Is there a call-to-action above the fold on the page? Do you have internal links that point to related pages or posts? Do you have a menu that’s easy to use? Does the page invite people to look further on your site? These are all things you need to consider when optimizing your page.
The bounce rate is frequently mistaken for the exit rate. Literally, the exit rate is the percentage of pageviews that were the last in the session. It says something about users deciding to end their session on your website on that particular page. Google’s support page gives some clear examples of the exit rates and bounce rates, which make the difference very clear. This comes directly from their page:
Monday: Page B > Page A > Page C > Exit Tuesday: Page B > Exit Wednesday: Page A > Page C > Page B > Exit Thursday: Page C > Exit Friday: Page B > Page C > Page A > Exit
The % Exit and Bounce Rate calculations are:
Page A: 33% (3 sessions included Page A, 1 session exited from Page A)
Page B: 50% (4 sessions included Page B, 2 sessions exited from Page B)
Page C: 50% (4 sessions included Page C, 2 sessions exited from Page C)
Page A: 0% (one session began with Page A, but that was not a single-page session, so it has no Bounce Rate)
Page B: 33% (Bounce Rate is less than Exit Rate, because 3 sessions started with Page B, with one leading to a bounce)
Page C: 100% (one session started with Page C, and it lead to a bounce)
Bounce rate is a metric you can use to analyze your marketing efforts. You can use it to measure if you’re living up to your visitors’ expectations. As we have seen, visitors bouncing from your website don’t necessarily puke before they leave, in spite of what Avinash Kaushik says. Nevertheless, you want them to engage with your site. So you can use the bounce rate to decide which pages need more attention. Meeting your visitors’ expectations and making your pages more inviting for visitors all leads to creating an awesome website. And we all know that awesome websites rank better!
When talking with customers about Google Analytics, you often hear the same thing: “I’m not really using Google Analytics because I don’t know what I’m looking at. It’s just too much”. And that’s a pity because you can learn a whole lot about your website and your audience with Google Analytics’ data. So, is there a simple way to use Google Analytics without getting lost? There might be, by using segments.
What’s a segment?
In Google Analytics a segment is a way to specify the data you’re seeing in every standard view. Google Analytics just throws it all in there, on one big pile of data. This means that when you’re looking at a standard view in Google Analytics you see: ‘all sessions of all visitors’, you see: total revenue, all pages, average time on page of all users, the landing pages of all visitors.
You might recognize this: You’re in the Acquisition section and you’re all happy, because you’ve created the perfect table. You’ve used the advanced filter option to include the Medium: “Organic” and you’re seeing the data you want to see. Then you think: “I’m curious to see which pages these visitors looked at, let’s take these filters to the next section of Google Analytics.” You hit the Behavior section and Poof! your filter is gone. Oh, the frustration!!!
If you want to know which pages people coming from organic search visit, you need to find another way. A segment helps you to narrow down the aggregated data Google Analytics shows, into data you want to see and need, to answer a specific question you have. You can use that segment throughout the sections, the segment doesn’t get lost when switching between sections. For instance, if we want to know which source customers who bought an eBook came from, we can create a segment of people who bought an eBook. By applying that segment and looking at the Acquisition – Source/Medium section, we can conclude that most of our eBook customers came from a newsletter. Goodbye frustration!
Without segmentation, all data you see is aggregated. This makes it really hard to draw conclusions. As Avinash Kaushik once said: “All data in aggregate is crap.” And I certainly agree with him. If you want to draw a valid conclusion, you need to specify your data.
For example, you can’t just say that most of your visitors visit your site around noon. Well okay, you can. But what does it mean? This data is so aggregated that you can’t build a strategy on it, it doesn’t provide any insight. Based on this data you might conclude that promoting a new product around noon is the way to go. But what if a large amount of your non-paying visitors visit your site around noon, but your high-potential visitors visit your site in the evening? Then you could’ve made the wrong decision based on non-specific aggregated data. So with a segment, you can zoom in on a specific part of your data. And if you do that right, you can make important business decisions that help your business move forward.
How to create a segment in Google Analytics?
First of all, creating a segment in Google Analytics isn’t dangerous. You can edit your segments, you can delete your segments, but you won’t delete the actual data you have. For me this was an important realization, because it meant that I could just ‘play’ with segments without any consequences.
The first step is thinking about what kind of segment you need. Which question do you want answered? What’s important for your business? And where can you find the data to create that segment? Do you want to segment on demographics of the user? And/or, the behavior of the user? Or, the technology the user uses to visit your website? And so on. Knowing what it’s called what you’re looking for in Google Analytics really helps when creating segments.
The second step is adding the actual segment. You can find the segment section at the top of the page in every view from Audience down to Conversions.
This means that if you’re in Dashboards, Shortcuts, Intelligence Events or Real-Time section, you can’t see the segment section.
Google Analytics offers ‘fixed’ segments which you can find in the ‘System’ section. A lot of these segments are pretty darn useful. For example, there’s an Organic Traffic segment that groups all visitors that came from an organic search result to your site. Very useful, if you want to know which landing pages these users visit. Another example: There’s a Mobile Traffic segment, that groups users that use a mobile device to visit your site. Very helpful as well, for example to find out if the ‘time on page’ is what it should be, this might say something about the mobile friendliness of your site.
There are more segments to think of than the system segments Google Analytics offers. For instance, you can create a segment that filters out all visitors that spend less than half a minute on your site. Or you can create a segment that focuses on the organic traffic from all visitors from the Netherlands. Or, as mentioned before, create a segment based on the products visitors bought or a certain amount of revenue a visitor yielded.
I found this video on YouTube that explains creating a custom segment pretty well:
For me, a couple of segments are really useful. I have segments for every country that’s important for our business, for every product and for every product page. And I have a segment for every medium like Organic, Newsletter and in our case: plugin traffic.
A nifty feature in Google Analytics is the ability to add more than one segment for the same view of data. This means you can compare different segments. For instance, if you created a segment of visitors that stayed longer than 5 minutes on your website and created a segment of visitors that stayed less than 1 minute on your website, you can compare the two and find out more about the behavior of these two groups and in which aspects these two groups differ.
If you want to know what you’re looking at, when clicking your way through Google Analytics, segmentation is the way to go. If you have questions like, “how do the visitors from California behave on my site?” Or, “what are my newsletter visitors doing on my site?” “How’s my campaign going?” Creating a segment is the easiest way to go. It’s a way to dissect your data and actually know what you’re looking at, when looking at all the different sections in Google Analytics. Say farewell to your Google Analytics frustration!