Oh, the wonders of email marketing. It can keep your audience up-to-date whilst hopefully resulting in an increase in sales. But how do you measure the efforts of email marketing? Google Analytics can give you insight into how much of your traffic is generated by email. It’s an interesting tool that can break down the email performance, so that – if needed – you can adapt your site accordingly. I’ll explain down below how to monitor your email performance successfully!

Use UTM tags

If you want to track your email performance in Google Analytics, it’s pretty important to get email data into your Google Analytics, right? If you want to know how many people came to your site by clicking on a link in your newsletter, you need to send a piece of information so that Google Analytics can recognize the traffic is coming from your email campaign. You can do so by adding UTM (Urchin Tracking Module) tags to all links in your newsletter that link to your site, so-called campaign tracking. As a result of that, a link from your email newsletter might look something like this: x.com/postx/#utm_source=x&utm_medium=y&utm_campaign=z 

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If you google more information about UTM tagging, you might find a lot of different approaches. And tagging your links isn’t something you should think lightly of. You need to find a way that will help you with easily identifying links in Google Analytics. Browse through your source/medium stats, look at campaigns and ask yourself what kind of elements of links in your emails you want to see in your reports. Think about how you want to handle the following UTM tags:

  • utm_medium
  • utm_source
  • utm_campaign

An example: let’s say you’re planning to do a summer sale and you’re sending out an additional email to your customers. How would you add UTM tag links in such an email? One UTM tag you don’t have to think about is the utm_medium tag. That should always, always be ’email.’ That way, Google Analytics will organize this traffic in the Channel email, and that is something you’d want if you’re going to work wilt Multi-Channel Funnels.

Then you have the utm_source tag. Some say you should use the Branded source, for instance, utm_source=mailchimp if you use MailChimp, or utm_source=helpscout if you use HelpScout for support emails and such. But again, it’s all about how you can identify from which source your traffic is coming from. If you sent multiple emails, for instance, your regular newsletter and an occasional sales email, you can decide that for your newsletter, you use utm_source=newsletter and for your sales email utm_source=sales.

Use the campaign tag for more specified tagging. In the example of the Summer Sale, you want to give that sale a specific tag that is used by all the marketing efforts you do for that sale. Your Social Media efforts and so on should use the same utm_campaign tag. That way you can easily recognize what your email did for that campaign and it it’s the best performing source for that campaign. For  example: utm_campaign=summer-sale-july-18.

There are two other UTM tags you can use to differentiate even further:

  • utm_term
  • utm_content

You can use the utm_term, for instance, to add the subject of the post you’re linking to. And you can use utm_content to differentiate elements of the newsletter. For instance, if you’re linking to the same page twice, but one with a text link and the other with a banner, you can use utm_content=textlink and utm_content=banner.

Where to find your emails in Google Analytics?

If you use campaign tracking on all links in your emails, you can find them in your Acquisition reports when clicking on All Traffic –> Source/Medium. You can find what you used for utm_source in the Source report, and what you used for utm_medium in de Medium report. Or both in the Source/Medium report:

email in aquisition reports in Google Analytics

If you can’t find what you’re looking for, you can use the search bar that searches in the first column of your report:

search for email in Google Analytics

Then you’ll get a nice overview of all sources for your utm_medium=email. In the screenshot above, you can see the performance of a sales email for a given period. You can see how much users came to your site, how many sessions there are, how long they lasted on average, and in the last column you can see how your email converted for the goals you’ve set. And you can compare this with your other email marketing efforts and check which was most successful.

If you want to know how your email campaigns (utm_campaign) worked out for you, you can add a Secondary dimension: Campaign to your report.

email campaigns in Google Analytics

You can also go to your campaign report that’s filed under Acquisition: Campaigns –> All Campaigns campaigns report in Google Analytics

You can add Source / Medium as a Secondary dimension here as well. But there are other UTM tags you can add as Secondary dimensions, like the utm_term and utm_content tags. For utm_term, you need to find ‘Seach Term,’ and for utm_content you need to look for ‘Ad Content.’

I find it very insightful to click my way through these reports and check if I’m tagging in a way I can understand my traffic sources. If I see a UTM tag that I find useless, I’ll know I have to change the way I’m tagging. This is especially the case if I decide to use utm_term and utm_content tags for links to my site.

utm_term in Google Analytics

utm_content in Google Analytics

Create a segment for email

If you don’t want to deal with Secondary dimensions and want to see more than what the Acquisition reports have to offer, you can decide on creating a segment for your emails in general. Or you can narrow the segment down to just the email you’re interested in using all UTM tags that are in your email as shown in the image below. Creating an email segment in Google Analytics

Just play a little with your segment. If you just want to see Medium=email, create that segment. If you just want to see Source=sales, create another segment. Find the joy in segments; they’re fun!

Reports to look at

Before you look at all the numbers in your Google Analytics report, think about what kind of questions you want to be answered. This will help you with finding what you’re looking for in the jungle called Google Analytics. Do you want to know how many users came to your site via email? How many new users your email drove to your site? How long they stayed and so on: check the Audience Overview report and use a segment to you’ll only see traffic from your emails.

You can also compare email with other sources, see how effective your emails were by checking the stats in your Acquisition report. Did email get the most sessions, conversions and so on? Are the people coming from email more engaged than other sources? What’s your question and hypothesis here?

And using an email segment shows you which pages users saw in the Behavior reports, the products they bought in the Conversion reports, the (goal/eCommerce) conversion rate of your newsletter subscribers. And you can use this data to compare it with other marketing efforts. Which was more effective? Do newsletter subscribers convert better? And do you know why?

One final tip, when sending out an email to your users, check the real-time report. Is what you’re seeing what you expected? Or isn’t there any traffic coming from email? Then there might be an issue with your newsletter.

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Conclusion

The most important thing if you want to analyze your newsletter performance, is using campaign tracking on the links in your email. There are email services that can add UTM tags automatically, like MailChimp. Otherwise, you have to do this manually. And trust me, you want to do this. Because you want to check your email performance in Google Analytics. When analyzing your newsletters, think about the questions you want to be answered. Using segments will make sure you rock your Google Analytics reports!

Read more: ‘Tools to improve your online marketing campaign’ »

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The Audience data in Google Analytics beholds a lot of interesting data about your users. Not only does it provide you information about from which country they’re coming or the language they’re using, but it also gives insight in the device they’re using when visiting your site and the browser they’re using for doing that. And that my dear friends, is information you can use to make your site more accessible and user-friendly.

Technology report

Information about the browser people are using to visit your website, can be found in the Technology report. Expand the Audience tab and scroll down:

Technology report in Google Analytics Expanded Technology report in Google Analytics

 

 

 

 

 

The Technology report has some pretty cool features, let me show you:

Technology reporting features in Google Analytics

This is the default report you see when clicking on Technology. You can see the most popular browsers that are used for visiting your website. For this particular website, Chrome is by far the most important browser. But you can also check Operating System, Screen Resolution, Screen Colors, Flash Version and Java Support.

What does it tell you?

Browser

Of course, it’s interesting to know what your visitors are using for visiting your website, but that’s just information that’s ‘cool’ to know. But how can you use this data to optimize your website even further? Take a look at the report and see if you notice anything that’s a bit odd.

A higher bounce rate for a particular browser for instance. It may be an indication that your site looks different on a Safari browser than on a Chrome browser. Take a look at the Average Session Duration too, is there a browser with a very low session duration? Use that browser yourself and visit your website to see if you can understand why.

And if you have particular goals, like a contact form submit goal, you can check if there’s a browser performing poorly for that goal. It might just be that the contact form isn’t working properly for that browser. The same goes if you have an online shop, check the eCommerce stats and go over the report to check if you see anything unusual.

Keep in mind that you base your conclusions on a sufficient amount of data. But it won’t hurt testing your website across different browsers.

Operating System

You can do the same checks for Operating System. How does Windows perform on your site in comparison with Macintosh? Of course, it’s very well possible that people who are using Windows differ from people who use Macintosh. Do iPhone users convert better than Android users like discussed in this article? But again, it doesn’t hurt testing if your site works on your most popular Operating Systems. How awful would it be if your checkout doesn’t work on Android? Check the conversions for each of your goals, which Operating System is underperforming?

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Screen resolution

When creating a new design for your website or deciding where your most important call-to-action should be, looking at screen resolution is a wise thing to do. You want to optimize for the vast majority of your visitors so check how your site looks on the most-used screen resolutions. Perhaps you’re always using an enormous monitor yourself when browsing while others might just be using laptops. Keep in mind that your site is for your users, take into account the screen resolution your visitors are using and take that as the basis for your design. How’s the font size? Can you see your call-to-action without scrolling?

Conclusion

To keep your site as optimized as possible, checking your Technology reports once in a while is a good idea. It can help you identify technical issues your site might have with particular browsers or browser versions and operating systems. If you’re planning to do a redesign, check if your redesign works on the most popular browsers, operating systems and screen resolutions. And if you’re using new software or plugins on your site, the Technology report gives great insight into whether or not everything works for your visitors.

Read more: ‘Tracking your SEO with Google Analytics: a how to’ »

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Anyone who has browsed through Google Analytics should have come across a whole lot of variables in the reporting stats. The reports consist of dimensions and metrics; Google Analytics calls these the building blocks of your reports. And if you want to create a custom report in Google Analytics or Google Data Studio, you have complete freedom in what dimensions and metrics you put in this report. But be careful, you might create a useless report. In this post, I’m going to explain what the difference is between dimensions and metrics. And what to look out for when combining these two yourselves.

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What are dimensions in Google Analytics?

All the data you see in Google Analytics, all variables in reports is either a dimension or a metric. Google explains dimensions as:

Dimensions are attributes of your data.

So in a way, a dimension is a description, a characteristic, a feature or aspect of your data. It’s not a quantitative variable but more a qualitative variable. Let me make this clear by giving you a couple of examples of metrics:

  • City
  • Device
  • Source/Medium
  • Campaign
  • Page
  • Goals
  • Products

Notice what they all have in common? They all consist of words, not numbers. Of course, some dimensions are expressed in numbers, like hour and date. But still, the dimension is an aspect or feature of the user itself, but not how or what the user is doing on your site. Dimensions describe the data that’s collected.

You can see dimensions in the first column of your reports.

dimensions in Google Analytics

The report also gives you clues on what other dimensions there are and there are sooooo many. If you’re curious on what other dimensions you can add to, in this example, the Acquisition: Source/Medium report, click on the Secondary dimension button.

Adding a secondary dimension in Google Analytics

When you click on ‘Display as alphabetical list’ you can browse through all dimensions you can add to this particular report. It’s an easy way for you to get familiar with dimensions.

For instance, you can add ‘User Type’ as a secondary dimension, to see which source drives more New visitors to your site. You can add ‘Page’ to your report, to check which pages people land on from a particular source. You can do a lot of cool things here, and quite easily as well. But before you go all out; what’s the question you’re trying to answer?

What are metrics in Google Analytics?

Metrics are the numbers you see in each dimension. Metrics show you what a user did on your site, expressed in numbers. For example, if we look at the Behavior – All Pages report:

Behavior report with page dimension in Google Analytics

The page is the dimension; it’s the variable in which specific metrics are collected. Pageviews and entrances and such are metrics; these variables show you numbers on what users did in this particular dimension.

Metrics need dimensions, for context, otherwise, it’s just numbers.

The standard Google Analytics doesn’t allow you to add a secondary metric, because not every metric is collected for every dimension. It might raise your eyebrows, and it’s a bit confusing. But it gets less complicated if you know how Google Analytics collects data.

What’s scope in Google Analytics?

Ever wondered why Google Analytics shows certain dimensions and metrics but leaves out other seemingly essential dimensions and metrics in their default reports? That’s because Google Analytics doesn’t want to combine these two, it would show incorrect data and will let you draw conclusions based on the wrong data. Now, why is that? Why does Google Analytics want to prevent you from combining this? It all has to do with how Google Analytics processes its data: Google Analytics scope. Each dimension and metric can only have one of the following scope-types:

  1. Hit
  2. Session
  3. User
  4. Product

Hit

You can see a hit as everytime a user (cookie) does something on your site, it will send data to Google Analytics. Every single action is stored. The hit scope is the lowest level of data storage. A page is a hit-level dimension, just like language and page title is. Pageviews, time on page, load time and total events are examples of metrics on hit-level.

Session

The session scope is more time-based and is one level higher than the hit-level. A session consists of hits that happen in just one session for the same user. Dimensions and metrics on session-level collect data about a session. Examples of dimensions on a session-level are Source/Medium, Landing Page, and Device Category. Examples of session-level metrics are sessions, bounce rate, exits, goals, and pageviews per session.

User

The user scope is the highest level in which data is organized. Users can have more sessions, and a session can have more hits. Examples of dimensions that belong to the user scope are user type, days since the last session, gender. Examples of user-level metrics are users, new sessions, and percentage of new sessions.

Product

The product-level scope has everything to do with data about a product.

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Combining dimensions and metrics: do’s and don’ts

The session-level dimensions and metrics contain data about specific sessions. But hit-level dimensions and metrics don’t have data on session-level variables because they’re independent of sessions. So if you decide to combine pages with sessions in a custom report because you want to see how many sessions a page has gotten during a session, you’d be looking at something else than what you were expecting.

hit + session level report in Google Analytics

This report will show you something like this:

Pages and sessions in a custom report in Google Analytics

But if you think that page 1 was viewed in 1,199 sessions in total, then you’re wrong. What you are seeing is how many sessions began on page 1. because that’s the first hit of the session. There are a couple of common reporting fails described by LunaMetrics that explains this in more detail.

We just learned that you couldn’t combine dimensions and metrics that don’t share the same scope. Best practice is obviously to check whether or not the dimensions and metrics you want to combine, do share the same scope. But how can you find out? Google has a Dimensions and Metrics Explorer. On this page, you can find all dimensions and metrics. When I first saw this huge list and expanded a couple of items, I got confused. I couldn’t make sense of it.

Dimensions & Metrics Explorer of Google Analytics

But it helps if you use the UI Names, the names that you see in Google Analytics itself. And by expanding them all, you’ll have a nice overview. Don’t click on the dimension or metric, instead click on the checkbox. Some will turn to grey if you do that, then you’ll know you can’t use these in combination. Still, if you select ‘pageviews’, the ‘sessions’ metric doesn’t turn grey. And the list doesn’t show you on which scope every dimension or metric is processed. So this tool isn’t foolproof when it comes down to combining your dimensions and metrics in a custom report. Unfortunately, defining which scope it is, is something you have to do yourself.

Conclusion

When creating custom reports, segments or you’re going more advanced with custom dimensions and custom metrics, think about what you want to measure first. Think about on what level, or scope your dimensions and metrics are. And think about if it all makes sense. In general, if you want to add the Sessions metric to a custom report, make sure you stick to the Session-level scope! And don’t combine hit-level variables with session-level variables.

Read more: ‘How to guide: Tracking your SEO with Google Analytics’ »

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When browsing through the ‘Behavior’ section in Google Analytics, you’ll come across the term ‘pageviews’ a lot. And you might think that the more pageviews a page has, the better. But is that actually true? What’s a pageview exactly and can pageviews help you understand your site and audience better? Find out in this post!

What are pageviews in Google Analytics?

Google Analytics has this handy feature that explains what a certain metric or dimension is when you hover over the question mark icon. According to Google Analytics, the definition of a pageview is:

definition of pageviews in Google Analytics

Pageviews is the total number of pages viewed. Repeated views of a single page are counted.

According to Google’s Google Analytics support site, a pageview is:

A pageview (or pageview hit, page tracking hit) is an instance of a page being loaded (or reloaded) in a browser. Pageviews is a metric defined as the total number of pages viewed.

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Now that’s a pretty straightforward explanation. So, let’s say you have a page about a Basic SEO course: pageviews will show you the number of times that page is viewed for a given period. The metric itself says nothing about how many visitors saw that page or how many times the page was viewed per session. It’s just the total number of pageviews per page. This means that one visitor can be responsible for a lot of pageviews, and that a page can be viewed multiple times per session.

Pageviews in combination with other metrics

Pageviews can give an indication of how popular a post or page is. But having a high number of pageviews for a post doesn’t necessarily mean it is popular. Is it a good thing that you have a lot of pageviews per visit? Does it mean that people like to read a lot of pages on your site? Or does it mean that they can’t find what they’re looking for? A good data analyst is critical of his or her data at all times. A single metric doesn’t tell you a lot; it’s the context that provides the information you can use.

Speaking of context, you might think: “Why don’t I see ‘sessions’, ‘pageviews’ and ‘users’ in one grid table in Google Analytics?” There’s a reason why Google Analytics doesn’t let you see pageviews in combination with sessions and users by default. And that has everything to do with the way Google Analytics collects its data. The Google Analytics data is organized based on scopes. You can see these four different scopes if you want to add a Custom Dimension:

Scope in Google Analytics

Lunametrics wrote a blog post on understanding scope in Google Analytics, which explains why you can’t combine metrics from different scopes. In short, they say: never combine hit- and session-level metrics. So if you create a custom report that shows pageviews and sessions per page, then you get a report that doesn’t make any sense. Because sessions have hits, but hits don’t have sessions.

Adding context to pageviews

So if you can’t combine user and session metrics to pageviews, what can you do to add more context to the pageviews metric?

Unique Pageviews

First of all, you can look at the number of unique pageviews compared to pageviews. According to the question mark in Google Analytics:

Unique Pageviews in Google Analytics

Unique Pageviews is the number of sessions during which the specified page was viewed at least once. A unique pageview is counted for each page URL + page Title combination.

I think this definition needs some more explanation. Let’s say a visitor visits a page about a Basic SEO course, then reads a basic SEO article and then visits the page about Basic SEO course again. During this session, the Basic SEO course page is viewed two times. These two pageviews in this single session will be added to the total number of pageviews for that page. But only one unique pageview will be added to the total number of unique pageviews for that page during a single session.

In fact, if you want to see the number of sessions for a page, the best way is to look at the unique pageviews metric. And if you divide the number of pageviews by the number of unique pageviews, you get the average number of times a particular page was viewed per session. It’s a good idea to check the pages for which the number of pageviews differs a lot from the number of unique pageviews. This means that visitors viewed this page a couple of times during a single session. That may indicate that the page is confusing people. But there are other explanations for this as well. Our knowledge base articles, for instance, have a lot of pageviews compared to the number of unique pageviews. People refer to those articles a couple of times during a single session to follow the steps listed in these articles.

Creating segments

You can also look at the number of pageviews per visit and create a segment. That lets you compare groups of users and see where they differ from each other. For instance, visits with more than three pageviews against visits with less than three pageviews.

creating a page depth segment in Google Analytics

Are these two groups coming from different sources? Do they read different articles? Do they buy things or not? Comparing groups will help you understand your audience better.

Conclusion

There you have it; an understanding of pageviews in Google Analytics. All in all, pageviews probably isn’t the most spectacular metric you can use in your analysis. And if you do consider it one of the most important metrics in your reports, please reconsider because there are more valuable metrics out there. What do you want to know? And is pageviews the way to get that information? Probably not.

Read more: ‘Analytics basics: Which posts and pages perform best?’ »

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I remember my first time in Google Analytics. As a data lover, I enthusiastically clicked my way through the numerous tabs. Seeing terms like sessions, pageviews, users, bounce rate and so on. Being so enthusiastic, I didn’t really think about what these terms actually mean. And that’s pretty important, because without knowing what Google Analytics’ definition of the term is, you might draw the wrong conclusions. In this post, I’m going to discuss an important term in Google Analytics: a session. 

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What are sessions in Google Analytics?

If you think of the term session, what do you think it means? My definition is that it is a period in which a certain thing happens. Keep your own definition in mind and check if it equals Google Analytics’s definition of a session:

A session is a group of user interactions with your website that take place within a given time frame.

Cool, it’s pretty much the same as my definition. And that helps me with understanding what I’m looking at when dealing with sessions in Google Analytics.

Let’s break it down. If a visitor or user enters your website a session begins. Google Analytics records it and collects data from the very start. Within that session, a user can do a lot of things on your website that Google Analytics records, for instance, view pages, buy products, fill out forms and so on.

When does a session end?

Looking at the definition, you see that a session has a given time frame. This implicates that it can end after a certain period and that you can adjust when the session ends. A session can end because of one of three reasons:

  1. After 30 minutes of inactivity
  2. At midnight
  3. Campaign change

1. After 30 minutes of inactivity

By default, a session ends when a user did nothing on your site for 30 minutes straight. For example, a user looks at a page on your site, then reads a blog post and leaves that open without doing anything on that page for 30 minutes, the session ends. If after, for instance, 29 minutes a user interacts with the page, by clicking on a link or a menu item or something like that, the very same session is extended by another 30 minutes. So every time you interact with the site, the session is extended. If you don’t do anything for 30 minutes, it ends.

There are cases where 30 minutes is too short. If you have very long articles, for instance, people need more time than just those 30 minutes. There are also cases in which 30 minutes is too long, for instance for product pages in a shop. Luckily you can adjust the session timeout. Go to the admin section, at property level you’ll see an item about Tracking info. There you can find session settings:

adjusting session timeout in Google Analytics

As you can see, the minimum you can set is 1 minute, the maximum is 4 hours. If you want to have an idea about how long an average session on your site is, go to your audience tab, click overview and you’ll see a summary with a couple of statistics like Avg. Session Duration:

average session duration in Google Analytics

Before drawing conclusions, please check the date range you’ve set. Check for a month, or compare a couple months to see if the duration doesn’t change that much. You can use this information to set the right session timeout. Usually it makes most sense to set it at the average session duration.

2. At midnight

The second reason a session can end is simply because a new day is beginning. If a user is on your website and reads a post at 11:58 PM for instance, that session ends at 11:59:59 PM and a new session begins at 12:00 PM.

3. Campaign change

Users of your site come from different sources, like Google, Facebook or email. Sometimes they arrive on your site following a specific campaign link, for instance, if you’re running an AdWords campaign or you’ve added a utm_campaign parameter to a URL in your newsletter. Let’s say a visitor lands on your website by a certain AdWord paid keyword, then Google Analytics stores that campaign in its data. But if that same user goes to your site via a different campaign, the first session ends and a new session starts.

Now what?

Just knowing how much sessions you’ve got, isn’t that interesting per se. It gets interesting when you compare it with something. For instance, if you compare last month’s sessions with the month before that. Does it follow the same trend? And if you see a spike in sessions, do you know what caused that spike? Or compare weeks, do you see a drop in sessions in the weekends? You can also compare sources, which source drives most sessions to your site? And how many pages per session does every source have? What’s your most successful source of traffic when it comes down to sessions? There are a lot of questions you can ask yourself. My tip: ask the question first, then open up Google Analytics and try to find the answer.

Conclusion

If you want to be able to analyze your Google Analytics data you have to understand what the variables of this tool mean exactly. A session is a group of actions of one user in a given time frame. It starts when a user enters your site and it ends after a certain time of inactivity, a change of campaign or at midnight. You can set the time after which it should end, depending on the average time a user spends on your site.

Now go have a look at your sessions! Do you see anything remarkable?

Read more: ‘Understanding bounce rate in Google Analytics’ »

 

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When looking for information about keywords in relation to SEO, you get bombarded with information about keyword research. And of course, keyword research is crucial if you’d like your page to rank. But it’s also important to understand what the basic principle of a keyword is. And that’s the thing I’ll explain here.

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What is a keyword?

A keyword, or a focus keyword as some call it, is a word that describes the content on your page or post best. It’s the search term that you want to rank for with a certain page. So when people search for that keyword or phrase in Google or other search engines, they should find that page on your website.

Let’s say you’ve got a website about pianos: you sell all sorts and types of pianos. You blog about what to look at when buying a piano and you share reviews about the pianos you offer on your online shop. You sell digital pianos so you’ve created a product category page about digital pianos. Ask yourself this:

  • What kind of search term do you want to be found for?
  • Which words do you think people will use in search engines to find you?
  • What would the search query look like?

Probably [digital piano], right? Because this keyword reflects what’s on the page best. If you’d have to explain the bottom line of your content, how would that look? What words would you use? That’s your keyword or key phrase – if it consists of multiple words.

We use the word ‘keyword’ all the time, this does not mean it consists of only one word. A lot of times keywords consist of multiple words. So when talking about keywords, a lot of times we mean a phrase instead of just one word.

Why are keywords important?

One of the things Google looks at when ranking a page is the content on that page. It looks at the words on the page. Now picture this, if every word on, for instance, a blog post about a digital piano is used 2 times, then all words are of equal importance. Google won’t have a clue which of those words are important and which aren’t. The words you’re using are clues for Google, it tells Google and other search engines what the page or post is about. So if you want to make Google understand what your page is about, you need to use it fairly often.

But Google isn’t the only reason why keywords are important. Actually, it’s less important, because you should always focus on the user: on your visitors and potential clients. With SEO you want people to land on your website when using a certain search term or keyword. You need to get into the heads of your audience and use the words they use when they are searching.

If you use the wrong keywords, you’ll never get the visitors you want or need, because your text doesn’t match what your potential audience is searching for. But if you do use the keywords people are searching for, your business can thrive. So if you see it like that, your keywords should reflect what your audience is searching for. With the wrong keywords, you’ll end up with the wrong audience, or none at all. That’s why having the right keywords is really important.

How do you use keywords in your pages and posts?

There used to be a time where you could add a lot of keywords to your pages and posts, do some old-fashioned keyword stuffing, and you’d rank in search engines. But a text with a lot of the same keywords in it is not a pleasant read. And because users find this kind of copy terrible to read, Google finds it terrible too. That’s why ranking in Google by doing keyword stuffing, fortunately, became hard to do. 

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So what are the rules of thumb here? First and foremost, it’s very important that your content is easy to read. Of course, you should use your keywords in your text, but don’t stuff your keywords in almost every sentence. In general, if 1 or 2% of all words of your copy, is your keyword, then you’re not overdoing it. Make sure your keywords are well-distributed throughout your text. Don’t put all your keywords in the first paragraph thinking you’re done with that part of the optimization. Naturally spread the keywords throughout your page or post. Use your keywords in a subheading or a couple of subheadings, depending on the length of your page or post. And use the keyword in your page title, first paragraph and in your meta description. You can find all of these recommendations in the SEO analysis of Yoast SEO.

Now you have a common understanding of what a keyword is. This knowledge will really help you with your keyword research, which of course is the next and vital step!

Read more: ‘Keyword research: the ultimate guide’ »

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It’s Monday morning and you open up your Google Analytics stats. Then there it is, something you don’t wish to see at the beginning of the week: a sudden drop in traffic. And not just a small decline in traffic, no this is a significant drop. Panic strikes, time for action! First, take a couple of deep breaths and grab a piece of (digital) paper and write down the things you should check. This post will help you with trying to find what caused that drop.

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1. Look at ‘the drop’ in Google Analytics

After you’ve taken your deep breath, check how ‘bad’ the traffic drop is. Sometimes a drop can look sharp because you’ve set the wrong date range. For example, you’ve included today and the day isn’t over. Or you’re looking at an hourly report.

Hourly report in Google Analytics

It’s also possible that you’ve included a weekend in your date range.

Weekend date range in Google Analytics

What I’m trying to illustrate is that you can get skewed graphs because of the date range you’ve chosen. No website has a consistent amount of traffic; it goes up and down. It’s key that you put the drop into perspective. Take a broader date range that you can divide by seven, or compare date ranges.

One of the things worth exploring is to compare the date range with last years date range. Did you have a similar drop in % last year? Then it might be that you have an off-season around the same time each year.

Compare dates in Google Analytics

Is the amount of traffic recovering? Then there might’ve been a temporarily issue with your site. Still worth exploring, but less frightening than an actual drop.

2. Check with IT

If the drop is massive and quite unnatural, my first instinct would be that a technical issue has occurred. Someone from IT can tell you if something happened to the website. Perhaps the site experienced downtime, or they’ve used a new template or did a migration. Check if there’s been a change that could’ve influenced the Google Analytics tracking code.

Use Chrome extensions like Google Tag Assistant, Ghostery and/or Google Analytics Debugger to check whether there’s nothing wrong with the tracking code. And don’t forget to look at your Google Search Console stats, do you see a lot of crawl errors or a drop in the number of indexed pages? And check the search analytics stats while you’re there.

3. Zoom in on your traffic sources

You’ve established that there is a significant traffic drop and it’s not caused by a technical error or an unlucky chosen date range, it’s time to look further. You need to check if you’re getting less traffic from one or more of your traffic sources. The acquisition tab in Google Analytics gives more insight into what drives people to your website.

Drop in traffic source in Google Analytics

First, have a look at the Channels you’ve got and plot rows of each channel, you can plot six channels at a time:

Plot rows in Google Analytics

It’ll show you a specified graph with a graph line for each channel you’ve plotted. That way you can identify which channel caused the drop. Once identified, you can specify even further by clicking on the Channel or by narrowing down the Source and Medium of that Channel in the Source/Medium tab.

If you see a decline in organic traffic, you might have an SEO issue on your hands, like a Google Penalty. If so, sprint to your Google Search Console account to check if you’ve got a message from Google. Also, if you see less traffic coming from social media channels, check whether you’re still active on these channels. A decline in Direct traffic could indicate things like a new competitor showing up, or some pages don’t work anymore.

4. Analyze the audience tab

If the traffic sources aren’t giving you the answer you’re searching for, it’s time to look at your audience tab.

Audience Overview in Google Analytics

New vs. returning

Starting with the New vs. returning, you can find this under the Behavior item in Google Analytics. When you’re seeing a decline in new visitors, you need to work on your visibility. Invest more in SEO, social media and content SEO to drive more new visitors to your site.

Seeing fewer visitors return to your site? Take a firm look at your site’s health. Do you have a proper site structure and is it user-friendly? Are you providing the best user experience? Do you meet your visitor’s expectations? Do your pages work and is your site fast enough?

Country

Don’t forget there can be causes of a traffic drop in which you don’t have control. Like for example, the holidays, hurricanes, power outages, unstable political climate and so on. By looking at countries, you can identify if a specific country has a significant drop in traffic. Then you can check the news and find out if something has happened in that country. You can also do this check on a regional level or a city level.

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Conclusion

When you identified there’s a significant drop in traffic in your Google Analytics, follow these steps to identify what might’ve caused it. If it’s not a technical issue, you can’t see a drop from one of your traffic sources and your audience stayed pretty much the same; then it’s time to ask around. The cause won’t be that obvious, so you need to get a full view of everything that happened on your site and in your marketing efforts. That’s probably where the answer lies. Good luck!

Read more: ‘Understanding bounce rate in Google Analytics’ »

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Black Friday is almost here. 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!

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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:

  1. Your business objective for this Black Friday sale
  2. The strategies of your business objective
  3. The Key Performance Indicators (KPI)
  4. Set targets per KPI
  5. Identify segments

There are a couple of sources you can consult for more detailed information: this post from Avinash Kaushik about the measurement model, a Google Analytics YouTube tutorial about creating a measurement plan and these two posts with practical examples of measurement plans: one about Black Friday and one about a charity website.

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.

ecommerce data in Google Analytics

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 everytime 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:

1a. Promoted post on Facebook
https://example.com/shop/#utm_source=social-media&utm_medium=FacebookAd&utm_campaign=BlackFriday

1b. Regular post on Facebook
https://example.com/shop/#utm_source=social-media&utm_medium=Facebook&utm_campaign=BlackFriday

2a. Text link in Newsletter
https://example.com/shop/#utm_source=newsletter&utm_medium=email-11-24&utm_campaign=BlackFriday&utm_content=textlink

2b. Button in Newsletter
https://example.com/shop/#utm_source=newsletter&utm_medium=email-11-24&utm_campaign=BlackFriday&utm_content=button

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.

Black Friday campaigns in Google Analytics

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. You can do a lot of cool things with this campaign; I described all of this in a post I wrote about custom campaigns.

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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.

Conclusion

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!

Read more: ‘Analytics basics: Which posts and pages perform best?’ »

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Picture this, you have an excellent website with nice pages and posts, but you have no clue how these pages perform. Sound familiar? How do you know if people like the posts you’re writing? Where do you find out if your pages convert visitors into newsletter subscribers or customers? The answer lies in the data you’re collecting. In this post, I’m going to show you where to look at in Google Analytics to see how your pages and posts perform.

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The behavior tab

Let’s start with the Google Analytics tab that brings insight into your pages and posts. On the lefthand side, you can find the behavior tab. Expanding that tab brings you the following:

Behavior tab in Google Analytics

When clicking on Site Content, you’ll find the place that hides all of your site’s content: All pages. That shows a valuable grid table immediately!

All pages grid in Google Analytics

In the columns, you see very cool stuff like

  • Unique Pageviews;
  • Average Time on Page;
  • Entrances;
  • Bounce Rate;
  • Page value.

What do these items tell you about your pages? Unique pageviews say something about how many visitors saw the page during a session. This in combination with how many visitors entered through the page (entrances) gives insight into how many people might have come multiple times to see this page.

The average time on page and bounce rate says something about how popular a page is. If people stay long on a page, they’re probably reading something they like. If the post also has a low bounce rate, they want to see more on your site.

And then there’s page value, this value tells you something about to what extent the page contributed to a conversion. You’ll only see page values if you’ve set up goals and attributed values to your goals.

Purpose of a page and bounce rate

Keep in mind what the purpose of a page or post is. If a product page has a high bounce rate, then that’s a bad sign because these people that bounce aren’t buying your products. A high bounce rate for an informative blog post isn’t necessarily a bad thing. If you’ve written a fairly long post and the average time on that page is low, then people might not be enticed enough to read the post. If it’s a short post, then it’s logical that the average time is low.

Take a close look at the data you’re seeing, which pages stand out in a positive way or in a negative way? Do pages with a high bounce rate need work? Do pages with a low average time on page, need to be rewritten? Analyze and take action to improve your content even more and learn what the audience likes and doesn’t like.

Content goals

If you really want to measure the performance of your content then you can’t live without Google Analytics goals. Setting up goals gives you more insight into what people are doing on your website and if they actually read your content. A pageview doesn’t necessarily mean that the page is actually read, with goals you can find out.

Goals in Google Analytics

Creating a goal in Google Analytics

There are a couple of goals you can think of when it comes down to your pages and posts. You can set up a goal for the number of pages viewed, how long they stayed on your pages and a goal if the page has gotten a comment. With scroll depth goals and how long it takes to scroll down, you can tell if someone read the post. You can even set up a goal if people scroll down the bottom of the page in less than a couple of seconds, identifying the so-called scanners. These last couple of goals are a bit hard to implement, you can read more about that in an article Justin Cutroni wrote about advanced content tracking.

When setting up goals, don’t forget to add goal value. Adding this value really gives you invaluable insight into which pages contribute to conversions and which pages are not. Not sure how to do that, read this post about goal values.

Content grouping

Google Analytics offers something called content grouping, it’s a way to group content obviously. If your pages or post URL don’t follow a logical structure, and you want to group them, content grouping is the way to go. You can group pages into product categories, your posts to certain categories or tags and so on. Once implemented, you can easily see which categories, for example, perform best in term of the variables described above.

Content grouping in Google Analytics

Where to find content grouping in Google Analytics

You can create powerful segments with content groups and check which categories, for instance, are most popular amongst people that come from Facebook. Content grouping in combination with page values will show you which categories or which authors convert better.

Page performance in Google Analytics

As you can see, there’s a lot you can do to find out how your pages and posts perform in Google Analytics. Looking at the general data from the ‘All pages’ in the Behavior tab is a good place to start. Combine that data with segments to give your data more meaning. If you’re serious about web analytics, you can’t go without goals and content grouping.

Read on: ‘Tracking your SEO with Google Analytics’ »

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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.

We’ve just launched a brand new training on structured data and SEO. This training has an introductory price of $119. On July 2, this will jump to the regular price of $149.

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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.

google tag manager structured data workspace

Tags

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.

Triggers

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

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:

  1. Make structured data
  2. Create tags and triggers
  3. Create variables
  4. Trigger your code
  5. Validate and publish

Step 1: Creating the structured data code

Produce structured data JSON-LD code, either by hand or by using Google’s Markup Helper. In this example, we’re using Course markup, which looks like this:

<script type="application/ld+json">
{
  "@context": "http://schema.org",
  "@type": "Course",
  "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",
  "provider": {
    "@type": "Organization",
    "name": "Yoast",
    "sameAs": "https://yoast.com/"
  },
      "offers": {
        "@type": "Offer",
        "price": "99",
        "priceCurrency": "USD"
  }
}
</script>

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
  • Hit Save

google tag manager structured data tag configuration

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.

google tag manager structured data trigger configuration

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.

google tag manager structured data variable configuration

Once you’ve created these variables, you can use them in your tags.

google tag manager structured data meta description

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.

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Step 5: Test, saving and publishing

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!

google tag manager structured data preview

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:

google tag manager structured data end result

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.

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Read more: ‘Structured data with Schema.org and JSON-LD: the ultimate guide’ »