This came as an unwelcome surprise for anyone working in the experimentation industry. Even if you didn’t use the tool itself, it was the first tool most newcomers used to get themselves into experimenting on their websites.

For a while, Google Optimize going away was everything people talked about on Twitter and LinkedIn.

Exporting Experiment Data From Google Optimize

Since several of our existing clients asked for it, we built Google Optimize Data Exporter to store your experiment data for as long as you need it. It supports almost any data destination, including popular ones like Google BigQuery, Amazon S3 and Snowflake.

Google Optimize Data Exporter runs on the same robust and scalable Reflective Data Infrastructure that you hopefully already know and love.

We’ve made the process of exporting your Google Optimize data as simple as possible. Here’s a quick overview.

1. Planning and scoping

Get in touch with one of our data analysts to plan your Google Optimize Data export. The main questions to answer are the list of experiments, dimensions, metrics, time frames and the data destination you wish to use for your Optimize data export.

2. Data export and storage

Executing the plan. Our data analyst will configure Reflective Data Export System to pull the requested data from your Google Optimize instance and store at your chosen data storage destination.

Most exports use Google BigQuery as a data destination.

3. Reporting and consultation

The post Export Experiment Data From Google Optimize – While You Still Can appeared first on Reflective Data.

Custom Events provide a perfect solution for adding context and tracking more specific user actions. In this article, we are giving you a good amount of ideas for custom events you should implement on your own and/or your clients’ websites.

This post is divided into sections by different event categories so you could skip the ones that are not relevant for you.

Clicks

For almost all websites, the most common user interaction is a click. By default, Google Analytics isn’t very good at tracking them. Let’s see how we could improve this situation.

Navigation clicks

Tracking usage of the main menu, sidebar and other navigation elements is critical. This is how your visitors explore your business and move in the funnel.

Detecting navigation interactions is easy with Google Tag Manager and sending data to Google Analytics works as with any other event.

Since there may be several navigation elements containing links to the same page, it is important to also pass the information about which navigation was used. For example, you might a have link to your blog both in the header and in the footer.

Recommended event parameters:

category: click
action: top-navigation, sidebar etc.
label: link text
non-interaction: false

CTA clicks

Tracking clicks on all of your CTAs (call to actions) is extremely important if you have more than one CTA on a single page pointing to the same location (i.e. long-form sales pages).

Don’t forget that buttons like “Get a Quote”, “Add to Cart” and “Checkout” are also CTAs.

Setup is the same as with generic click tracking using GTM.

Recommended event parameters:

category: click
action: CTA
label: text (and index the same CTA appears multiple times)
non-interaction: false

Outbound link clicks

Also known as tracking website exits, this custom event tells you exactly to which external pages people navigate from your site.

Again, setting this up is quite easy with GTM.

Recommended event parameters:

category: click
action: outbound link
label: link URL - link text
non-interaction: false

File download clicks

Doesn’t matter if you provide whitepapers, ebooks, PDFs, or other types of downloadable files, you should be tracking how often they get downloaded.

There are some really good tutorials online but we recommend setting it up using Google Tag Manager. A simple “just links” click trigger with a regex that matches desired filetypes should work just fine.

Regex Example:

\.(pdf|docx)$

Recommended event parameters:

category: click
action: download
label: filename / link text
non-interaction: false

Rage clicks

Visitors rage clicking on certain elements on your website is a good indicator of a UX error. For example, people may click on a blue text that is not a link or on an image that has no click functionality.

We have a separate blog post about tracking rage clicks using Google Tag Manager and Google Analytics.

Recommended event parameters:

category: click
action: rage click
label: element selector
non-interaction: false

Button clicks

Your website is likely to have all sorts of clickable buttons. There might be some other ways for you to get an overview of the usage of the features related to those buttons but knowing how many clicks each button received definitely helps.

Some ideas for which buttons should be tracked:

• Add to wishlist/favorites
• Add/remove item from cart
• Update cart
• Continue shopping
• Log in/out
• Register
• etc.

Recommended event parameters:

category: click
action: button
label: button text/description
non-interaction: false

Form Interactions

When it comes to tracking forms, I would like to recommend a few good articles by Simo Ahava that cover everything you need for getting started.

• Track Form Engagement With Google Tag Manager
• Track Form Abandonment With Google Tag Manager
• Form Field Timing With Google Tag Manager

Since forms are the most important part of many websites (i.e checkout, lead form etc.) you should really nail tracking them correctly.

A/B Testing

Experiment and Variation

Most A/B testing tools provide some sort of integration with Google Analytics. Most of them, though, are using custom dimensions. A problem with custom dimension based integration is that you need to make sure that the dimensions aren’t overlapping between experiments because otherwise, you might end up overwriting the dimension value for some experiments.

What we recommend having, besides the default integration, is a secondary event-based integration. That is, sending a custom event for every running experiment in a following format:

category: ab testing
action: experiment ID
label: variation number
non-interaction: true

PS! One event per experiment-variation combination.

This gives you raw information about each experiment and variation that the visitor saw. You can easily use this information in your custom segments or reports.

Every testing has a bit different solution for exposing experiment data to the front-end but here are a few links that should be helpful.

• VWO – instead of custom dimension, send this data using custom event action and label.
• Google Optimize – this allows you to get experiment data to the datalayer, now send it using a custom event.
• Optimizely X – access data about live experiments using Javascript.

Google Optimize Anti-Flicker Snippet timeout

If you have any experience with JavaScript-based A/B testing and/or personalization tools you know that flicker can be a real headache.

In case your tool of choice is Google Optimize, you should be using their official anti-flicker snippet to minimize the flicker effect.

We wrote a full separate article on Tracking Optimize Anti-Flicker Snippet Timeout in Google Analytics.

Recommended event parameters:

category: optimize
action: snippet timeout
label: true/false
non-interaction: true

Scroll depth

Whether you are working with a blog, some landing pages or any other page that is longer than a fold, you want to know how far down do the visitors scroll.

It used to required some custom Javascript but now, tracking scroll depth is a built-in feature of Google Tag Manager.

Recommended event parameters:

category: scroll
action: scroll depth threshold
non-interaction: false

Social interactions

While Google Analytics has a dedicated feature for tracking social interactions, having this data in custom events gives you more flexibility in reporting.

There is a really thorough blog post about tracking social interactions using Google Tag Manager – although, if you want something simpler, tracking clicks on your social icons is a good starting point.

Recommended event parameters:

category: social
action: share/like/follow
label: social platform
non-interaction: false

Video events

Doesn’t matter if it’s a sales video, a video that explains how your product works or a tutorial – you do care about how many people start the video and how far through will they make.

Google Tag Manager provides a really easy solution for tracking YouTube videos but tracking others such as Vimeo is completely doable as well.

Recommended event parameters:

category: videos
action: start/pause/percentage
label: video id
non-interaction: false

Errors

No matter how good your site is, there will always be errors. Since errors are directly related to bad user experience, tracking them is absolutely crucial.

The first step here should be sending your Javascript errors to Google Analytics. Next, consider sending other errors like popup alerts and system errors as well.

Recommended event parameters:

category: error
action: error message
label: feature or other relevant information
non-interaction: true

reCAPTCHA bot score

Google Analytics does have a simple bot-filtering system in place but it comes nowhere near catching all the bots that visit your site. Even tools like reCAPTCHA by Google can’t usually say for sure whether a visitor is a bot or a human but they can give you a score (from 0.1 to 1). Simo Ahava has put together a great tutorial for tracking the reCAPTCHA both score using Google Analytics custom dimensions.

Recommended event parameters:

category: reCAPTCHA
action: reCAPTCHA answer
label: reCAPTCHA score
non-interaction: true

Don’t forget to test whatever new custom event you add to your setup.

Should you have any questions related to custom events in Google Analytics, shoot them in the comments below.

PS! If you need help with implementing custom events, you can hire us to help you out!

Photo by Annie Spratt on Unsplash

The post Data You Should Be Tracking Using Google Analytics Custom Events appeared first on Reflective Data.

In case your tool of choice is Google Optimize, you should be using their official anti-flicker snippet to minimize the flicker effect.

<!-- Anti-flicker snippet (recommended) -->
<style>.async-hide { opacity: 0 !important} </style>
<script>(function(a,s,y,n,c,h,i,d,e){s.className+=' '+y;h.start=1*new Date; h.end=i=function(){s.className=s.className.replace(RegExp(' ?'+y),'')}; (a[n]=a[n]||[]).hide=h;setTimeout(function(){i();h.end=null},c);h.timeout=c; })(window,document.documentElement,'async-hide','dataLayer',4000, {'OPT_CONTAINER_ID':true});</script>

Looking at the anti-flicker snippet (previously known as page-hiding snippet), you see that the default timeout is set to 4000ms. That means that, potentially, some of your visitors may see a blank white page for 4 seconds.

Since four seconds is a long time, many companies reduce it. A common timeout I’ve seen is 2 seconds. Changing the maximum timeout to a shorter period, although, means that there can be a good amount of people to whom the snippet occasionally times out.

When the anti-flicker snippet times out, no experiments will be loaded on that page load (people will see the control for all experiments and personalizations) which can lead to a user experience where a single user is seeing different variations in single session.

What you probably want to know is the optimal timeout period for your website. To figure that out, you’d need to know how many timeouts occur with your current setup. Let’s take a look how to set that up using Google Tag Manager and Google Analytics.

Before moving forward, you should read about how the anti-flicker snippet works.

Catching the timeout

To make this a little bit easier for us, Google has added a variable in the data layer that indicates whether the snipped has timed out or not.

You can access this variable like so:

window.dataLayer.hide["GTM-xxxxxx"] where GTM-xxxxxx stands for your Optimize container ID.

To make sure it’s not too easy, though, they don’t push this variable into the data layer as you normally would. This means you can’t access it using GTM Data Layer variable nor the Custom Javascript variable.

What you need is a Custom Javascript function variable in GTM to check the value.

Here’s the function you can use

function () { 
    if ( window.dataLayer.hide ) { 
        return window.dataLayer.hide["GTM-xxxxxxx"]; 
    } 
}

And here is the same function implemented in Google Tag Manager.

PS! In the beginning, the value is always true, it turns to false if the timeout period is over and it managed to load Optimize before this happened (the snippet did not time out).

Our recommendation is to check the value on GTM’s default DOM Ready event.

Sending data to Google Analytics

This part is quite straightforward for anyone that has used GTM to send custom events to Google Analytics so let’s get right to it.

1. Create the DOM Ready trigger

In case you haven’t configured this default trigger in GTM, go ahead do it now.

2. Create a new Tag for sending the event to Google Analytics

Create a new Tag with a tag type of Google Analytics: Universal Analytics and choose track type of Event.

These are the recommended event parameters but you can use whatever works for you.

Category: optimize

Action: timeout

Label: true/false (using the Custom Javascript function variable you created before)

Non-Interaction Hit: True (because it’s not related to a user action)

That’s it. This is all you need to start tracking Optimize anti-flicker snippet timeouts using Google Tag Manager and Google Analytics.

How to use this data?

Your goal should be to find the optimal timeout duration for your website and audience. The percentage of users who experience the timeout should be kept under 10% and you might consider excluding those with timeouts from your post-analysis process using a custom segment in Google Analytics.

Any questions or ideas? As always, feel free to post them in the comments below.

The post Tracking Optimize Anti-Flicker Snippet Timeout in Google Analytics appeared first on Reflective Data.

So, what’s our verdict? Is it going to replace other tools like Optimizely or VWO? In this article, we are going to tell you exactly what we think about Google Optimize.

Seamless integration with other Google products

If you (like we) are using Google Analytics as your main analytics platform and Google Tag Manager as your main tag manager then it’s logical step to start using Google Optimize as your main testing platform?

Well, the integration is truly simple. The installation with Google Tag Manager is easy, here’s how it’s done. Next, just link Optimize with your Analytics property and view and that’s it.

All your experiments will automatically show up in Google Analytics, take a look at Behavior -> Experiments.

For more advanced analysis we recommend creating segments or filters for each experiment and variant. That way you will be able to really see how your experiments are changing the way your website’s visitors behave.

Here’s how to create a new segment for a specific experiment and variant.

So, if it works so well with the tools that you are already using, doesn’t it make sense to just start using it as your main A/B testing platform? Okay, let’s take closer a look at Google Optimize’s pluses and minuses.

The bad

I am going to start with some of the aspects that I don’t like so much about Google Optimize.

Just a little notice that besides Google Optimize, I am also actively using Optimizely and VWO, plus I have been experimenting with an open-source testing tool called Wasabi and even built an A/B testing solution based on Google Tag Manager.

Three experiment limit

Today, Google Optimize allows optimizers to run only three experiments at the same time. You can have more as a draft or ended but not running.

That can be a real issue for companies who are really into testing, especially for those who like to run separate tests for mobile and desktop.

For those just starting off with their A/B testing game, three experiments at once could be just enough!

Limited code length

That’s right, with Google Optimize, your scripts are limited to 10240 characters.

This might not be an issue if you are just using the visual editor for some copy changes but if you are building a more advanced experiment this can become really annoying. Quite often I end up splitting my code into three or four sections.

No image upload functionality

There is no way to upload images into Optimize’s servers. You will have to upload them to your own server or use third-party services.

While this might not be a big issue for some, I found it really bothering. All of the other testing tools that I use have this feature.

Preview mode is a pain in the…

As seasoned A/B testers know, your experiment just doesn’t look right in the editor. To see the real picture, you have to use preview mode or URL-s.

When I work with VWO or Optimizely, I always have the editor open in one window and preview in another one. As I make changes in the editor I simply press “Save” and almost immediately preview my changes in the preview mode.

When it comes to Google Optimize, the preview doesn’t get updated unless you click on “Save” and “Done”, the latter exits the editor! After doing so you will need to re-activate the preview mode and then load the editor again to make some changes. And that’s how it goes, over and over.

This is why setting up a more advanced experiment takes so much longer in Google Optimize when compared to some other testing tools.

The good

If the “bads” didn’t scare you away, let’s take a look at some of the reasons why I really like Google Optimize.

Works perfectly with other Google tools

As I already mentioned, if you are already using Google Analytics and Google Tag Manager, installing and using Google Optimize goes super smoothly.

While you can integrate Google Analytics with other testing tools, there will almost always be some issues with that. Most common is that the numbers just don’t match up. Google Optimize’s data is based on Google Analytics, so that won’t be an issue.

Very nice visual editor

Whether you are a beginner in A/B testing, don’t write any code or just most of the time run simpler A/B tests, you will really like the visual editor that comes with Optimize.

It is super easy to use, a simple copy or an image change will take a second. Really, it’s that simple.

Growing community

As with other free tools, especially those from Google, the community tends to be huge and rather active. That means you can expect to see all sorts of tutorials and other cool stuff related to Google Optimize, online & for free.

While paid tools might (sometimes) have a good support system, I almost always prefer an active community on StackOverflow where nearly all of the issues have already been solved.

Right now, the community seems to be rather small but I am sure it will grow pretty fast.

Does everything it’s paid competitors do

Doesn’t matter if you come from Optimizely, VWO or some other similar testing tool, you will find all the features you loved about them in Google Optimize. Maybe in a bit different format, but most of them are there.

Of course, there are some slight differences, like missing image upload option etc. but for most of them, you can easily find a workaround.

IT’S FREE

Best things in life are free, so is Optimize.

Just sign up with your Google account, add the snippet on your website, link your Analytics property and start testing. It’s that simple.

Other testing tools are very expensive, especially if you have a lot of traffic and your optimization process is not very effective (yet).

Conclusion

While it has its minuses, Google Optimize is almost as good as any other A/B testing tool and you will definitely like using it.

I really hope that some of the issues I listed in this article are going to be fixed in the nearest future. It’s a rather new tool after all.

Three test limit will most probably stay to keep you considering upgrading to Optimize 360 but if testing is just something you do besides other stuff, three tests can easily be enough for you.

Are you new to A/B testing?

Go ahead, install Google Optimize on your website today and get to know what optimizing your website really means.

Are you already running a few tests every month?

No matter what tool you are using, give Optimize a try. It’s free, you don’t have anything to lose.

Are you an hard-core A/B tester?

Well, if you know for sure that three test limit is just not enough for you, you should probably wait before you cancel the tool you are currently happy with. But still, consider giving Optimize a try. Maybe you have another website where you run fewer tests or maybe you will like the platform so much that will consider the paid version.

Whatever your background is, my recommendation is to try new things (and tools). That’s the whole point of testing and optimization, right?

Click here to get started with Google Optimize.

Have you already tried Google Optimize? Let us know what you think about it in the comments below.

If you liked the article, please subscribe to our newsletter to get posted on what’s new in digital analytics!

The post Using Google Optimize For 3 Months appeared first on Reflective Data.

We finally received our access around four months later and now we have been actively using it for three months.

Here’s what you need to know in order to get started with running experiments on your website using Google Optimize.

The wait is finally over!

I can’t be the only one who went to see if Google Optimize is available already and they just forgot to tell me.

After waiting for four months I finally got an email announcing that the wait is over for me. Not everyone got their access at the same time.

Needless to say, I was super excited about the email and went straight to Optimize to install in on a test website.

Installation process

The process of getting Google Optimize ready for testing is rather straight forward.

The first thing you have to do is to link your Google Analytics property. Just click on “LINK PROPERTY”, choose right property and the views you want to use for testing.

Next up is the snippet, for most websites that means modifying the Google Analytics snippet.

Keep in mind to insert the snippet as close to opening <head> tag as possible!

If you are using Google Tag Manager, refer to this article when installing Google Optimize.

We also recommend installing the Page-Hiding script to make sure there is as little flicker as possible.

And that’s it, Google Optimize is now installed on your website!

Creating your first experiment

If you have worked with Google products and at least some sort of A/B testing software then it should a be a really simple process. And if you haven’t, you will still most probably figure everything out pretty fast!

In this example, we are going to create an experiment called “Homepage Subheading” that will run on our homepage.

On the next screen, you will need to choose an objective for this experiment. You can also choose multiple objectives.

The primary objective should be related to the KPI that this experiment should have an effect on. In our case let’s pick “Bounces”.

Next, you will have to choose targeting rules for your experiment. This can be an URL, a device category, geolocation etc. For this example, we are going to target only our homepage.

Now, let’s go ahead and create the first variation. Just click on “NEW VARIANT”. If you are going to have more than one variation, give them descriptive names, if there’s only one then “Variant 1” will work fine.

You can also change the percentage of visitors included in the experiment as well as the traffic split between the variants. In our case, we are targeting all visitors and use a 50/50 split.

This is what our experiment screen looks like.

Now comes the fun part, making the actual changes to your website.

In this article, I am not going into too much detail on how to set up A/B tests but Optimize’s visual editor is rather good and you can use it for simpler changes. For more advanced stuff, some coding skills are required.

Here’s how the actual editor looks like:

Once done with your changes, click “Save” and then “Done”.

Next, activate the preview mode and make sure your variant looks like expected, you can also share the preview URL with others. Or use it to preview on mobile devices.

Let’s take a look at our test experiment on Reflective Data homepage.

Everything looks perfect and thanks to the page hiding script, there was no flicker!

Once you are happy with your experiment click on “START EXPERIMENT” to set it live.

Analyzing the results

There is a slight delay in the data coming into Optimize. Expect to see first numbers around 12 hours after you started the experiment.

To see the results, navigate to the “Reporting” tab of the experiment page.

There you will see the number of sessions in total, and for each variant. As well as an overview of your objectives per variant.

The reporting screen actually looks pretty good and it’s a nice place to get a quick insight of how your experiments are doing.

For more advanced analyzing though, you should head to Google Analytics. Luckily, the integration between Google Optimize and Google Analytics is seamless.

Start by taking a look at the Experiments section in Google Analytics. BEHAVIOUR -> Experiments

To build some really useful reports, you should be using custom segments and filters. You can create a filter for a specific experiment and variant like this:

That way you can really compare the performance and effect of each variant.

Conclusion

Google Optimize is a powerful A/B testing tool that has almost all the features that do its paid (and expensive) competitors like VWO or Optimizely.

Should you cancel your current tool right away? No, but go ahead and give Optimize a try, it might do just what you are looking for!

One thing to keep in mind is that the free version of Optimize allows you to run only three tests at once, so if you are big on testing, you should pick something else. Google Optimize 360 to give an example.

In case you are new in A/B testing, absolutely go and install Optimize on your website. It’s the best way to get started, and it’s free!

At Reflective Data, we are going to keep on using it as the main testing platform for at least next 6 months.

Click here to get started with Google Optimize.

The post Getting Started With Google Optimize appeared first on Reflective Data.