Chances are, you’ve heard of Google Optimize by now. It’s Google’s solution for A/B testing and personalization. It launched in beta last year, which left optimizers around the world waiting in line to try it out. Now that it’s out of beta, you can give it a try without the wait.

But what can you expect? How do you configure it properly? How do you run your first experiment?

First, why Google Optimize over other testing tools?

Marketers love tools and tools love marketers. What results from this romance is tool overload. You have a tool for keyword ranking, a tool for broken links, a tool for social media mention monitoring, a tool for social media analytics, a tool for… you get the idea.

Google Analytics has been trying to diminish tool overload and bring marketers out from their silos for years. It addresses all channels, all conversions. It’s a central heart instead of multiple arms.

As Sean McQuaide of LunaMetrics explains, Google Optimize’s native integration with Google Analytics is what sets it apart…

“SeanSean McQuaide, LunaMetrics:

“Enter Google Optimize, an A/B testing and personalization tool that uses Google Analytics data to power your CRO efforts. Obviously A/B testing is nothing new, neither is serving personalized content based on customer behavior. The true progress here is how Google Optimize pairs with Google Analytics, and how easily we can tie our experiments to KPIs in Google Analytics.” (via Online Behavior)

Sean believes the deep integration allows for…

  1. Easier setup.
  2. More advanced targeting.
  3. More advanced reporting.
  4. Applying learnings faster.

It’s difficult to disagree that having Google Optimize data in Google Analytics and Google Analytics data in Google Optimize is a big competitive advantage.

Krista Seiden of Google, who gave an awesome talk on Google Optimize and personalization at CXL Live this year, gives some examples…

“KristaKrista Seiden, Google:

“One of the things that makes Optimize so powerful is it’s deep integration with Google Analytics. You can use your Google Analytics data to identify key segments of users to target users as audiences shared Optimize. Examples:

  • Loyal customers: Been to your site X times and purchased Y instances/value
  • Status groups: Premium frequent fliers, Economy standard fliers
  • Geo-location: Special offer for San Antonio residents

Once you’ve identified these key audiences, create a unique offer for each target group, and then use Optimize to target that offer to your intended audience.” (via Digital Debrief)

If you’re reading this, you’re probably already using a testing tool like Optimizely or VWO. So, why give Google Optimize a try?

  1. It’s a familiar UI.
  2. Your Google Optimize data will be available in Google Analytics and your Google Analytics data will be available in Google Optimize, allowing for: more advanced targeting, more advanced reporting, more advanced conversion tracking, etc.
  3. It’s free, so what’ve you got to lose?

Google Optimize vs. Google Optimize 360 (Free vs. Paid)

I know I just said it’s free, but of course, there’s a paid version: Google Optimize 360. If you’re a small to medium-sized business or just getting started with a testing program, the free version will work for you. If you’re a big enterprise or have a very sophisticated testing program, you’ll probably need the paid version.

Here’s the official breakdown of the differences between the two versions…

Google Optimize vs. Google Optimize 360

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So, to summarize, the limitations of the free version are…

  • No Google Analytics audience targeting.
  • Limited multivariate testing (16 variations).
  • Pre-selected experiment objectives. Google Optimize 360 allows you to go back and change the experiment objective to see how the experiment would’ve impacted other Google Analytics goals.
  • Limited concurrent testing (3 tests at a time).

Setting Up Google Optimize

Now, to get started, head to the Google Optimize site and click that big, green “Sign Up For Free” button.

Welcome to Google Optimize

Now you’re ready to create your account and container.

1. Creating an Account and Container

Choose an account name, first. This can be your domain, company name, whatever you’d like…

Creating Your Account

Google recommends opting into improving Google products, benchmarking and in-depth analysis. I recommend it as well since it’s a new(ish) product and the more info you can gather about it and how best to use it, the better.

Next, you need to add a container to your account. Your container name might be “CXL Blog” or “CXL Institute”, for example…

Creating Your Container

And you’re done! Now you should be looking at your Experiments view…


You can click the gray information icon in the right-hand corner of the view if you don’t see your onboarding checklist right away. Then you’ll see this on the right-hand side…

Onboarding List

Notice that “Manage accounts and users” is already complete. If you expand the checklist item, you’ll see this message…

An account and container have been created for you! Google Optimize uses accounts and containers to organize your experiments. An account is the top level of your organization hierarchy, and it usually represents a company. A container is located within an account and typically represents a website.

You’ll also see your Account ID and Container ID…

Container Info

2. Linking Google Analytics

Now Google Optimize will be encouraging you to start an experiment, but I recommend linking Google Analytics first. So go ahead and expand the second checklist item, “Link to Google Analytics”…

Linking Google Analytics

Click the blue “Link Property” button and you’ll be prompted to select a Google Analytics property…

Linking Google Analytics

Once you select a property, you’ll also be asked to select the view you’d like to link. Then just click “Link” and you’re all set.

3. Installing the Google Optimize Snippet

Now you need to install the Google Optimize snippet on your site. This is step three on your onboarding checklist…

View Snippet

Click the blue “View Snippet” button. You’ll end up seeing something like this…

Add Your Snippet

Note that Universal Analytics (analytics.js) is required to install Google Optimize.

Now, you have two options for getting this Google Analytics tracking code updated: manually updating each page or using Google Tag Manager.

With Google Tag Manager

I recommend using Google Tag Manager.

If you don’t already have it setup for your site, Chris Mercer taught a live course for beginners via CXL Institute. If you have Google Tag Manager setup, but aren’t sure how to use it effectively, Jacob Shafer taught a live course for intermediate folks. I’ve also written a beginner’s guide. This is a really valuable skill to have.

Sean explains why he thinks GTM is the way to go, too…

“SeanSean McQuaide, LunaMetrics:

“Why use GTM? Event tracking, that’s why. Google Optimize uses GA goals as experiment objectives and pulls data from GA to calculate experiment results. So if you want to test objectives that involve user interaction, you’ll need to set up an event-based goal first. The easiest way to do that is by using GTM.” (via Online Behavior)

So, head over to GTM and create a new tag. You’ll notice that Google Optimize is right there as a tag type…

Create a New Tag

Now enter your Google Analytics Tracking ID and your Optimize Container ID…

Tag Settings

If your tag settings here don’t match your tag settings for your Google Analytics Pageview tag, you will run into issues. So, be sure you’re using the same Google Analytics Tracking ID input and the same “More Settings” inputs.

Now you can choose your trigger options. I’m going to experiment on my entire site, so I’m going with “All Pages”, but you can choose whatever you’d like…

Trigger Rules

Save it, preview it, debug it. And you’re done!

Without Google Tag Manager

Without Google Tag Manager, you can simply follow the instructions given after clicking “View Snippet”. You’ll be adding a single line to the existing Google Analytics tracking code. Unfortunately, you’ll have to do this page by page, which is likely to be time-consuming.

Page-Hiding Snippet

Are you familiar with the flicker effect? The flicker effect is when the visitor is shown the control quickly before seeing the correct variant. Of course, this has a number of negative impacts on both user experience and the validity of your test results.

Google created the page-hiding snippet to prevent the flicker effect. Just insert it as high as possible in your <head>. So, that’s between <meta charset> and your Google snippets.

Here’s how to deploy it manually or via Google Tag Manager.

Setting Up an Experiment

On to the fun stuff! Now you’re going to create an experiment…

Create an Experiment

Experiment Types

When you click the blue “Create Experiment” button, you’ll be asked to enter the name of the experiment, the URL of the page you’d like to test and the type of experiment you’d like to run…

Creating an Experiment

Perhaps you’re familiar with all of these experiment types. If so, just skip ahead to the Configuration section. If not, here’s a little about each.

A/B Tests

This is the most familiar experiment type. You compare two versions of the same page to see which one performs better… A vs. B, control vs. variant. Visually, it looks something like this…

A/B Tests

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If you want to brush up on your A/B testing know-how, I recommend reading this massive, incredibly useful guide that Alex Birkett wrote.

Redirect Tests

Redirect tests are a type of A/B test, technically speaking. Instead of testing two versions of the same page, you’re testing two separate pages against each other. This is useful if you’re looking to test a complete redesign or even two different landing pages.

Redirect Tests

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Multivariate Tests

A multivariate test allows you to test multiple variants of multiple elements at the same time to see which combination produces the best results. So, here’s how that might look if you were testing two headlines and three hero images simultaneously…

Multivariate Tests

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Alex also has an article on when to do multivariate testing.


For the sake of simplicity, let’s continue forward with an A/B test. You’ll want to start by adding a variant to test against the control…

Add a Variant

Of course, that’s as easy as clicking +NEW VARIANT.

You can also change the variant weights and preview the variants here.

Google Optimize Visual Editor

Google offers a WYSIWYG visual editor, which should feel very familiar and intuitive to anyone who has ever used one before. (And you probably have… I’m using one right now to write this blog post.)

First, you’ll need to be using Google Chrome and install the Google Optimize extension for Chrome…

Chrome Extension

Here’s what you’ll see once you’ve grabbed the extension…

Chrome Extension

As I said, the experience is fairly straightforward and familiar. Here’s what you really need to know…

  1. The app bar at the top. Here you can change the experiment name and status, show changes, switch between variants, etc.
  2. The palette. This floats along as you scroll and contains all of the editable elements of your current selection.
  3. Current selection. In the screenshot above, I’ve currently selected the two lines of text before the bullets.

If you’re confused about anything as you get started, Google has a what’s what guide you can use.


When you scroll below the variant section, you’ll end up in the configuration section. Here, you can choose between either managing your objectives or your targeting.


First, choose your objectives…

Setting Objectives

You will be able to choose from basic objectives like pageviews, session duration and bounces. But what makes Google Optimize awesome is that you can also choose from any of the Google Analytics goals in your linked account.

In the free version, you can choose one primary objective and two secondary objectives. Remember that you can’t retroactively change these objectives in the free version, so be sure to choose all of the relevant objectives upfront.

You’ll also notice room to add a test hypothesis.


Here, you can choose the percentage of visitors to target and the weighting of visitors to target…

Targeting Who

So, in this case, I’m targeting 100% of my visitors and showing each of my two variations 50% of the time.

Now on to the when…

Targeting When

Instead of explaining all of these targeting options in detail, as Google does at each of the pages linked to below, here’s a high-level summary…

This is where, if you had Optimize 360, you could do audience targeting.


Reporting is another area where Google Optimize really shines. Krista explains how that native integration with Google Analytics comes into play again…

“KristaKrista Seiden, Google:

“Your test stats are available in the Reporting tab within the Optimize UI. They are also available in Google Analytics in a number of ways: Every hit from Optimize is sent to GA with an Experiment Name, Experiment ID, and Variant number automatically attached. This means that you can get much more creative with how you analyze your test data outside of the Optimize UI. You can:

  • Segment and add secondary dimensions to a report with Variant #, Exp ID, and Exp name
  • Create audiences and segments based on previous test behavior, and even target to future test experiments based on being a part of a prior test” (via Digital Debrief)

(Both of Krista’s quotes in this article were taken from an article on her blog, which you should read if you’re looking to go beyond the basics after this beginner’s guide.)

But, if you’re keeping it simple and sticking to the Google Optimize reporting UI, here’s what you’re working with…

  1. Summary Card: Here you’ll see the experiment status and a summary of the results (so far). The leader, improvement, probability to be best, etc.
  2. Improvement Overview Card: Here you’ll see how your control compares to the variants based on the objectives you set. Note that you can click the column headers to have the results sorted.
  3. Objective Detail Card: Here you’ll see the performance of each of your variants against whichever objective you’ve selected from the drop-down list. Note that at the beginning of your experiment, the graph will show more uncertainty, but that uncertainty will narrow over time as more data is collected.

Here’s an example of the summary card…

Summary Card

And also the graph from the objective detail card…

Objective Detail Card Graph


Google Optimize is relatively new and it’s going up against giants like Optimizely and VWO, but the value of the native integration is hard to ignore. Especially with a $0 price tag.

At the very least, create an account and run an experiment. Hopefully this guide makes that process even easier for you. Then, see for yourself how it compares with your current A/B testing and personalization tool.

Is anyone using Google Optimize or Google Optimize 360? Please let me know what you honestly think of it in the comments.

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