Croct vs. Google Optimize
If you are beginning to AB test the content on your website – or even if you have done it for some time already – you have probably asked yourself which tool you should choose. Understanding which of the available platforms best meets your team's maturity is essential.
Google Optimize inevitably stands out amongst many available alternatives. After all, it is free and connects with one of the market's most used suites.
If you use this tool as a beginner, you are probably happy with it. However, if you have been optimizing your site for a longer time, you must have noticed its drawbacks and are bound to require a more robust platform.
Since we realized that using Google Optimize paid version means having relatively high costs and many companies embrace its free version, we created this post to clarify the free version's limitations. Also, based on the most frequent questions our sales team gets, we will take a moment to discuss Croct's positioning concerning each of those factors.
Google has announced its decision to discontinue Google Optimize in September 2023. Click here to understand how this will happen and what you should do about it.
Croct vs. Google Optimize at a glance
The table below summarizes the differences between Croct and Google Optimize. Next, we bring you more details on some of the main points.
|Test Type||A/B test||A/B test, multivariate test, and URL redirect test|
|Scope||Multipage personalizations and segmentation based on a complete user history||Multipage personalizations (beta) and segmentation based on current session|
|Segmentation||Advanced (natural language)||Basic (combined filters)|
|Native Segmentation Variables||Page URL, UTM parameters, complete data about device, browser, operating system, session, complete user history, location, and e-commerce data.||Page URL, Google Ads campaigns, UTM parameters, device, time since the first session, referrer page, and location.|
|Segmentation with external data||Yes||Yes|
|Simultaneous experiences||Unlimited||Up to 10|
|Performance and impact on SEO||Low||High|
|APIs||Evaluation, data import and export||No|
We recently published an article on the importance of thoroughly analyzing the user journey before optimizing a website. To make practical aspects of such a mindset possible, Croct uses the user browsing history to create first visit personalizations, for example, while still offering complimentary content for later interactions.
On the other hand, Google Optimize takes the context of the particular current session. It may be satisfactory if you need to test only a few elements within one specific flow. However, it becomes a critical drawback when your experiments require a thorough understanding of the user journey.
Website optimization processes require you to segment part of the traffic to ensure results accuracy. Every experiment needs a specific segmentation approach, and the necessary data for each one is not always available. This is why Croct splits segmentation into two types, one based on information available within the platform itself and another based on external data.
Native segmentation variables
Google Optimize offers the following parameters for defining an audience:
- Page URL
- Google Ads data (campaign, ad group, and keywords)
- UTM parameters (source, medium, campaign, content, and term)
- Device (device category, browser name, and operational system name)
- Time since the first session
- Referrer page URL
- Location (city, state, and country).
These variables enable creating browsing experiences closer to the current user session context, which might be enough for basic testing.
However, the more you know about your audience, the broader the spectrum of experiences that could better resonate with users.
This is why Croct's segmentation parameters go beyond and include the whole user journey. Enriching a user profile allows you to use:
- Page URL
- UTM parameters (source, medium, campaign, content, and term)
- Complete device, browser, and operational system data
- Complete session and user history data
- Location (city, state, country)
- Complete e-commerce data, including complete cart information (products, coupons, etc).
Segmentation with external data
For the sake of flexibility, both Google Optimize and Croct enable the use of external data, which in each platform comes from different sources.
Google Optimize paid version offers an integration with Google Analytics that enables the use of its audience data for segmentation, which includes the possibility of identifying marketing channels without UTMs (organic traffic from specific sources, for instance). This isn't possible with the free version, though.
Besides Google Analytics data, Google Optimizer enables the use of:
- Variables from the data layer
- First-party cookies
You can use data imported into Croct in real-time and whenever necessary afterward. It means you could use data collected in a given session to optimize later sessions even after a couple of days have passed.
Suppose your business model is based on annual or monthly subscription pricing options. You could, for instance, use information related to acquisition campaigns or visualized plan offers to personalize content the user will see on the website. Or yet, use information filled into forms, such as texts and values, to segment a test or dynamically personalize content.
Neither Croct nor Google Optimize currently enable the use of information available in local or session storage for segmentation or personalization.
Limited amount of simultaneous experiences
Google Optimize's free version limits simultaneous experiences on a website to a maximum of 10 (including both AB tests and personalizations).
Croct currently doesn't impose any limits regarding the number of experiences simultaneously undertaken.
Segmented website traffic usually requires parallel testing.
Google Optimize does enable parallel testing based on segmentation, though it does not allow segment prioritizing, nor can it guarantee that intersections don't occur. Consequently, a user could participate in several tests simultaneously.
Croct, on the other hand, allows you to create experiences prioritizing rules to prevent the same user from participating in more than one experience simultaneously. This accelerates the optimization process, as you don't have to wait until a test with a given audience finishes before starting a new one.
Check out this blog post for a view on the matter in greater detail.
With so many segmentation possibilities, the platform dashboard must provide high granularity reports of the personalized experiences. Croct dashboards enable real-time tracking of each experience, including information on:
- Audience size
- Number of users and sessions in a given period
- Share of website users reached
- Website personalized areas
- Products sold
- Conversion rate (per device).
The information above supports a complete mapping of the conversion funnel with filters that detail the funnel by, for instance, device and date.
Croct uses the Bayesian approach for AB tests analysis. See this post for a clear vision of how experiment data is processed and which metrics are available.
Google Optimize allows seeing only the final results of experiments, which leads its users to Google Analytics to obtain more detailed metrics. However, despite providing more information, Google Analytics does not enable you to automatically view segmented data neither from experiences nor from advanced segmentation. You must create customized segments and reports, making such a process considerably more complicated.
Croct's dashboards present highly refined information. Nevertheless, some of our clients choose to produce even more granulated reports by crossing Croct's data with those from third-party sources. Croct has developed a data export API for that, which isn't available in Google Optimize. It allows you to export data related to events, users, sessions, experiences, and tests to datasets, besides performing cross-analysis with data from sales and paid ads, among others.
Other event collecting tools, like Segment and Snowplow, also provide data export. However, the difference is that Croct has integrated it into its AB testing and personalization functionalities.
Identifying someone connected to several devices as a unique user is also one of Croct's advantages. As the user journey gets increasingly complex, this functionality becomes extremely important for offering experiences that link into each user's context.
Recognizing a user at every interaction with your brand is table stakes to creating complete browsing history. It also allows you to use progressive profiling techniques for drawing coherent user context as they browse through channels and devices.
To know more about this feature, check the article we wrote about it.
Visual editors are common in traditional CMSs and simple AB testing platforms, where page style is also editable, besides copy and images. However, those tools offer users only static content, since it is delivered in HTML with inline CSS.
Google Optimize offers a visual editor allowing users to make their own page changes, while Croct uses a headless CMS for content distribution. Personalizing and testing style attributes are nevertheless possible: since Croct delivers dynamic content, it is possible to test alternative layouts simultaneously.
Check the post we wrote about CMSs comparison and details on how headless CMSs ensure, at the same time, security and flexibility for developers, designers, and marketing professionals.
Both Google Optimize and Croct offer preview tools that allow you to visualize content to validate it before experiences are up and running.
Croct enables the use of variables not only to create segments but also to create dynamic content, which increases the scale and impact of AB testing and personalization.
An example might clarify the benefits of creating dynamic content: imagine you would like to personalize a banner text to show the name of the current city where the user is located. Doing it with Google Optimize means limiting the AB test to 10 cities and creating a different experience for each one. With Croct, you could create a single experience and use the city name as a dynamic content attribute.
Google Optimize works as a mask upon a website, which means that when a user accesses a page, the original content is loaded first, and only then does the personalized content gets loaded upon it. This reduces loading speed and causes undesired effects such as page flickering.
Croct, on the other hand, delivers dynamic content, meaning page elements (banners, images, copy, etc.) are natively mutable. Croct's personalization engine selects which experience must be applied at runtime, and all content is loaded at once.
Croct's API latency is below 100 milliseconds, while average websites may load in 3 to 5 seconds. Therefore, Croct's performance doesn't impact page load time.
AB test configurations are set only through its interface in Google Optimize, not through an API, which limits integration with other systems.
Croct, on the contrary, offers several APIs for integration with other systems, enabling different ways to track events, segment, and import and export data.
To know how this can suit specific business needs, read more in the post we wrote about the advantages of using a headless and API-first CMS.
The more you learn about optimizing, the more complex the hypotheses to test will be.
Google Optimize could be a good tool for teams and professionals initiating their adventure into the universe of testing and personalization. However, as knowledge evolves and teams become more mature, new needs, such as using a standardized design system, emerge, and Google's limitations begin to show.