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Google Content Experiments (discontinued)

Google Content Experiments (discontinued)

Overview

What is Google Content Experiments (discontinued)?

Google Content Experiments was a tool that can be used to create A/B test from within Google Analytics. It has been discontinued since 2019, and Google now recommends using its Google Optimize service for A/B testing.

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Pricing

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Unavailable

What is Google Content Experiments (discontinued)?

Google Content Experiments was a tool that can be used to create A/B test from within Google Analytics. It has been discontinued since 2019, and Google now recommends using its Google Optimize service for A/B testing.

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VWO is an A/B testing and conversion optimization platform that enables growing businesses to conduct qualitative and quantitative visitor research, build an experimentation roadmap and run continuous experiments on their digital properties.With its 5 capabilities Plan, Track, Test, Analyze, and…

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Product Details

What is Google Content Experiments (discontinued)?

Google Content Experiments was a tool that can be used to create A/B test from within Google Analytics. It has been discontinued since 2019, and Google now recommends using its Google Optimize service for A/B testing.

Google Content Experiments (discontinued) Competitors

Google Content Experiments (discontinued) Technical Details

Operating SystemsUnspecified
Mobile ApplicationNo
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Comparisons

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Reviews and Ratings

(74)

Attribute Ratings

Reviews

(1-2 of 2)
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Score 9 out of 10
Vetted Review
Verified User
Incentivized
We use Google Content Experiments for AB testing in our Digital Marketing Department. Google Content Experiments allows us to test bounces, duration, click-throughs and session duration of users that enter our consumer websites. This tool allows us to test different marketing messages and designs to enhance the users experience, and helps us convert shoppers into buyers.
  • Real time data
  • Personalization
  • Back end development needed for detailed tests.
  • Some training required.
Google Content Experiments is suited for large and small organizations, no matter your organizational goals. It is not recommended for organizations that are only interested in qualitative data, as there are other tools for receiving specific user experience feedback. It is also not recommended that you implement tests without some sort of goal in mind.
Testing and Experimentation (19)
91.57894736842104%
9.2
a/b experiment testing
90%
9.0
Split URL testing
100%
10.0
Multivariate testing
100%
10.0
Multi-page/funnel testing
90%
9.0
Cross-browser testing
80%
8.0
Mobile app testing
80%
8.0
Test significance
90%
9.0
Visual / WYSIWYG editor
100%
10.0
Advanced code editor
90%
9.0
Page surveys
80%
8.0
Visitor recordings
80%
8.0
Preview mode
80%
8.0
Test duration calculator
100%
10.0
Experiment scheduler
100%
10.0
Experiment workflow and approval
80%
8.0
Dynamic experiment activation
100%
10.0
Client-side tests
100%
10.0
Server-side tests
100%
10.0
Mutually exclusive tests
100%
10.0
Audience Segmentation & Targeting (4)
100%
10.0
Standard visitor segmentation
100%
10.0
Behavioral visitor segmentation
100%
10.0
Traffic allocation control
100%
10.0
Website personalization
100%
10.0
Results and Analysis (8)
98.75%
9.9
Click analytics
100%
10.0
Form fill analysis
100%
10.0
Conversion tracking
100%
10.0
Goal tracking
100%
10.0
Test reporting
90%
9.0
Results segmentation
100%
10.0
CSV export
100%
10.0
Experiments results dashboard
100%
10.0
Platform Integration Features
N/A
N/A
  • Increased ROI
  • Faster decision making
Google Content Experiments is a free tool and the leading tool in the industry. It's pretty simple to set up a test and use content experiments to monitor objectives once Google Analytics is installed. Less experienced team members can run tests with some training. There are plenty of resources for instructions to use the tool through Google's documentation, which sets it apart from other tools.
Using the free tool, overall "live support" is limited. However, there are plenty of online resources to get started. If you need handheld support, it is best to upgrade the service or hire a developer through one of Google's partner agencies. There could be more support for understanding what makes a test useful or not.
Score 7 out of 10
Vetted Review
Verified User
Incentivized
Google Content Experiments was one of the tools that we used when looking to do A/B testing within the organisation. Typically we would work with customers to determine what elements were important to their business and use this to come up with ways to validate the ideas or disprove them. Content Experiments was ideal as it was a free tool - that could be rolled up quite quickly and was free!
  • Has a great analytics engine in its backend which uses multi-arm bandit methodology- and thus can perform multiple variations at once.
  • Multi-arm bandit means that it's also really effective in finding the winning solution.
  • It can be based on Analytics Goals via Optimize so you can drive things that are important to the business.
  • Their documentation is not the best and it's quite a steep learning curve.
  • They also don't tell you particularly well what sorts of things you should be testing.
  • Compared to other suppliers of A/B testing tools- it needs a simpler interface. Optimize is starting to answer that - but is still quite Beta-like.
Google Content Experiments (along with Optimize) are best suited to get your team started on the path of A/B testing. It's a cheap and low-risk way to test, and also ties well into Google Analytics. Its integration with Optimize is built on top of Google Tag Manager so again this is well-understood technology and chances are most businesses would have someone who is familiar with it.
  • Doing good experiments/Optimize has helped to take out the guesswork of the things we want to implement.
  • We have done fairly complex changes such as changing navigation and managed to see improvements outcomes immediately before we have to request developer.
  • Our teams have become more data centric in how they approach changes.
It frankly was down to cost. Other platforms offer better targeting etc., however, we found that unless we could demonstrate early value - we didn't get budget sign off. Our teams aren't usually large enough to justify the cost and time to invest in a more complex platform - so Google's tech fits the bill perfectly.
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