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.
A superb A/B Testing tool for smaller teams.
Good tool for optimizing websites
Google Content Experiments: Quick and easy (and free) A/B/n testing you should already be using.
Pros:
* Easy to set up a test and use content …
Limited Testing Solution, but Not Without Value
FREE and integrated, but no advanced testing possibilities and harder setup
Google Content Experiments - Adequate and free
Google Content Experiments: Your Free Gateway to A/B Web Content Testing
Google Content Experiments Review #58,733 (probably)
Another Google Freebie, but could be improved for real testing strategies
A great place to start your conversion rate optimization adventure. However the limited features will have you searching for a more advanced tool within a few months.
Not a bad tool, but not for the code-shy
Google CE Impressed Me
Pricing
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.
Entry-level set up fee?
- No setup fee
Offerings
- Free Trial
- Free/Freemium Version
- Premium Consulting/Integration Services
Would you like us to let the vendor know that you want pricing?
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Product Details
- About
- Competitors
- Tech Details
What is Google Content Experiments (discontinued)?
Google Content Experiments (discontinued) Competitors
Google Content Experiments (discontinued) Technical Details
Operating Systems | Unspecified |
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Mobile Application | No |
Comparisons
Compare with
Reviews and Ratings
(74)Attribute Ratings
Reviews
(1-2 of 2)Integrates well with Google Analytics
- Real time data
- Personalization
- Back end development needed for detailed tests.
- Some training required.
- 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
- Standard visitor segmentation
- 100%10.0
- Behavioral visitor segmentation
- 100%10.0
- Traffic allocation control
- 100%10.0
- Website personalization
- 100%10.0
- 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
- Increased ROI
- Faster decision making
A superb A/B Testing tool for smaller teams.
- 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.
- 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.