Integrates well with Google Analytics
We use Google Content Experiments for AB testing in our Digital Marketing Department. Google Content Experiments allows us to test …
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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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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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 Systems | Unspecified |
|---|---|
| Mobile Application | No |
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Score 6 out of 10
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Verified User
I have used Google Content Experiments as a great way to introduce various businesses to the idea of conversion testing and to create a conversion culture. Its ease of use, the fact that it is available to anyone that uses Google Analytics and also its agreeable price tag (it is free,) have made it my go to tool when I need to demonstrate and educate businesses to the value of conversion testing.
- Quick and easy to create and set up experiments
- Results are presented in a way that is familiar and easy for any Google Analytics user to understand. So is great for beginners to conversion testing
- Already integrated into Google Analytics and can measure results against your existing conversion goals
- Allows nine possible variants to be A/B tested
- Features more than one testing methodology, Bayesian (Multi-Armed Bandit,) and Full Factorial
- Allows the user to select one of three possible confidence thresholds to ensure that experiment results are robust
- Great value, it is free!
- Should include a multivariate testing (MVT) option. Whilst the ability to test nine possible variants using A/B/n testing is great for strong bold tests, the ability test multiple elements on the same page is essential for a successful testing program
- Reliance on your IT department to code the variants you wish to test and also to insert the experiment code on the test page can be an issue which may slow the testing process for some businesses
- It is very easy to make the wrong decisions and find a false winner. A high level of conversion rate optimisation knowledge is needed to ensure that the results from the experiment are valid and of statistical significance
- Should not default to Bayesian (multi armed bandit,) methodology and a 95 percent confidence threshold as a those new to testing may not fully understand the impact of these setting and whilst these options can be changed in “Advanced Options” the combination of these two factors could easily find an incorrect winner
- Google Experiments should not declare the winning variant as it does not understand your business or business cycles, so can easily find a false winner. Although the option to set a minimum time for the experiment to run before declaring a winner goes some way towards mitigating this issue it is limited to a maximum of two weeks which may not be long enough for some businesses
- Google Content Experiments has shown a great return on investment as it is a free tool that has been used to answer various business questions.
- I have Google Content Experiments to demonstrate various percentage uplifts to key metrics across the business
- Maxymiser,Visual Website Optimizer
If you are looking for a more advanced great value for money solution I would recommend investigating Visual Website Optimizer. For a more powerful enterprise level solution with the option to have a fully managed service I would recommend Maxymiser.
1
Used by Marketing to ensure that all landing pages perform at their highest potential
2
The two main skills need to use Google Analytics Content Experiments are:
- A strong understanding of conversion rate optimisation and testing methodologies
- Some coding knowledge to build the alternative test variants and deploy the test code to the test page
- Improving landing page conversion rates
- Developing a testing culture within the business
- An always on back up testing tool should it be needed
No
- Price
- Vendor Reputation
- Existing Relationship with the Vendor
- Analyst Reports
The most important factor in choosing Google Content Experiments was the fact that is was already available to us through Google Analytics
Ensure that we research all possible testing methodologies and available options, then map those onto a matrix to ensure that you are selecting the most appropriate tool for the job.