Google Analytics is perhaps the best-known web analytics product and, as a free product, it has massive adoption. Although it lacks some enterprise-level features compared to its competitors in the space, the launch of the paid Google Analytics Premium edition seems likely to close the gap.
$0
per month
Google Content Experiments (discontinued)
Score 7.3 out of 10
N/A
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.
N/A
Pricing
Google Analytics
Google Content Experiments (discontinued)
Editions & Modules
Google Analytics 360
150,000
per year
Google Analytics
Free
No answers on this topic
Offerings
Pricing Offerings
Google Analytics
Google Content Experiments (discontinued)
Free Trial
No
No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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—
More Pricing Information
Community Pulse
Google Analytics
Google Content Experiments (discontinued)
Considered Both Products
Google Analytics
No answer on this topic
Google Content Experiments (discontinued)
Verified User
Analyst
Chose Google Content Experiments (discontinued)
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 Website Optimizer was a better product but has been discontinued. We have also used Test and Target , which has more features but we have been doing fine with Google Content Experiments. Most testing situations can be handled with Google Content Experiments.
Google Content Experiments provides significantly more insight, historical data and analysis than Unbounce. However, if you do need a solution that offers a WYSIWYG editor, landing page hosting, and limited reporting and testing, Unbounce is a good all-in-one solution and that …
Google Content Experiment cannot compete with Adobe Test and Target, Quadratics or even Optimizley. It is harder to use with no editing interface, so pages must be actually developed. It doesn't allow for any advanced segmenting or multivarient testing. But it is free, so …
Google CE is free, Optimizely isn't plus only until recently I found out that Optimizely can work with multiple goals, however, this was found by meeting their employees at a trade show and not via their website.
We'd use content experiments as a complimentary testing tool alongside more comprehensive testing packages out there. As a free testing tool it does the job for basic A/B testing.
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.
Google CE does a great job streamlining tools and features. Optimizely does not offer nearly the same amount of tools or resources that G CE does. I would use CE in the future but stay away from Optimizely. Google also has a lot more resources for accruing knowledge on it …
Features
Google Analytics
Google Content Experiments (discontinued)
Web Analytics
Comparison of Web Analytics features of Product A and Product B
Google Analytics
8.4
11 Ratings
4% above category average
Google Content Experiments (discontinued)
-
Ratings
Lead Conversion Tracking
8.210 Ratings
00 Ratings
Bounce Rate Measurement
8.410 Ratings
00 Ratings
Device and Browser Reporting
9.211 Ratings
00 Ratings
Pageview Tracking
9.111 Ratings
00 Ratings
Event Tracking
8.411 Ratings
00 Ratings
Reporting in real-time
7.910 Ratings
00 Ratings
Referral Source Tracking
8.610 Ratings
00 Ratings
Customizable Dashboards
7.910 Ratings
00 Ratings
Testing and Experimentation
Comparison of Testing and Experimentation features of Product A and Product B
Google Analytics
-
Ratings
Google Content Experiments (discontinued)
9.2
1 Ratings
9% above category average
a/b experiment testing
00 Ratings
9.01 Ratings
Split URL testing
00 Ratings
10.01 Ratings
Multivariate testing
00 Ratings
10.01 Ratings
Multi-page/funnel testing
00 Ratings
9.01 Ratings
Cross-browser testing
00 Ratings
8.01 Ratings
Mobile app testing
00 Ratings
8.01 Ratings
Test significance
00 Ratings
9.01 Ratings
Visual / WYSIWYG editor
00 Ratings
10.01 Ratings
Advanced code editor
00 Ratings
9.01 Ratings
Page surveys
00 Ratings
8.01 Ratings
Visitor recordings
00 Ratings
8.01 Ratings
Preview mode
00 Ratings
8.01 Ratings
Test duration calculator
00 Ratings
10.01 Ratings
Experiment scheduler
00 Ratings
10.01 Ratings
Experiment workflow and approval
00 Ratings
8.01 Ratings
Dynamic experiment activation
00 Ratings
10.01 Ratings
Client-side tests
00 Ratings
10.01 Ratings
Server-side tests
00 Ratings
10.01 Ratings
Mutually exclusive tests
00 Ratings
10.01 Ratings
Audience Segmentation & Targeting
Comparison of Audience Segmentation & Targeting features of Product A and Product B
Google Analytics
-
Ratings
Google Content Experiments (discontinued)
10.0
1 Ratings
13% above category average
Standard visitor segmentation
00 Ratings
10.01 Ratings
Behavioral visitor segmentation
00 Ratings
10.01 Ratings
Traffic allocation control
00 Ratings
10.01 Ratings
Website personalization
00 Ratings
10.01 Ratings
Results and Analysis
Comparison of Results and Analysis features of Product A and Product B
Google Analytics is particularly well suited for tracking and analyzing customer behavior on a grocery e-commerce platform. It provides a wealth of information about customer behavior, including what products are most popular, what pages are visited the most, and where customers are coming from. This information can help the platform optimize its website for better customer engagement and conversion rates. However, Google Analytics may not be the best tool for more advanced, granular analysis of customer behavior, such as tracking individual customer journeys or understanding customer motivations. In these cases, it may be more appropriate to use additional tools or solutions that provide deeper insights into customer behavior.
Do you already have Google Analytics? If so content experiments is a good, free, starting point to dip your toes in A/B testing. Do you need to run Multivariate experiments? If so, Google Content Experiments is not going to fit your needs.
We will continue to use Google Analytics for several reasons. It is free, which is a huge selling point. It houses all of our ecommerce stores' data, and though it can't account for refunds or fraud orders, gives us and our clients directional, real time information on individual and group store performance.
Content Experiments just makes it is simple and easy to implement A|B tests. We will be evaluating other tools in search of a more robust system for multivariate and cross-page testing, such as Optimizely or Visual Website Optimizer. However, for basic testing, you can't really beat it.
Google Analytics provides a wealth of data, down to minute levels. That is it's greatest detriment: find the right information when you need it can be a cumbersome task. You are able to create shortcuts, however, so it can mitigate some of this problem. Google is continually refining Analytics, so I do not doubt there will be improvements
We all know Google is at top when it comes to availability. We have never faced any such instances where I can suggest otherwise. All you need is a Google account, a device and internet connection to use this super powerful tool for reporting and visualising your site data, traffic, events, etc. that too in real time.
This has been a catalyst for improving our site's traffic handling capabilities. We were able to identify exit% from our sites through it and we used recommendations to handle and implement the same in our sites. We have been increasing the usage of Google Analytics in our sites and never had any performance related issues if we used Analytics
The Google reps respond very quickly. However, sometimes they can overly call you to set up an apportionment. I'm very proficient and sometimes when I talk to reps, they give beginner tutorials and insights that are a waste of time. I wish Google would understand my level of expertise and assign me to a rep (long-term) that doesn't have to walk me through the basics.
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.
love the product and training they provide for businesses of all sizes. The following list of links will help you get started with Google Analytics from setup to understanding what data is being presented by Google Analytics.
I think my biggest take away from the Google Analytics implementation was that there needs to be a clear understanding of what you want to achieve and how you want to achieve it before you start. Originally the analytics were added to track visitors, but as we became more savvy with the product, we began adding more and more functionality, and defining guidelines as we went along. While not detrimental to our success, this lack of an overarching goal resulted in some minor setbacks in implementation and the collection of some messy data that is unusable.
I have not used Adobe Analytics as much, but I know they offer something called customer journey analytics, which we are evaluating now. I have used Semrush, and I find them much better than Google Analytics. I feel a fairly nontechnical person could learn Semrush in about a month. They also offer features like competitive analysis (on content, keywords, traffic, etc.), which is very useful. If you have to choose one among Semrush and Google Analytics, I would say go for Semrush.
Google Website Optimizer was a better product but has been discontinued. We have also used Test and Target , which has more features but we have been doing fine with Google Content Experiments. Most testing situations can be handled with Google Content Experiments.
Google Analytics is currently handling the reporting and tracking of near about 80 sites in our project. And I am not talking about the sites from different projects. They may have way more accounts than that. Never ever felt a performance issue from Google's end while generating or customising reports or tracking custom events or creating custom dimensions