Google Content Experiments (discontinued) vs. OpenText Optimost

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
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
OpenText Optimost
Score 7.0 out of 10
N/A
OpenText Optimost is designed to help companies deliver engaging, profitable websites and campaigns and includes self-service capabilities. Optimost also provides white glove consulting to help companies test confidently when the stakes and complexity are highest; immediately when speed is of the essence, and to match the perfect content to every customer.N/A
Pricing
Google Content Experiments (discontinued)OpenText Optimost
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Google Content Experiments (discontinued)OpenText Optimost
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Google Content Experiments (discontinued)OpenText Optimost
Features
Google Content Experiments (discontinued)OpenText Optimost
Testing and Experimentation
Comparison of Testing and Experimentation features of Product A and Product B
Google Content Experiments (discontinued)
9.2
Ratings
11% above category average
OpenText Optimost
-
Ratings
a/b experiment testing9.00 Ratings00 Ratings
Split URL testing10.00 Ratings00 Ratings
Multivariate testing10.00 Ratings00 Ratings
Multi-page/funnel testing9.00 Ratings00 Ratings
Cross-browser testing8.00 Ratings00 Ratings
Mobile app testing8.00 Ratings00 Ratings
Test significance9.00 Ratings00 Ratings
Visual / WYSIWYG editor10.00 Ratings00 Ratings
Advanced code editor9.00 Ratings00 Ratings
Page surveys8.00 Ratings00 Ratings
Visitor recordings8.00 Ratings00 Ratings
Preview mode8.00 Ratings00 Ratings
Test duration calculator10.00 Ratings00 Ratings
Experiment scheduler10.00 Ratings00 Ratings
Experiment workflow and approval8.00 Ratings00 Ratings
Dynamic experiment activation10.00 Ratings00 Ratings
Client-side tests10.00 Ratings00 Ratings
Server-side tests10.00 Ratings00 Ratings
Mutually exclusive tests10.00 Ratings00 Ratings
Audience Segmentation & Targeting
Comparison of Audience Segmentation & Targeting features of Product A and Product B
Google Content Experiments (discontinued)
10.0
Ratings
16% above category average
OpenText Optimost
-
Ratings
Standard visitor segmentation10.00 Ratings00 Ratings
Behavioral visitor segmentation10.00 Ratings00 Ratings
Traffic allocation control10.00 Ratings00 Ratings
Website personalization10.00 Ratings00 Ratings
Results and Analysis
Comparison of Results and Analysis features of Product A and Product B
Google Content Experiments (discontinued)
9.9
Ratings
16% above category average
OpenText Optimost
-
Ratings
Click analytics10.00 Ratings00 Ratings
Form fill analysis10.00 Ratings00 Ratings
Conversion tracking10.00 Ratings00 Ratings
Goal tracking10.00 Ratings00 Ratings
Test reporting9.00 Ratings00 Ratings
Results segmentation10.00 Ratings00 Ratings
CSV export10.00 Ratings00 Ratings
Experiments results dashboard10.00 Ratings00 Ratings
User Ratings
Google Content Experiments (discontinued)OpenText Optimost
Likelihood to Recommend
9.0
(0 ratings)
10.0
(0 ratings)
Likelihood to Renew
7.5
(0 ratings)
10.0
(0 ratings)
Support Rating
8.0
(0 ratings)
-
(0 ratings)
User Testimonials
Google Content Experiments (discontinued)OpenText Optimost
Likelihood to Recommend
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.
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The ease of implementation combined with the managed services result in a tool that virtually anyone can use - implementation is less than 10 lines of code added to the relevant pages of the website (we simply added it to our master page template to have it available on any page) and from there the customer can be as involved or not involved as they wish. At BSI we are very hands on with the testing programme - usually developing and designing the tests ourselves and having HP build them, but if we wanted to HP to develop, design and build and limit our role to QA and review that is an option.
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Pros
  • When you need to measure against event-based goals
  • If you need to see how the test variations performed against secondary goals
  • Given that the the platform requires you actually code a new page with a unique URL, this tool can be good for radical redesigns.
  • Great insights into other information about your testing groups, like whether or not they're mobile, screen size, browser, or really any dimension available in GA.
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  • Because it is a managed service the need for intervention by our internal IT group was removed. This allowed us to control the pace of the testing programme without being influenced by IT resource allocation
  • The client and technical account managers are very good at suggesting tests or potential improvements
  • HP regularly holds custom forums which are always informative and provide an opportunity to learn from and network with peers and industry leaders
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Cons
  • You can only optimise for one goal, so if you have several conversions, like phone call and email you need to do it manually.
  • It seems not to work that well for pages with lower amounts of traffic - not great for new or niche sites.
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  • The dashboard interface is difficult to navigate, but I understand that they are currently developing/testing a new much more user friendly interface
  • The cost can be a barrier for some organisations, but for us it is worth it. Also they are in the process of releasing a less expensive self authoring testing tool.
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Likelihood to Renew
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.
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We have not only renewed our subscription three years running, but we have added the self authoring tool and are looking to expand the subscription so that we can take advantage of the managed services on a global level.
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Support Rating
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.
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Alternatives Considered
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.
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We evaluated Optimost again Adobe's similar offering (Target). The big difference between the two and the reason why BSI choose Autonomy was the managed service aspect. The idea that once the code was deployed on the site IT no longer had to be involved gave my team full ownership of the testing programme. With the Adobe product, the involvement of the internal IT group would have been required to launch each test - and this would have decreased the number of tests we could run each month. Back in the day I also used offermatica/omniture and this too required IT involvement.
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Return on Investment
  • 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.
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  • Use HP Optimost was the primary driver behind a 40% increase in UK classroom training courses booked online read more details here: http://www.autonomy.com/work/news/details/hsx6767d
  • HP Optimost testing led to a 9% increase in sales by improving the BSI Shop's checkout funnel in 2012
  • HP Optimost is integral to the success of BSI's continuous improvement testing programme
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ScreenShots