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.
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OpenText Optimost
Score 7.0 out of 10
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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.
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Optimizely Feature Experimentation
Score 8.3 out of 10
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Optimizely Feature Experimentation unites feature flagging, A/B testing, and built-in collaboration—so marketers can release, experiment, and optimize with confidence in one platform.
Google Tag Manager was less flexible for the business and required the Google Analytics tool for analysis and metric tracking. Optimizely allows the building of use cases. Optimizely provides real-time data and metrics that are easier to use. GTM provides tracking …
We have not used any other similar tools, we evaluated both Kameleoon and VWO. With the combination of price, features, and expandability, we moved forward with Optimizely Feature Experimentation.
When Google Optimize goes off we searched for a tool where you can be sure to get a good GA4 implementation and easy to use for IT team and product team.
Optimizely Feature Experimentation seems to have a good balance between pricing and capabilities.
Optimizely FX is the only tool I've used that specifically allows for testing in the back-end. Most front end tools are great for simple tests, but there comes a time when you need to go a level deeper and that's not possible with front-end tools.
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.
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.
Based on my experience with Optimizely Feature Experimentation, I can highlight several scenarios where it excels and a few where it may be less suitable. Well-suited scenarios: - Multi-Channel product launches - Complex A/B testing and feature flag management - Gradual rollout and risk mitigation Less suited scenarios: - Simple A/B tests (their Web Experimentation product is probably better for that) - Non-technical team usage -
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
It is easy to use any of our product owners, marketers, developers can set up experiments and roll them out with some developer support. So the key thing there is this front end UI easy to use and maybe this will come later, but the new features such as Opal and the analytics or database centric engine is something we're interested in as well.
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.
Would be nice to able to switch variants between say an MVT to a 50:50 if one of the variants is not performing very well quickly and effectively so can still use the standardised report
Interface can feel very bare bones/not very many graphs or visuals, which other providers have to make it a bit more engaging
Doesn't show easily what each variant that is live looks like, so can be hard to remember what is actually being shown in each test
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.
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.
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
Easy to navigate the UI. Once you know how to use it, it is very easy to run experiments. And when the experiment is setup, the SDK code variables are generated and available for developers to use immediately so they can quickly build the experiment code
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.
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.
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.
When Google Optimize goes off we searched for a tool where you can be sure to get a good GA4 implementation and easy to use for IT team and product team. Optimizely Feature Experimentation seems to have a good balance between pricing and capabilities. If you are searching for an experimentation tool and personalization all in one... then maybe these comparison change and Optimizely turns to expensive. In the same way... if you want a server side solution. For us, it will be a challenge in the following years
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
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
We have a huge, noteworthy ROI case study of how we did a SaaS onboarding revamp early this year. Our A/B test on a guided setup flow improved activation rates by 20 percent, which translated to over $1.2m in retained ARR.
