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.
$150,000
per year
Optimizely Feature Experimentation
Score 8.3 out of 10
N/A
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.
Wix and other website platforms have a built-in analytic tool, but it is not as sufficient as Google Analytics, so I always use GA as the main source of information about sales. Most of the analytic tools on web platforms can't visualize user flows, which is very important when …
The entry threshold is lower and Google Analytics can be used to grant access even to technically intermediate users who can draw basic conclusions on their own.
Google Analytics is for me the default one to implement especially for business starting in analytics. The time (aka cost) of implementation is very low and it provides results in a matter of hours. The integration with the Google ecosystem is also a plus especially when …
Microsoft Clarity is speedy, extremely tidy, and straight to the point, and it contains everything a SME would need to maintain a healthy SEO without the need for technical understanding; its UI is far superior to GA, and it also provides additional capabilities like as …
Webtrends as a platform is older than Google Analytics and still quite good. If you have a company that is used to using Webtrends, it's likely still a good fit for you. Google Analytics has a lower entry cost and more accessible training to new Users, so that's why I would …
Adobe Analytics is good but it is more suited to people who are fully and technically into reporting and the solutions it provides. Google Analytics on the other hand provides a much easier way of setting up the Analytics. Most of the data reporting, charts and visualisations …
Ease of use: Google Analytics is known for its user-friendly interface and straightforward setup process, making it accessible for beginners. Adobe Analytics has a steeper learning curve and requires more technical expertise. Features: Adobe Analytics offers a more comprehensive …
Universal GA is free to use, offers a good amount of data, and is relatively easy to use. Other products may not offer the detail needed (Google Tag Manager), or require payment (Adobe Target)
Built-in reports are beneficial but you can create custom reports if you need more details with different dimensions and metrics it also provides insights which is just little data about your site traffic in sentence format its the best way to know which strategy you are on …
Adobe and Google Analytics are fairly similar. Google Analytics was more widely known among my team. Most of us have used it in some capacity in the past. It's also easy to navigate, and there are loads of free training out there on how to use the platform.
Google provides a wide suite of products that all tie into Google Analytics. Some that I use most often are Tag Manager, Ads and Datastudio. All of these connect directly with Analytics and allow me to accomplish my goals. For example, Ads will connect and show me what Ads are …
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 …
Adobe Analytics and Google Analytics 360 are both paid/premium options for website tracking. Though there are certain use cases when these might make sense (you operate entirely in the Adobe suite, you're a massive company/site that doesn’t mind the price tag on Google …
Google Analytics provides everything you need in terms of straight forward analytics needs. The tool is not very flexible compared to other software such as adobe, and if you want to upgrade to premium or add in a bunch of custom situations, that can be become very [tedious] …
Google Analytics is easy to use and widespread, it's a must-have software for all businesses. The price point compared to other software that we use is very reasonable, and the suite of services and training tools/certifications available for free is hard for other software …
Adobe Analytics has been in the market for a long time; some people still know it as Omniture or SiteCatalyst. It seems that some great ideas from Google Analytics, such as Enhanced Ecommerce and the new way of measuring events with GA4, are adapted from the traditional Adobe …
GA will always have an advantage with data, because it's the source, but other companies do a better job of specializing in certain areas or providing better UX/UI. HubSpot is the king of the latter and SEMrush is ideal for making organic improvements based on data. Ahrefs are …
We have been using Adobe Analytics for a while but the system seemed to be more complex when compared to super user friendly Google Analytics. Moreover, the option to add custom metrics and dimensions is lacking in Adobe Analytics. Google Analytics is good with transactional …
Google Analytics is really unique so it's hard to have competitors - especially when Google Analytics is free (unless you are part of a huge company so in the case you will need the Premium version). Other products like SemRush are good as third party tools and figure out the …
I used Facebook Analytics for mobile and web games but Facebook Analytics was discontinued. Google Analytics is more universal and is suitable for both web and native mobile applications. Facebook Analytics is more suitable for apps and games on web and mobile. For mobile …
In previous companies I've used Monetate which is a similar A/B testing kind of feature experimentation engine that is very similar from my memory, but again, back to the point of these new features of the analytics engine and Opal, it kind of cuts it above Monetate from my …
I wasn’t part of the team that selected Optimizely, but its integrations with other tools were a big plus for us in making our decision. It was more expensive, however.
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.
Google optimize is great that it is an add on to an existing Analytics implementation, but only has a web version. Optimizely has the SDK so better option for testing new features
We selected Optimizely as it was easy to use/understand, had clearly defined SLAs for keeping the platform up and was regarded as resilient within the industry. We needed something at our point in our experimentation journey that could be used for Product testing at scale and …
Optimizely Feature Experimentation has similar features to Amplitude. As a matter of fact it looks like Amplitude copied Optimizely. However, Amplitude did not mimic the nomenclature issues.
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.
In other companies, all of the feature flag controls were done locally and it got messy after a while. There was no much control on who was doing what. With Optimizely Feature Experimentation, it is clear what feature flags are enabled and which ones are not. It is easier to …
Optimizely offered both web experimentation (WSYWIG editor for nontechnical marketing folks) and Feature Experimentation. That made the decision easier to get max value across different stakeholder groups.
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.
I prefer Optimizely Feature Experimentation to web experimentation. I think it's more straightforward to set up and as an engineer, I like being able to have more control from the code side.
We haven't evaluated other products. We have an in-house product that is missing a lot of features and is very behind from making the test process easier.
Instead of evolving our in-house product with limited resources, we decided to go with Optimizely Feature Experimentation …
Overall, Optimizely Feature Experimentation is an industry leader in terms of experimentation across web and mobile. For apps I would say amplitude does slightly a better job as it is tailored to that niche.
Optimizely Feature Experimentation is better for building more complex experiments than Optimizely Web. However, Optimizely Web is much easier to kickstart your experimentation program with as the learning curve is much lower, and dedicated developer resources are not always …
Optimizely Feature Experimentation is less of a point solution than LaunchDarkly, so LD has a few extra features, but Optimizely offers a much greater solution for experimentation, personalization etc.
Feature experimentation is much more robust and allows more granular control over the decisions you want to make. While Optimizely Feature Experimentation is nice and can be delivered via Optimizely Feature Experimentation's UI, its still not ideal because its brittle and can …
Honesty, there is no reason that a company wouldn’t want to implement Google Analytics. The regular version is completely free, is very easy to configure, and provides immense volumes of website data. There are also tangible benefits to the other Google tools it can connect to, and it integrates with any BI/data platform that you might use. The only time I’d advise not using standard Google Analytics is if you’ve purchased Google Analytics 360.
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 -
While raw data is nice to have, I do wish there was an easier way to provide reports from Google Analytics directly. Something that could answer questions straight-forward for people.
I would appreciate "helpful hints" or a cheat sheet of some sort, so when quickly searching for something such as time on a certain page, I can find it quickly.
Having used Google Analytics for the last 9 years, I have no intention of discontinuing my service. Google Analytics is a fantastic product that provides me with almost everything I could wish for. The positives in this product outweigh any negatives that you might find. I can not think of a single reason to not immediately start using Google Analytics for your business.
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.
Make sure to put the tracking code on every page. Ideally this would be part of a template or "include" so you can update the code on all pages (or at least within pages of the same category) at once.
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.
In previous companies I've used Monetate which is a similar A/B testing kind of feature experimentation engine that is very similar from my memory, but again, back to the point of these new features of the analytics engine and Opal, it kind of cuts it above Monetate from my experience. Obviously Monetate may have improved since when I lost use it, but from what I can see, yeah.
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
We have improved various metrics throughout the course of our experimentation program with Optimizely and therefore sharing numbers is tricky. Essentially we only implement versions of the product that perform the best in terms of CVR, revenue/visitor, ATV, average order value, average basket size and so forth dependent on the north star we are trying to move with each release.