Adobe acquired Omniture in 2009 and re-branded the platform as SiteCatalyst. It is now part of Adobe Marketing Cloud along with other products such as social marketing, test and targeting, and tag management.
SiteCatalyst is one of the leading vendors in the web analytics category and is particularly strong in combining web analytics with other digital marketing capabilities like audience management and data management.
Adobe Analytics also includes predictive marketing capabilities that help…
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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.
Maybe for a small company with small products for their thing, Adobe may be bit of an implementation too much for them, but when it comes to companies like us, like a life sciences or large enterprises and even small enterprises, but with more products, more analysis that they need to make their marketing experience better, maybe Adobe product is the best suitable.
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 -
It summarizes large complex data better than any other analytics solution I've dealt with without the need for sampling, gives the right level of detail, does the right level of breakdowns, aggregation. I consistently not only use Adobe Analytics, but I use other data sets and compare against Adobe Analytics. And as I go into Adobe Analytics and compare, as long as I've done the query right and the other systems, they're very, very close. And if anything, with a lot of Adobe's newer products, they've gotten more accurate over time. So that's basically, you asked me what I liked about it. I like that it's accurate. I like that I don't have to do a lot of explaining. There's enough explaining in the world of web analytics to have to go back and explain why data's problematic. And so like I said, provided that the implementation is correct, it's a very easy conversation. Even if people may not like the answer.
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.
Support. I mentioned this earlier and we don't know what we don't know. Researching the massive amounts of documentation isn't realistic with bandwidth constraints, and our rep getting frustrated with us when we go through what we are seeing is disappointing.
Education. More please, and designed more towards the "business side". I get with the many many many different implementations (every company is different!), that it's tough, but even a basic of the basics would be nice for situations that everyone is looking at, like the engagement with the merchandising on the home page (or any certain page).
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've found multiple uses for Adobe Analytics in our organization. Each department analyzes the data they need and creates actionables based off of that data. For E-Commerce, we're constantly using data to analyze user engagement, website performance and evaluate ROI.
Sometimes the processing times are very long. I have had reports or dashboards time out multiple times during presentations. It could be improved. It is understandable since there is a huge data set that the tool is processing before showing anything, however for a company that large they should invest in optimizing processing times.
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
I do not ever recall a time when Adobe Analytics was unavailable to me to use in the 8 or so years I have been an end user of the product. My most-used day-to-day analytics tool Parse.ly however, generally has a multiple hours planned offline maintenance every two to four weeks, and sometimes has issues collecting realtime analytics that last anywhere between 15 minutes to an hour, and happen anywhere between 1 to 5 times a month.
Again, no issues here. Performance within the day updates hourly. other reports are updated overnight and available to access by the next morning. Pages load quickly, the site navigates easily and the UX is quite straightforward to get command over. On this front, I give Adobe kudos for building a great experience to work within
I barely see any communication from Adobe Analytics. The content on the web is also not that great or easy to read. I would recommend a better communication about the product and the new addons information to come to its user by a better mean.
It was a one-day training several years ago that cost the organization several thousand dollars. There were only about 10 people in the training class. Adobe tried to cram so much information into that one-day class that none of our users felt like they really learned anything helpful from the experience. Follow-up training is too expensive
The online training for Adobe SiteCatalyst consists of short product videos. These are ok, but only go so far. For a while Adobe charged a fee for this, but recently made these available for free. There are many great blog posts that help users learn how to apply the product as well.
One of the benefits and obstacles to successfully using Adobe Analytics is a great / more accurate implementation, make sure your analytics group is intimate with the details of the implementation and that the requirements are driven by the business.
Google Analytics comes across more of a reporting tool whereas Adobe Analytics is more of an Enterprise level analytics tool. Contentsquare provides some traffic and flow capabilities but not to the same level as Adobe Analytics. However, Contentsquare's major advantage is its Zoning (Heatmapping), Impact Quantification and Find 'n' Fix modules; none of which are knowingly available in Adobe Analytics.
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
Adobe Analytics is relatively affordable compared to other tools, given it provides a range of flexible variables to use that I have not found in any other tools so far. It is worth investing in if your company is medium or large-sized and brings a steady flow of revenue. For small companies, it can be overpriced.
My organization uses Adobe Analytics across a multitude of brand portfolios. Each brand has multiple websites, mobile apps and some even have connected TV apps/channels on Roku and similar devices. Adobe can handle the multitude of properties that have simple, small(ish) websites and the larger brand properties that include web, mobile and connected TVs/OTT devices.
Each of those larger brands has multiple categories and channels to keep track of. We can see the data by channel/device or aggregate all the data together. This gives our executive teams the full picture and the departmental teams the view they need to see their own performance.
The professional services team is one of the best teams for complex adobe analytics implementations, especially for clients having multiple website and mobile applications. However, the cost of professional services is a bit high which makes few clients opt out of it, but for large scale implementations they are very helpful
Adobe Analytics impacts nearly every aspect of a billion plus dollar revenue eCommerce business. From measuring the impact of new build features to marketing campaigns.
We are saving substantial money and resource effort by consolidating all of our properties to Adobe Analytics from alternative solutions, at which point we will finally be able to report on Total Digital, rather than disparate reports.
We support experimentation on every platform and the performance is only known through Adobe Analytics tagging.
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.
