Likelihood to Recommend
Where it's particularly well suited, figuring out just the ins and outs of how we drive traffic to certain editorial articles that we're using. That Word Of The Year was a good example of that. We have a team of lexicographers that a few times a year put out collections of new entries. The thing about a dictionary is even in the old days when it was just print dictionaries, the day it goes into print is the day it starts going out of date. It really just has to constantly be updated. So we have a lot of good content that comes from the lexicographers team about which words are getting updates and why that is. We try to put some thought based on influence and how they organize their queue. If they find words that are particularly high volume, that might be a good reason to kind of get that up in the work queue, relative to where something else might be. For example, I know the team got really excited recently. Only the kind of thing a lexicographer can get excited about, but the word "at" can now be a verb because of all the use in Twitter of "Don't at me." So they added a separate entry for "at" to be a verb. That's just one of those words that you never even think about. So they got real jazzed about it. So with using the tool, we love using it to spark ideas and to dig up ideas. It's testing our own performance. For example, we had to make some changes to our crossword last year, so we were keeping a very close eye on session duration and how long people were taking. And that time on duration, Adobe Analytics has it set up in the reporting. You can do it kind of bucketed into groups or you kind of run your straight average, which is helpful because that sort of data, you always have some wonky outliers that can skew it. So I find it really helpful to be able to show that distribution because if you take something like our crossword puzzle and games, that's something where we hope people can come play word games and learn, but obviously there are ads going along the side, too. We want to maximize that time. We use the tool to see if we've made these changes - is time going up or down - and we can adjust based on that.
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It is well suited for situations or professionals that works with figures and data, or were you need to present this kind of information to your stakeholders. It may also be useful for students in the area of economics, accounting, finance or administration, to develop or train themselves in this area, linking the professional career with some IT knowledge.
Read full review Pros Reporting-wise, I think Adobe Analytics workspace analysis is a very powerful tool in terms of reporting. It provides very good insights and this is well integrated with the other Adobe products like Target Audience Manager and the content creation. So it's a good product to use. Read full review No code writing Connection to platforms Connection to warehouse Read full review Cons So the first con is that the experimentation reporting is sort of lacking, right? So it's just the very standard significance calculation, but you don't get to do the same thing for segments. So if you segment it, you will also segment the amount of users that entered that data. So we want to know actually from all of those, okay, what does this segment do? Not just reduce the whole result to that segment. The second one is that it's very complicated to implement custom tracking for each experiment. If you need that, you need to go back to the tag manager convince someone in there to put your tag and approve it and launch it. So customizability is a blessing and a curse. Read full review Having a longer 'data period' in the 'Growth' plan Read full review Likelihood to Renew
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.
Read full review Usability
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.
Read full review Reliability and Availability
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.
Read full review Performance
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
Read full review Support Rating
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.
Read full review In-Person Training
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
Read full review Online Training
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.
Read full review Implementation Rating
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.
Read full review Alternatives Considered
I think Adobe's been around longer as a product but Tealium, from when I did research, it has auto-tagging. So one of my biggest pet peeves is when I'm rolling out new features, and whether it's an app or a website, is that I have to go speak with our metrics team or tagging team and we have to come up with these different strategies. Okay, how are we gonna tag it? What are we going to name it? It just seems like a lot of wasted time in my opinion. I want to track everything. I want to know every single thing these people are doing. We shouldn't have to have this conversation if we tag this, you might not have time to tag this right away for MVP. It's like that to me right now. That shouldn't even be a conversation. I should be able to release a feature, I should be able to just automatically go pull reports on that. And just figure out exactly what they were doing.
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More intuitive and friendly when using it in comparison to
plus the positive experience with their support team when experiencing bags in the system.
Read full review Contract Terms and Pricing Model
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.
Read full review Scalability
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.
Read full review Professional Services
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
Read full review Return on Investment A ton. So when I first started with Adobe Analytics, our analytics team only had one tag per media channel with no additional breakdowns available within the tag. So a lot of the parameters were very redundant saying the same things. We just weren't getting a lot of the support that we needed. So I had to work with each of our channel teams and develop a taxonomy for our tags to tell us our main funding sources, our act, our AC paid channels, and their sub-channel tactics. So we now have a very granular view of marketing in Adobe Analytics that has allowed us to ask for incremental funding. We're hitting global RevPAR targets and we're able to use that data and supplement where there's risk and need elsewhere in the company. So it's been super cool. Read full review Insight of financial figures Read full review ScreenShots