Adobe Analytics vs. Countly

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.

Incentivized

Countly is wonderful. It mhas affordable options for startups that are experimenting with event and market-tracking services that can't afford more expensive services but do have the cloud credits to operate Countly. For later-stage companies that have the money, but not the time to set up a service like this, a service like Amplitude, Segment, or Mixpanel may be a better alternative.

Incentivized

• eVars (love, wish there was more but I heard they are unlimited in AJA)
• Projects. The transition from Reports to Projects was easier for me to navigate than I thought it was going to be.
• Adobe Templates. Again with the love. Nothing helps me more than copying a template and then deconstructing it to see how it works and reconstruct to how I want it to be.

Incentivized

• It helps in understanding the user journey.
• Customer attributes and persona is also a good feature.
• Analytics & attribution as well real time user data.

Incentivized

• Our site has about 250,000 definitions pages on dictionary.com. We've got about 150,000 synonym pages across the source.com. So very high volume of pages. As you can imagine, most of these are pretty low traffic. You've got maybe that top 5%, 10% are really driving a huge amount of traffic, but then you have all these really obscure things out there. There's still a lot of important information you can get there and oftentimes in our Adobe Analytics reporting suite, it'll kind of bundle things at low traffic at a pretty low threshold for us to get to. So that can be a limitation when we're trying to do some really detailed keyword analysis. The way we've gotten around that is we make use of the data feed and the export. So we make the data available to our analyst in more of that raw state. So when they really do need to truly get into that weeds data, we don't run into that low traffic limitation.

Incentivized

• Bad UI - The UI is quite outdated and poorly designed, which was one of the principal reasons for us moving away from Countly.
• Some poor documentation - 3rd-party documentation and tutorials for some of their mobile SDKs are better than Countly's own documentation.
• Server requirements can be a bit high - For startups with trial credits on cloud computing services, this may not be a problem. Otherwise, Countly can get as expensive as hosted services like Segment and Mixpanel.

Incentivized

• New pricing models are very expensive compared to old pricing model, even though it includes several additional tools, most of which seem to be beneficial
• Horrible support experience despite working with escalation teams to try and resolve
• Several bugs in recent releases which remain unresolved for many months at a time

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.

Incentivized

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.

Incentivized

Overall, Adobe's servers seem responsive. Like any
large-scale SAS provider, they can have occasional slowdowns where, I
presume, a node is not available and other servers get bogged down with
the user load. I have noticed this with both large and small data sets
and reports.

On that note, Adobe Analytics can take a long time to run reports and pull various data points, depending on the period of time, number of metrics and segments applied. As you create reports, particularly in Workspace, the data are pulled in real-time while you're creating the report. This can often cause issues while trying to drag more metrics into the interface when certain elements of a table are grayed out because data is being pulled in.The more data points and segments involved, the longer it takes to update. When you look at larger windows of time, it takes even longer. If one were to compare to Google Analytics or one of the open source products like Piwik or Motomo, Adobe seems much slower. However, Adobe also supports far more variables than other web analytics products.

Incentivized

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.

Countly practically does everything you need it to do. However, it can have challenges of its own sometimes.

Incentivized

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.

It is a large effort to implement. Throwing a developer with zero experience with Adobe Analytics with no support is a REALLY BAD IDEA!!! Having experienced developers working as a team is crucial to a strong implementation. I say this because I have experienced both scenarios. I was the only developer on an implementation project and I had no experience with Adobe Analytics. As a result I made many architecturally bad decisions which lead to a rigid fragile implementation that eventually was scraped. It took some hard lessons to learn that Adobe Analytics was not as simple as their sales reps make it sound. Using the Adobe Dynamic Tag Manager made sequential implementations incredibly STRONG. Having a DTM to manage the code was a miracle and a life saver!!! If you plan on doing a big enterprise level implementation, please seriously consider using the Adobe Dynamic Tag Manager!!! it made code maintenance super slick and easy which is super important for a developer!!!

Historically I've looked at a lot of different products. More recently I'd say Mamo and Google Analytics. Those are probably the two big ones that I've seen around, so yeah. It's more feature rich. It provides more dimensions, more breakdowns, and it also scales data better

Incentivized

Well, Countly is open-source. It got a very helpful community in its back that will surely help you on your projects. Countly is known for its mobile analytics and marketing platform for businesses. It excels at mobile data analysis and working directly with customers to boost engagement. Its main job in "user retention" is to assist you to comprehend custom activity in any component of your app and communicating that data to the server. Its user-friendly and well-designed app features improve consumer happiness. Unique features like in-app activity tracking and analysis can increase in-app usability and user experience, resulting in higher retention and income.

Incentivized

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.

Incentivized

• 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.

Incentivized

• Allowed me to understand my customer on a deeper level
• Allowed me to tweak my content and sales pages
• Allowed me to better understand my target market.

Incentivized