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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KickFire
Score 9.0 out of 10
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KickFire’sB2B solutions provide account-level information such as industry, revenue, employee count, and more based on an IP address. KickFire’s proprietary TWIN Caching® technology and robust firmographic database deliver business intelligence for first-party intent, content personalization, account-based marketing, predictive/intent, data enrichment, and much more. KickFire offers IP address intelligence and B2B firmographic data through its LIVE Leads platform, API, and integrations…
Adobe Analytics is better than some other tools as it feels better set up for actual "analysis", rather than simply "reporting". The power of Workspace allows you to drag 'n' drop at ease which makes you are far more in control of your own analysis/discovery/exploration. However, regards the final reports and dashboards' look 'n' feel the Workspace PDF output is lacking visually compared to other products like Google's Looker. To engage with less technical end users sometimes Looker feels the better, more polished option.
For small businesses that don't have big budgets for marketing automation, VisiStat is an ideal first step. For companies that have sophisticated systems in place, VisiStat will augment your analytics and provide a deeper dive into your website activity. Since the implementation involves adding javascript to your site, the user should be familiar with how to do this
They've been really an industry standard tool in analytics for a long, long time. They've got the trusted brand and the reputation, a wonderful community behind it. It is always nice, having that level of support where you can meet other practitioners. It's a great benefit because I can meet other people who have already pushed the tool a lot farther than I have. And it's a great place to get ideas in that way. We came from a world where we were running on a homegrown system that we'd use to do click tracking. You get some advantages on that of the customization, but losing out on community of support was one of the big reasons why we decided to move beyond that and implement Adobe Analytics instead.
De-anonymizes website activity at the account (company) level.
Identifies net new target accounts.
Displays click path, time on page, time per session, and engagement level of each de-anonymized website visit.
Gives great daily insight on watchlists you've set up.
Delivers every possible de-anonymized visit with little filtering for accuracy.
More on the watchlists. I really love that you can receive immediate alerts on website visits from accounts you've listed on your watchlists. This way, you never miss the window of opportunity to reach out to your key targets while they are currently on your site.
Salesforce integration is good. KickFire pushes most recent website visits, pages visited, website click path, activity percent change, and more to the given account in Salesforce. You can then create reports and run them regularly to see which accounts are surging in website activity. This is also great for account prospecting, and for planning your sales outreach plan of attack. You can see which bits of your website content are most interesting to the company, and which products they are most interested in.
Most of the problems that Adobe Analytics as of now is having, it is getting addressed in a newer tool called Web Desk DK from implementation. They are already addressing that issue with the new tool and also the time data with the customer general analytics. So there is something not in workspace analysis and this is what they're addressing in customer general analytics. Which is good.
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.
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.
They are very good at solving cases that I bring to them. I'd like to see more proactive support to make sure we are getting the full value out of the solution.
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.
The tutorials are very good and they explain how to get started using the system. The online webinars are very good for advancing your knowledge of the product.
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.
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.
I covered this pretty extensively in the cons. The key differentiator here is that KickFire serves up almost all the data (or so it seems) to the end client. The client then has to do their own work on interpreting it. This is good because it means we don't miss out on any website activities, but it's bad because we get a lot of false positives. 6sense uses the confidence score approach I mentioned in the Cons section, which means the match rates of the data we get are much higher. Our experience with Clearbit comes from other tools that are built on it (Bombora, Drift, etc.), and it has not been great. We've seen many more inaccuracies with Clearbit.
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
I like to think it's positive. It's a very steep learning curve, so we do face a lot of challenges with adoption inside of the companies. My team and I evangelize this and also who's in charge of data and advanced analytics, but it's very hard to leverage that with typical business analysis people. These are people who live their life in Excel and SQL and Power BI. They just use this very occasionally and by only looking at that sort of aggregate data, they miss out on behavior and what actually happens in execution. And because it's such a steep learning curve, we do have a challenge pushing it in there.
