Adobe Analytics Review
Overall Satisfaction with Adobe Analytics
So we are a pretty high volume reference website, so the goals for us are probably a little bit different than somebody who might be e-commerce. Typically people come and rely on us for looking up definitions and synonyms. It's really our bread and butter between the dictionary and the source side. So from a business point of view, obviously that is our mission. We want to be a resource for education and for literacy from a business standpoint. We are largely ad-supported so that's a primary source of revenue. We think about ways to optimize the page to be able to try to get people to spend more time going to different pages. You know, like another big reference site. Wikipedia is famous for getting people going down Wikipedia rabbit holes. So we'd love to be doing the same stuff for etymology and words you know, things to get people to spend a little bit more time on the page.
From an analytics standpoint, we're using Adobe Analytics in a few ways. One is tracking KPIs, tracking revenue, tracking performance. We have certain ads that are getting low viewability and we need to make some tweaks and adjustments on it. We also love to use our Adobe Analytics as just part of general research.
For the content team, it's often the case that there are stories within the data that we find. A really good example of that recently for us was we just had our Word Of The Year towards the end of last year which is always a fun time of year for us. And we chose the word "woman" as the word of the year. And the big reason we did was that we looked at the data and there were a few of these key events where the very definition of the word woman became a pretty major story. You know, a bigger one was Ketanji Brown Jackson, who was confirmed to the Supreme Court. Somebody asked her, "can you define woman?" She, in a legal context, didn't try to provide the exact definition. But when that happened, as a dictionary, searches soared, searches went over by a factor of about 14 what they usually are. We saw it happen a few other times in the year, too. Just related to certain events with trans rights being at the forefront of so many things. That definition of woman has really become this flash point. It did come down to the data for us because the more we looked at it, the more of an obvious pick it was. But we do love when we can do things like that. Oftentimes some really interesting stories surface just in the words that people look up and how those change over time.
From an analytics standpoint, we're using Adobe Analytics in a few ways. One is tracking KPIs, tracking revenue, tracking performance. We have certain ads that are getting low viewability and we need to make some tweaks and adjustments on it. We also love to use our Adobe Analytics as just part of general research.
For the content team, it's often the case that there are stories within the data that we find. A really good example of that recently for us was we just had our Word Of The Year towards the end of last year which is always a fun time of year for us. And we chose the word "woman" as the word of the year. And the big reason we did was that we looked at the data and there were a few of these key events where the very definition of the word woman became a pretty major story. You know, a bigger one was Ketanji Brown Jackson, who was confirmed to the Supreme Court. Somebody asked her, "can you define woman?" She, in a legal context, didn't try to provide the exact definition. But when that happened, as a dictionary, searches soared, searches went over by a factor of about 14 what they usually are. We saw it happen a few other times in the year, too. Just related to certain events with trans rights being at the forefront of so many things. That definition of woman has really become this flash point. It did come down to the data for us because the more we looked at it, the more of an obvious pick it was. But we do love when we can do things like that. Oftentimes some really interesting stories surface just in the words that people look up and how those change over time.
Pros
- 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.
Cons
- 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.
- The whole workspace, the idea that we can set up the workspace in such a way. The reality of it is that not everybody wants to get into that level of detail and get into the weeds. I do feel like Adobe Analytics' workspace is very well suited where I'm really comfortable, helping train some of our folks that have that interest in being able to do their own research to get in and poke around. That definitely makes us happy when the stuff's being used.
- Still pretty early for it, so I'd say it's still taking shape. It does a big one for us as it's just helping us pull back on some pretty complex technical debt that was associated with the Legacy tool. So that's one place I know where we're realizing some gains right out of the gate. I would say our team very regularly finds ideas. We came across this kind of obscure game that was pretty well hidden on our site. We've had it for a long time, like a word puzzle game, and found that it only had like one ad on it, but then we started looking at the data and saying, there's actually a lot of people using this and they're spending a decent amount of time on it. So right away that's low-hanging fruit of "Oh hey, we could be doing a little bit more to promote this game and monetize it."
The IBM tool was that we used, it had some nice things going forward, but they ended up spinning it off to a different company and so it was just one of those things that wasn't really getting the product development. Whereas Adobe Analytics is very obviously continuously driving the product forward. So I do think it's head and shoulders above that tool we were using with Google Analytics. I mean there's a little bit of an apples and oranges nature to them. I certainly prefer using Adobe Analytics as a primary tool. Google, I think even with the 360 product, sometimes you run into some weird things with sampling. I think we're definitely comfortable relying on Adobe Analytics as the primary tool.
Do you think Adobe Analytics delivers good value for the price?
Yes
Are you happy with Adobe Analytics's feature set?
Yes
Did Adobe Analytics live up to sales and marketing promises?
Yes
Did implementation of Adobe Analytics go as expected?
Yes
Would you buy Adobe Analytics again?
Yes
Comments
Please log in to join the conversation