March 01, 2014

Review: "AppNexus is the tool that you're missing"

Verified User

Analyst in Marketing

Publishing Company, 10,001+ employees

Score 8 out of 10

Vetted Review

Verified User

Use Cases and Deployment Scope

AppNexus was used by my department for data aggregation. We dealt in Journals and it was of utmost importance to make sure that we kept everything clear and organized across the different journal subsets and AppNexus made that easy with it's many inventory options.

Pros and Cons

Inventory - Clear ways to define journals, dating methods and unique identifiers
Data is curated to make everything as useful as possible - you can see what makes people click and what doesn't
You can easily match IDs to see which pages were browsed, which were clicked and to figure out which ads the user has or has not seen

Data is only stored for a year, I'd like to see longer result storage
Sometimes it get confusing to find things based on the website organization

Return on Investment

ROI over all has improved because we do have quicker leads and can tell user interest.
Analysts spend less time looking at the data because it's displayed in a clear and concise manner.
I personally like that it can work with Google's Doubleclick to make it double trouble in tracking ads and exchanges.

Alternatives Considered

Appnexus is the only one that i have used but I don't see why I would use anything else. It fits all of my needs, has extra things that I never got a chance to use and I look forward to learning and playing more with the data tools. I also like knowing that our user data is safe and never matched to identifiable information.

Likelihood to Renew

I love almost everything about AppNexus because I feel like the user data is easy to track because of the identifiers, you can see which adverts got clicked and which were ignored. We can track the location of the ad on the page fold and this makes it so much easier for future campaigns. The only thing I don't like is that the data is only kept for a year, and I'd like it for a longer period of time.

Likelihood to Recommend

This is incredibly well suited to targeting audiences for scientific journals and making sure that users don't see repeat ads. We don't want to overload someone with the same thing and like to keep it all fresh and interesting while keeping our data relevant to ad exchanges and user click patterns.