Radian6 review
May 06, 2014

Radian6 review

Anonymous | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source

Software Version

Radian6 (legacy)

Overall Satisfaction with Radian6

We use Radian6 for a social media monitoring engine. It is primarily used within our department, though in addition to cross department projects, we will get one off requests. Our department is the only in the company that does have direct access to the tool. Because we are the insights group (research), Radian6, along with other monitoring agents, serve as the base for our report. We use third party aggregators, like Radian6, to capture the universe of conversation pertaining to a set of keywords and then analyze and report on the data.
  • I think Radian6 have one of the best data crawls out of the Social Monitoring tools that I have used. The tool consistently returns the largest volume numbers.
  • Radian6 is great at getting a read on what is being said about your brand and most importantly, doing so quickly. It only takes a minute or two to set up a keyword group and the pull can run in a matter of seconds.
  • The tool's AI behind the data crawl is smart. When searching for certain keywords like Pepsi, social mentions that include Pepsi in a hashtag are also pulled back. So not only posts including #Pepsi, but also #ILovePepsi would be pulled back as well.
  • The export or raw data can be tedious. Currently, the tool exports a 10,000 mention bulk CSV file. When dealing with larger brands like Nike, you are looking at well over 300K posts for a year. Parallel to this, is the lack of an exportable sample of data.
  • Each widget can only showcase 3 months worth of data. So creating a trend line of volume of mentions must be done in 3 separate widgets and requires the user to manually piece them together.
  • Though the tool consistently brings back the most volume, the data is not always clean. Within the data crawl, twitter user names are also scraped for your kewords, so going back to the above example, if your keyword is nike, and someone's twitter handle is @IhateNike, the post is often irrelevant to the brand.
  • Though I find the tool quite easy to use, new users often tell me that the tool is incredibly confusing and not an intuitive process.
  • Lack of Facebook posts, though this is a limitation of all social monitoring tools given the privacy settings of the social network
  • Lacking the ability to input Boolean Syntax limits the depth of the keyword queries.
  • Overall it has had a positive impact on our process. This is less about specific numbers and more so about Radian being a primary tool for our Social Media Monitoring objectives.
Personally, Radian6 is the lesser of evils. Every social monitoring engine seems to have it's weaknesses. Constantly being in the nuts and bolts of the data, as a team we are able to dissect the tool and focus on what the tool does well. IMO, the tool has the least number of negatives. Often times though the lack of a random sample will drive me to use other tools given the time suck, but for the most part, Radian6 remains my go to.
Radian6 in my opinion is a very no-nonsense type of tool. I know what I am going to get. So in a sense of where it is best suited, I feel as though it is best suited for clients that need a basic read on volume for their brand as well as spikes in conversation over the last 3 months. Radian lacks an automated analysis that is usable. As with other tools, automated sentiment tends to be crap. When comparing to Sysomos, I tend to lead on Radian more because I see them as similar tools though Radian gives me more information. Sysomos has an influencer/'authoritative' portion that the basic Radian tool seems to lack, however, from prior vendor conversations (Im not sure if they have changed it since), Sysomos' was primarily based on twitter followers.

Using Radian6

Consistency is the main reason we will renew our contracts with Radian. Reporting data from one tool and comparing it to another is not an apples to apples comparison and often you run the risk of pin pointing errant details that are a product of the pull rather than the meat of the conversations.