harvest

CMS Wire reviews Telligent Social Media reporting and platforms

By Marc Smith

Telligent Logo

There is some very positive coverage of Telligent recently in the press.  First there is the very detailed review of the community platform and its reporting features from Barb Mosher at CMS Wire: “Social Web Analytics with Telligent’s Harvest Reporting Server“.  The article does a great job of detailing the features of the Harvest social media analysis product.  The article’s explanation of what social media analytics are is itself useful:

“You need to measure what’s happening in your community. If you are interested in knowing what your community members are up to, what information they are sharing and looking at, what they are saying about you, your product or your service (positive and negative), then you need social analytics.

If you need to know how many users are signing up, how many are contributing to blogs, wikis, forums, how many are asking and answering questions, then you need social analytics.

With social computing becoming much more mainstream and in many cases, a requirement for both external and internal relationship building, it has become critical to measure the impact these solutions really have. You also need to know how and where to improve these solutions.

And you aren’t going to get this information from traditional web traffic analytics.”

A mention of Telligent in the New York Times is also cause for note: the recent article on help communities listed Telligent as a provider of platforms, along with Jive, Lithium, and HelpShare, that enable companies to host communities of passionate users who help one another solve problems with their products.  There is a great quote from Natalie Petouhoff, Forrester Research analyst:

Natalie L. Petouhoff, an analyst at Forrester Research, said that online user groups conform to what she calls the 1-9-90 rule. About 1 percent of those in the community, she explained, are super-users who supply most of the best answers and commentary. An additional 9 percent are “responders” who mainly reply and rate Web posts, she said, and the other 90 percent are “readers” who primarily peruse and search the Web site for useful information.

“The 90 percent will come,” Ms. Petouhoff said, “if you have the 1 percent.”

I would extend this point and add: within the 1% of active users are all the different types of active contribution, both good and bad.  Top answer people, discussion starters, discussion people, question people, and flame warriors all crowd into this sliver of the online demographic.  It is important to have the tools to separate the different kinds of active contributions to be sure that an active community is also a properly productive one!

Conference: Web 2.0 in San Francisco – “Beyond Buzz: On Measuring a Conversation” with Kate Niederhoffer

By Marc Smith

2009 Web 2.0 San Francisco Logo

I will be speaking with Kate Niederhoffer from Dachis at Web 2.0 Expo Wednesday, April 1st at 10.50 in San Francisco.  We will be speaking about:

Beyond Buzz: On Measuring a Conversation
http://www.web2expo.com/webexsf2009/public/schedule/detail/6273

What is the most meaningful way to understand and measure a dialogue? As marketing transforms from a broadcast model to a conversational one, which constructs should be captured and how do you measure them? Is it necessary to make a distinction between the metrics used to tap into the value of a conversation per se and the ROI of a social media marketing campaign?

The proposed presentation offers new strategies to think about and tap into the depth of interactions and emotional connections people have online. Beyond buzz levels, sentiment, and other core metrics typically provided by brand monitoring solutions, the presentation will offer methods to understand a conversation: how emotional is it, how in synch are the constituents, how intimately do they relate to the brand or product? How much trust do the constituents reveal?

Marketing efforts that take advantage of technology to enable community and collaboration render traditional metrics limiting, at best. Traditional metrics have been optimized for more passive exposure to a specific message, frequency of exposure is considered a proxy for relevance; and, the premium is on reach over quality.

Primarily due to its more participative dynamic, a conversation engages constituents unlike static messaging. As many in the industry have noted, a natural development is to measure engagement. However, there is little consensus on what engagement means and how it can be measured. Often it is calculated by merely adding traditional metrics, assuming more is better.

The presentation will introduce new constructs and present case studies with empirical research demonstrating more valuable, still measurable constructs than the core metrics currently in use.