Category: Analytics

One of the really innovative things that the team has been working on, and that we showed at the in.Telligent conference, is something we’re calling Social Fingerprints. This is included in Harvest 2.0 which we’ll release in the next few weeks.

The concept is that each person in a community has their own unique contribution style or fingerprint that they they leave on a community. While finger prints from a variety of individuals may be similar they will almost always be unique. For example, here is mine:

I tend to skew heavily towards “Asker” meaning that I ask lots of questions or start lots of discussions.

Now compare this to Joe who is the program manager for Evolution who tends to skew more towards the contributor/answers side:

The fingerprint is built around how the user contributes in the community and their profile changes over time.

We think this is a pretty interesting way to think about how to categorize and classify groups of people too. Depending upon the type of community you are creating you would expect to have a fingerprint for the overall community type too. That is, a support community should look different than an enthusiast community. We’ll eventually tie this data into predictive profiling of users – so you know what types of users turn into high contributors, etc.

While this is only version 1.0 of our work in this area we’re going to be investing a lot of time and energy into helping customers use this kind of information to improve and measure.

The latest version of our business intelligence tool, Harvest, is nearing completion. One of the new included reports is the User Technographics report popularized by Groudswell:

The User Technographics report breaks down the user base into 7 categories: creators, joiners, collectors, inactives, critics, spectators, and overseers [1]. Jeremiah has some posts that details what all of these categories are.

This report breaks-down trending of users over time. We’ve also added in another graph so you can see the actual trend lines – it still needs a few tweaks:

We’re creating these types of reports to make sure we’re aligning with what customers are reading – such as Groundswell – about how to measure their communities. Of course there is still more to come 🙂

[1] Overseers are the administrators and moderators that help manage the community.

Jeremiah Owyang, a senior analyst for Forrester Research, says that some of the feedback he hearing from customers of the Wave report he is working on that

“…wasn’t surprised to hear from a few brands that not everyone is a fan of Software as a Service (Saas), in fact, for some, on-premise software makes a whole lot more sense.”

You can read his blog post about this here as well as follow the stream of comments.

There are some really valid point brought up – however, one that I think may be missing is a serious discussion around all the data that is created within a community solution. I reading an article in the Harvard Business Review on my flight today and there was a great article about “Putting Data to Work in the Marketplace”. The topic of data came up in some of the comments on Jeremiah’s blog post and one of the questions is: in an SaaS environment, who owns the data?

I imagine that in the coming years as we see the Enterprise 2.0 market continue to mature this is a question that will come up more often – more so as businesses start to think more strategically about their investments in Enterprise 2.0 solutions.

Jeremiah Owyang, a senior analyst for Forrester Research, says that some of the feedback he hearing from customers of the Wave report he is working on that

“…wasn’t surprised to hear from a few brands that not everyone is a fan of Software as a Service (Saas), in fact, for some, on-premise software makes a whole lot more sense.”

You can read his blog post about this here as well as follow the stream of comments.

There are some really valid point brought up – however, one that I think may be missing is a serious discussion around all the data that is created within a community solution. I reading an article in the Harvard Business Review on my flight today and there was a great article about “Putting Data to Work in the Marketplace”. The topic of data came up in some of the comments on Jeremiah’s blog post and one of the questions is: in an SaaS environment, who owns the data?

I imagine that in the coming years as we see the Enterprise 2.0 market continue to mature this is a question that will come up more often – more so as businesses start to think more strategically about their investments in Enterprise 2.0 solutions.

As I’ve mentioned previously, we’ve made some significant investments in our business intelligent tool, Harvest over the past 6 months since releasing Harvest 1.0.

One of the more exciting investments we’ve made is around sentiment. Sentiment provides the ability to rank content based on people’s attitudes. As this relates back to our customers it helps them understand whether people view their products/services negatively or positively.

Working with some experts in the field we’ve integrated sentiment into the Harvest business intelligence engine. Sentiment analysis can be done on user selected keywords or phrases as well as self-selected keywords that the engine sees.

Below is one of the reports that Harvest uses to show sentiment:

In this example for a period of time from July to September we can visualize the attitudes people have in the community. Further more, you can drill into the specific positive and negative discussions.

As you can also see, in the upper-right we’re making it easy to also embed any Harvest report as a widget, image, or simply sharing the data through RSS.

We’ll also have some dedicated session’s at this year’s in.telligent Conference. Just click the banner below for more details.

As I’ve mentioned previously, we’ve made some significant investments in our business intelligent tool, Harvest over the past 6 months since releasing Harvest 1.0.

One of the more exciting investments we’ve made is around sentiment. Sentiment provides the ability to rank content based on people’s attitudes. As this relates back to our customers it helps them understand whether people view their products/services negatively or positively.

Working with some experts in the field we’ve integrated sentiment into the Harvest business intelligence engine. Sentiment analysis can be done on user selected keywords or phrases as well as self-selected keywords that the engine sees.

Below is one of the reports that Harvest uses to show sentiment:

In this example for a period of time from July to September we can visualize the attitudes people have in the community. Further more, you can drill into the specific positive and negative discussions.

As you can also see, in the upper-right we’re making it easy to also embed any Harvest report as a widget, image, or simply sharing the data through RSS.

We’ll also have some dedicated session’s at this year’s in.telligent Conference. Just click the banner below for more details.