I had a nice chat today with Mark Searle, Co-Founder & CEO of Log Savvy, somewhat of a pioneer in the field of analytics for Social Networks and Online Communities. The Berkley California based company released its Enterprise Vision Engine Version 1.0 in April 2007 providing community developers, marketers and analysts with detailed visibility into the behavior of their respective communities. The company was selected by AlwaysOn as an AO100 Top Private Company Award Winner and was named a Red Herring 100 Winner last year so naturally, I wanted to know more...
With the explosion of social networking and the volumes of data generated through Web 2.0 enabled platforms, tracking user behaviors has become a challenge. Using buzz meters like Andiamo and conventional log files analytics may capture vital information like number of unique users, rate of growth and keyword popularity but the new paradigm calls for different measures.
Communities are built upon a number of activities that require external data sources. Video sharing, blogging, micropublishing, multi-player online gaming and wikis are only a handful of contributors to the ever-increasing amount of activity data that has sprung out of social networking. As a result community datacenters are archiving massive amounts of customer transactions, profiles, calls, page views, content downloads and emails. Due to the sheer volume and complexity of the data however, it is rarely mined.
When I asked Mark about the core value proposition of Log Savvy’s solution he quickly responded “If you have a community, you need to know which members are influencers and why. Ultimately, they are the drivers of community growth and revenue”. He went on to describe the value in understanding the difference between the user that is driving interest, discussion and leadership in music vs. the individual who is clearly a genius at online role playing games. Following vertical leader behavior can eventually give great insight into how purchasing influence flows through social networks
While influencer behavior is undeniably a killer app, content plays a major role in this type of analysis. The tool identifies the most addictive user generated content, provides a visual depiction of how buzz flows to the mainstream, measures most engaging content, and tracks viral activity. The tool also allows you to learn what behaviors drive the most content, participation, and traffic.
To date, most community owners are completely unaware of how their users are behaving. Mark alluded to the current measurement of “Macro” behaviors. This is the ability to track revenue in an e-commerce environment or any other transactional activity that has a defined closed path. It’s the micro activity however, that tells the more accurate story. Understanding micro transactions has been the challenge for the discipline of behavioral targeting for some time now.
In the main, behavioral targeting has been struggling to gain insight on micro activities (this user visited a gardening site 2 times this week and therefore must want tulip bulbs) to paint a consumer mindset picture. While there has been some advancement in self-learning behavioral tracking solutions for web sites (especially e-commerce enabled), the challenge has been to obtain critical mass of information from which to extrapolate reliable data. The solutions have also been focused on analyzing fairly short paths to desired transactions. Having a laser focus on the multiple layers of a community and empowering the community to harness this understanding is something unique to Log Savvy.
Log Savvy’s solution is a log analytics engine, which is designed for efficient execution of log-data processing and analysis. The true breakthrough here is that the solution understands, anticipates, and adjusts to log data changes and is able to correlate with non-log data sources such as customer profile or friend-connection databases.
Log Savvy is focusing on Digital Media, Blogs and Forums, Social Networks and Gaming as their four core verticals. The product is currently attracting the attention of mid-level community builders. The bigger social networks are working on proprietary solutions to capture the kind of detail that Mark’s team has been focusing on. Time will tell whether they might find a short cut through acquisition?
In the meantime, Log Savvy is well positioned to aggregate an enormous amount of intelligence on social networking behavior across a number of verticals. I’m looking forward to watching the company in 2008.