Social ROI: Intuition, Metrics, and Social Network Analysis
- Meghan M. Biro
- On April 12, 2010
by Meghan M. Biro
April 12, 2010
Today’s post is by our guest blogger, and friend, Jeff Wilfong. Jeff has assisted with web 2.0 and business strategy for a number of large-scale organizations like Conoco-Phillips, the City of Sacramento and a multinational conglomerate based in India. Jeff is currently earning his PhD in Organization Development with emphasis in Web 2.0 management. Learn more by visiting his site, E2.0 Pros.
I have been pondering lately about how we can measure, quantify, or understand whether we are getting value from a social technology. If we are going to move organizations into networked structures with all the latest and greatest tools (such as Web 2.0, E2.0, SCRM, and much more), then we better know what we are heading into. In my view, business ROI metrics that arise from a linear, cash-oriented productivity model are going to increasingly fade away as the analysis becomes much more sophisticated. Too many business analysts state that ROI is just too hard to measure and often horribly inaccurate.
So, how is ROI currently being measured in the new networked model?
One stream of thought is that you intuitively know when you find value. For instance, when I start meeting many different individuals on Twitter and find their thoughts interesting and creative, I then link up with them on LinkedIn and perhaps schedule an hour-long phone call to get the human-to-human connection going. That tells me that the technology was valuable. By the way, I have had numerous of these happening lately as I have developed my weak-link network. The weak-link network theory, aka “Brokerage and Closure” (see Ronald S. Burt’s book), states that social capital exists in structural holes. People become brokers between the links to get access to new knowledge and spread ideas. However, too much closure creates too much similarity in thinking (aka “group think”).
Another stream of thought about Social ROI is more quantitative: it states that we need to analyze metrics, the mathematical properties of the social networks, and user behavior.
Regarding metrics, we examine:
- the time spent on the site,
- the the click rate (which links are clicked on and which are not,
- the quality of postings on a subjective scale (perhaps through user voting),
- the length of postings, and
- the various words used (i.e., tags).
We analyze the social network itself by looking at:
- the number of connections,
- the density of connections,
- the number of weak links and the number of cliques (or strongly connected groupings),
- and the dispersion, the average length of paths, the hubs or connectors, and the outliers (to name a few).
With respect to user behavior, we look at which social tools are used most and examine the long-tail effect of user participation, the fact that a majority of behavior comes from a small few. Typically, this ratio is 20/80 where 80% of the behavior is accomplished by 20% of the population, and this exponentially tapers off (see Barabasi). Wikipedia follows this as do most other communities. Is the community an 80/20, or are more people engaged than this?
We can compare these metrics to established norms from other studies and cases, and determine how well we are doing. Still, the human in us tells us that we can do more with the networks. For example, we can design a better user-interface (a more human-centered design if you will) and psychologically fit the group to the tool. This is all cutting edge stuff, and we will see more in the immediate future.
We need to start examining a model of ROI in the new, networked organizations. This will get us closer to Org 2.0.
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