My Klout Score Went Up, but What Does It Really Mean?
Measuring social media influence may be becoming more meaningful. Klout recently announced that they have updated their service to add context and substance behind a user's Klout score. According to an article by the Chicago Tribune, Klout now includes 400 relevant input parameters as well as Wikipedia and LinkedIn information to more accurately measure a person's online influence. Daily input data has also increased, from 1 billion to 12 billion data points from social media sites like Tumblr and Google+.
Obama vs. Bieber
Past criticism of Klout surrounded the idea that social influence could be quantified by a single score between 1 and 100 as calculated by an algorithm. Under this methodology, celebrities like Justin Bieber were previously judged by Klout to have more social media influence than President Obama, largely because Bieber's loyal Twitter followers retweeted his posts and followed his every move. Under the new algorithm, the single score is still awarded, but the additional reference parameters are said to more accurately reflect an individual's influence. The new algorithm now awards President Obama with a higher influence score than Bieber's.
One of the challenges that midsize businesses face is that slim budgets mean that social media monitoring and the business analytics that go along with quantifying influence are difficult for the IT analyst to do in a targeted and meaningful way. So when the company has a stake in a social presence, when influencers are important to the business model, the IT analyst is always on the lookout for tools that capture social data from many sources and can be shown to be credible in their assessment of influence.
The goal is to find the tools that fit the needs of the analyst, rather than adjusting the business needs to fit what the tool is able to analyze. Perhaps the criticism of Klout and other social media analytics tools should be that they are still too broad in how so-called influence is quantified, making it difficult for businesses to decide how to use the resulting information.
Certainly adding "real-life" data culled from LinkedIn and Wikipedia gives some assurance that the input data to the Klout algorithm is becoming more meaningful, but as the article points out, the Klout score of most users went up as a result of the upgrade. One would not expect that this means that everyone is suddenly that much more influential, but it begs the question: what, then, does it mean? Perhaps the lesson is that IT analysts still need to be mindful of underlying statistics used in any analytics tool. That is, know what a statistic means before relying on it to make business decisions.
This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. Like us on Facebook. Follow us on Twitter.