New Metrics Are No Excuse to Continue a Pattern of Lazy Analytics: An Example Using Klout

As a student of analytics, I’ve learned that measuring success is never as simple as comparing two numbers. In fact, that’s exactly the kind of lazy analysis that can show false positives (or even worse, false negatives). To really do analytics justice, it’s vital to devote time to researching and understanding what you’re attempting to measure so that you can provide informative, relevant, and accurate findings.

A few months ago, a new metric for Twitter was created by Klout, a San Francisco-based company. Their “Klout score” measures your overall influence on Twitter: how much people listen to and respect your messages, and how likely they are to act upon and share those messages. Many third-party clients, such as Hootsuite and CoTweet, are now displaying the Klout score in their dashboards.

I personally think it’s great that Klout is gaining widespread acceptance. I feel it brings a true standard to the “quality” factor of social media analytics in contrast to the “quantity” factor of followers. However, I believe this score, like any other single metric, needs to be used carefully.

In this post, I’ll explain the mechanics of the Klout score, show an example of how similar Klout scores can be misleading when taken out of context, and explain why you can’t lean on new metrics to continue a pattern of “lazy analytics.”

The Klout Score

The Klout score is calculated from a broad range of data: your follower totals, how many accounts follow you back, how often you’re retweeted or mentioned, how frequently you tweet, etc. These data points are then boiled down into three values: your true reach, your amplification, and your network.

  • True reach is “the size of your engaged audience,” or basically those accounts with whom you engage with regularly, have common followers, and share similar interests.
  • Amplification “indicates how likely it is that your content will be acted upon,” in essence, the probability that you’ll get retweeted and how fast word with spread within your network.
  • The third value, network, is “a measurement of the influence level of the people who interact with you.” It’s important to note the emphasis on interaction here: this value is composed of the ratio of your followers vs. how many accounts you follow, how many of those you follow also follow you back, as well as unique senders and retweeters.

So, does this mean we can just look at the scores of any number of accounts and make assumptions about relative influence by directly comparing their Klout scores? No!

Let’s use an example to illustrate why.

An Example of Relative Influence… or is it?

As of August 30, 2010, I have a Klout score of 48. According to Klout’s calculations, this ranks me about halfway on the overall scale of 0 to 100, but based on the total number of accounts measured, I’m more accurately placed in the 80th percentile. Another Twitter account with a very similar Klout score is the CME Group, a Chicago-based financial firm billed as “the world’s most diverse financial marketplace.” Their current Klout score is 46; they’re also in the 80th percentile, overall. The CME Group’s Twitter account currently has over 750,000 followers, whereas I currently have 375. Their true reach is calculated to be 280,000, while mine is 9 (not nine thousand or nine hundred, nine… one less than 10).

At face value, based on Klout score alone, it looks like I’m just as influential as the CME Group, but when you start taking into account factors like followers and true reach, this assumption falls apart.

What happened? First, it’s because we’re making assumptions. Second, we’re missing context.

Let’s start digging into the data. You’ll notice that our network scores are roughly similar (59 for the CME Group, 57 for me), though my amplification is a slightly higher (21 for the CME Group, 26 for me). That still doesn’t explain why we have similar Klout scores, so let’s examine the supporting data points.

  • True reach: The CME Group has a massive amount of followers, but only follows back 0.003% of them; I follow back 20.3% of mine. They currently show 0% for both follower mentions and follower retweets, whereas I show 19% and 39%, respectively. This indicates that virtually no one seems to be talking to the CME Group or passing along their content. Note: While the 0% follower retweet looks like it’s a fluke, it may actually be a very small number (less than 0.1%) because of their high number of followers.
  • Amplification: The CME Group shows 77 total retweets, a mention count of 10, and 69 unique retweeted messages. I have 37 total retweets, a mention count of 254, and 31 unique retweeted messages. Their inbound/outbound message ratio is 0.26; mine is 0.74. This indicates that my followers tend to talk about me more frequently and are more likely to respond to me when I tweet.
  • Network: The CME Group’s follower to follow ratio is much higher than mine (172.71 vs. 3.16), their percentage of reciprocal followers is a bit lower (54% vs. 64%), and they have fewer unique folks who are mentioning them (10 vs. 71). They do have a higher number of unique retweeters, however (59 vs. 27). This indicates that my network is tighter and more engaged.

The key theme that emerges here is engagement. While my network and reach are much, much smaller in size and scope, I have a stronger connection with my audience. You also have to consider the function and audience of these accounts. The CME Group gathers and spreads time-sensitive financial information for consumption by their followers; they do some engagement, but are primarily focused on informing and sharing. I also share and retweet content (primarily on topics like social media and user experience), but I spend a larger percentage of my time connecting and talking directly with my followers. Not to mention, no one is trading stocks or making monetary decisions on my tweets (at least, not that I’m aware of). Finally, you need to consider the perspective: the CME Group offers a corporate experience vs. my individual one.

So, even though our Klout scores are very similar, you can’t say that I’m just as influential as the CME Group as a stand-alone statement. Our network, level of engagement, function, audience, and perspectives are significantly different enough to make this a false assumption. You could perhaps say we’re equally influential within our own unique networks, but not as a direct comparison. You have to consider the context.

Don’t Be Lazy With Analytics

As with website analytics, you should never use a single metric in a vacuum to make assumptions on the success or failure of what you’re measuring. Think for a moment about hits. Have you ever been asked to compare the number of hits on your website with those of another website? It’s a thoroughly unfair comparison. Even if the sites in question are similar in audience and purpose, you have many things to consider, such as: originality, readability, and freshness of content; strength and effectiveness of marketing and promotions; ease of use and overall usability; ranking for relevant terms in search engines. Each and every one of these factors, as well as a number of others I haven’t mentioned, all contribute to the success or failure of a website. Taking only one metric and directly comparing it to the same metric for a completely different website is not an apples-to-apples comparison, no matter what you may think. It’s essential to take everything in context and do thorough research of the data to determine relative success or failure when making comparisons.

It’s exactly the same with the Klout score.

You can see from my example how much happens behind the scenes in order to generate a Klout score. It’s a deeply interesting and unique metric in its own right, but, just like with website hits, it needs to be examined and valued in context with its supporting data points to form a complete picture of relative influence.

Don’t be lazy by looking at just one metric to measure your influence on Twitter. If you’re really interested in determining how well you’re doing or what you need to improve in order to make your presence in this channel more effective, do your homework: sift through the data, observe trends, and pay attention to the purpose and audience of your account. Klout allows you to refresh your score every six days, so take advantage of that feature and keep refreshing your score to see how your data shifts over time.

  • http://www.cmegroup.com Allan Schoenberg

    Mike — Thanks for pulling this together. I’m a firm believer in measurement and analytics, and you bring up some great points (Disclosure: I also manage CME Group’s presence on Twitter). While all of these tools and resources have helpful, perspective and context are two key points. We continue to try to improve what we do with social media and focus is be relevant, timely, open to ideas and conversational. We’re a large brand in a niche part of the economy so this presents challenges, but we also look at them as great opportunities to tell our story.
    Allan

    @allanschoenberg

    • http://www.bright-matrix.net/ brightmatrix

      Appreciate your reply, Allan. I like your perspective on social media to “tell our story”; it’s that “social” part of the medium that firms seem to be hesitant about. Another vantage point for business efforts in SM could be, “what makes for a successful story about us?” It’s something I’ll want to give more thought around in the near future.

      I like that you’ve cited the CME Group as being “open to ideas and conversational.” Those aspects are so vital in social media. We are all learning and continuing to learn.

  • http://blog.sysomos.com 40deuce

    Great post Mike.
    You make a great point that all of these measurements are very relative to the context in which they’re being used, and a lot of people know about Klout but don’t really undertand the metrics behind it.
    It’s very true that people shouldn’t be relying on one single metric when they are analyzing their social media data. Especially one that they are just given. As well, people need to know what metrics actually matter to them. Every social media campaign has different goals, so you can’t really compare apples to oranges. What works for one company/campaign isn’t going to work for a different one.
    I’m a big advocate in people using bench marking to do their analysis, that way they can actually pick what they want to look at and see where that metric started and where it has gone from there.
    People should be using the metrics that mean something to them specifically, and not just what others use.

    Cheers,

    Sheldon, community manager for Sysomos

    • http://www.bright-matrix.net/ brightmatrix

      Thanks for your insight and feedback, Sheldon. Your point about knowing what metrics matter to your business, organization, etc. is quite critical, not only from knowing what to measure, but how to measure success (or failure). Knowing which metrics “mean something to [you] specifically” reminds me of a quote I once heard about SEO: “Everyone ranks well for something. What [terms] do you want to rank well for?”. Excellent food for thought.

  • http://paulgailey.com Paul Gailey

    Thanks for post Mike. I´d be interested to read how it stack´s versus other influence filters.

    I understand Klout have data for “10 million plus” accounts which is, as of just announced twitter universe, less than 7%. Of course you can then argue how many are active/inactive twitter accounts, and that´s the point with these figures, they are contentious. Just like 500million FB accounts does not really matter (to them) compared to their continuity of use metrics.

    Klout filtering tweets in real time is an improved way for monitoring and segmentation for major events/brands. It can really help sort wheat/chaff as social noise just gets louder. Many will want better meta filters and super social filters.

    If Klout metrics become a currency as universally accepted then they carry more credibility regardless if they are imperfect currency, but who beyond geekdom is going to know? Does that matter, will such a tool get beyond the SM managers or will it ingratiate itself even more into the apps to get end user exposure?

  • Kathy M

    Great column, Mike. Been thinking about a lot of these ideas myself. No one seems to be able to figure out what a good multiplier would be. But then, I guess the newspaper can’t really measure how many people read that newspaper that I left behind in Starbucks either. Or at least that’s how I try to think.

  • http://www.margieclayman.com Marjorie Clayman @margieclayman

    This is the best post I have seen about Klout. Through painstaking research and writing, you’ve proven what I have given voice to, which is that while Klout may be useful, people give it a little too much clout.

    Fantastic post!

  • http://www.peerindex.net Azeem

    Mike

    You’ve put your finger on a key issue – which is what is the role of the metrics or rankings in any growing market.

    I would add two observations–really building on your insightful blog post.

    The first is the criticism that metrics are not transparently described–a criticism that is leveled at us at PeerIndex, as much as it is leveled towards Klout. The issue here-as true for us and is it for Klout-is that rankings and metrics are our business. Time, intuition, care and attention gets applied to testing and tuning our models to generate scores. These aren’t things built by teenagers in an afternoon and left to run. The result is that not only are they proprietary, but they are complex and tested rigorously.
    And what goes into generating those scores is often a complex model involving in our case a mix of graph analytics (including a set which includes Pagerank) as well a bunch of other statistical techniques.
    The result is much like Google’s ranking of pages: Google can’t tell you exactly what the effect of an extra inbound link would be, or what improving metadata on each page would be – but what google can tell you is that doing those things could improve your pages discoverability, all other things (i.e. all other pages and links between them) remaining equal.
    In the case of PeerIndex, I can’t tell you exactly what adding 20 high quality followers or being retweeted more would do for your scores. What I can say is that all other things being equal, tweeting to a high quality and engaged audience and having them engage with you, should improve your scores. (Unless other people do the same or more!)

    The second thing is about the purpose of rankings. Now I would agree Sysomos here–that you need to be understand what you are looking for, and tune your selection of metrics based on that.
    The best analogy I can give is in the corporate bond market. Millions of bonds, it’s hard to navigate. So S&P and Moody’s provide bonds with ratings against a scale. The ratings are a first cut to help you navigate the millions of instruments. However, any serious investor making a large investment will assign a credit or bond analyst to dig deeper into the company backing the instrument in question. The S&P rating guides you. Your own research builds the investment case.
    But most importantly S&P ratings are based on historical data of default rates. So an S&P rating of BBB has a 5yr default rate of 0.4% based on 30 yrs of history of how similar bonds have behaved. In other words, they are embedding a predictive claim.
    However, that we haven’t yet built the historical datasets that allow us to model and describe the predictive value of ratings is no reason not to find utility from them–either as end users or as companies. And ratings from ratings providers have the benefit of being internally consistent, continuously invested in and having better price/performance than ad hoc research projects.

    Thanks once again for a thoughtful post.
    best
    Azeem

  • Pingback: Social Media Measurement 2011: Five Things to Forget and Five Things to Learn « MetricsMan

  • Pingback: Social Media Measurement 2011 «

  • http://www.3angelsmarketing.com Karima-catherine Goundiam

    Hi Mike,

    With the plethora of analytic tools and mainstream being able to access data easily, you are totally right to warn against blind adoption.

    I like the parallel you make with website as in today, convergence makes it almost compulsory to never take one metric out of its context. We have to look at numbers in perspective and more importantly, as you point it, make sure we actually know what we are measuring.

    Always great to read you,

    @KarimaCatherine

  • Pingback: #30Thursday number 11 for 11/11