Bright Matrices

Writings & musings of Mike Zavarello (a.k.a. brightmatrix), a "red mage" web developer.

Tag: data visualization

My 2011 Wish List for Klout

This has been quite a year for Klout. Their suite of measurements, specifically their “Klout score,” has risen to become a recognized standard in the realm of user-generated content and social communications. They’ve generated numerous articles on how corporations and industries are considering Klout to award perks, recognize influencers, and even possibly screen for job applicants. Klout has become, in essence, a “credit score” for the social space. Of course, detractors have had their say, and I’ve written my own article on why Klout’s metrics need to be used within their proper context.

I realize Klout is nascent, but the fact that they’ve gained the clout (pun intended) they have today speaks volumes for the need for solid, reliable metrics in social media. With each announcement Klout releases, I admit I find myself craving more. So, in the spirit of the holidays, I’ve cobbled together a “wish list” of features I’ve love to see from the good folks at Klout in 2011.

More Historical Data

Right now, Klout’s various charts show measurements up to 30 days in the past. As an avid student of analytics, the ability to delve further into the past and download that data for further analysis would be valuable for tracking trends and correlating against other communications and campaigns I work on.

I really enjoy the flexibility offered by Google Analytics, where you can show comparisons between two spans of time, send yourself automated reports in various formats, and slice the data in any number of ways. If Klout released a similar suite of data tools, they would make me, and I’m sure many other analytics geeks out there, very, very happy.

Comparison of Metrics

Klout provides a healthy array of charts that show trends and measurements of several supporting metrics, not just the Klout score itself. It would be great to see overlays of various metrics, such as my inbound/outbound message ratio laid atop my amplification score, to see how the various data points interact with and affect each other.

I realize this could stray into “correlation does not equal causation” territory, but we’re not talking “pirates vs. global warming” here. I don’t see the various data points being that off target to create egregiously false assumptions. That is, of course, provided people continue to do their homework.

Data Segmented by Channel

Originally, Klout was focused specifically on Twitter. Starting in October 2010, however, metrics from personal Facebook pages were added to the mix, and a beta for gathering LinkedIn data is in the works. If you had tied your Klout profile to Facebook, historical data was adjusted as of October 21, 2010, which resulted in often dramatic changes to your overall score.

A sound tenet of communications strategy is matching your message to the medium. It may not be effective or possible to broadcast, engage, or interact the same on Twitter as Facebook or LinkedIn. Therefore, I would expect overall influence to differ between channels.

While an overall Klout score (and its supporting metrics) is useful as a broad indicator, it would be immensely helpful to segment the data by channel so I can give more thought and consideration to how I communicate on that channel.

Real-time “Influenced By/Influencer Of” Updates

Klout offers a simple chart of whom you influence and who influences you. Up to five of each is shown in your profile. Currently, this “rogue’s gallery of influence” isn’t updated with any frequency; my set has been the same for many months, and others in my network have reported the same situation. Most the accounts shown in this chart are pretty obvious, but it remains a good insight into the cornerstones of your network. I’d love to see more “drift” here.

Transparent Data on Total Number of Profiles Indexed

Klout doesn’t automatically connect to every single Twitter or personal Facebook profile; in most cases, you need to create a profile to share your data and acquire a score. Why is this important? If you connect your Twitter account to Klout, your score is relative to all other Twitter accounts captured in Klout’s database, not every Twitter account in existence.

As with any study or poll, it’s necessary to know the total size of the data set in order to establish weights or bias on the resulting statistics. Currently, Klout doesn’t share the precise number of accounts they index. I’d like to see more specificity and transparency here.

I feel this is important for measuring and reporting on success in the social web. While I’m sure a healthy amount of influencer heavyweights are already ensconced in Klout’s data sets, knowing the total number of indexed profiles will help put the scores into more accurate and meaningful context.

Hub-and-Spoke Influence Diagram

This is more of a “pie in the sky” request, but it would be sweet to see a hub-and-spoke diagram of influencers. The current “influenced by/influencer of” chart allows you to click on a specific account to jump to their Klout profile, wherein you can see who influences them and who they influence in turn. I’d love to browse through a Flash- or AJAX-based hub-and-spoke diagram that could show me dynamically who connects to whom in the influence realm.

The Obvious Conclusion

The obvious conclusion about the features in this wish list is that Klout could set up a “freemium” model: continue to offer the current suite of metrics and charts at no cost, and then offer an extended array of features to monthly paying subscribers. Hootsuite did much the same recently with their social services. Such a model would allow Klout to continue to add to its user base and secure a source of revenue from dedicated users.

Notes From Edward Tufte’s “Presenting Data and Information” Course

On July 28, 2009, I attended Edward Tufte’s “Presenting Data and Information” course in Philadelphia. Tufte is well respected for his expertise in data visualization and equally renowned for his complete disdain of PowerPoint as a communications tool.

I recently came across a page-and-a-half of handwritten notes I had taken during the lecture and wanted to share what I recorded. Below are elaborations on these notes.

  • Begin with the content by asking the question: “how can something be explained?” Be guided by the task. Don’t choose the mode of presentation in advance: it’s not about pre-specifying the dataset or methodology.
  • The character of relationships between elements is just as vital as the elements themselves. Provide “reasons to believe”.
  • Use causality thinking: which properties effect and govern the cause.
  • Annotate everything: annotation is the heart of explanation. Annotations reside in the background. They are subtle, but clear and help avoid optical clutter. Annotating “linking lines” adds credibility and texture to causal links.
  • Use tables; don’t be afraid of them. People read huge tables all the time: think sports, weather, market data, etc. “Bring your presentation up to the level of the sports section.”
  • Replace “chart junk” with evidence (but not selected evidence; avoid being a “cherry picker”).
  • Supergraphics are interactive: they allow individuals to explore and find what’s important to them and encourage discussion among an audience. Everyone will look at a different section at the same time. Find a really good supergraphic to open your presentation and give it to the audience on handouts.
  • There is no such thing as information overload: there is only failure of design. Add detail to improve clarity and content. Use more tables than graphics, especially for smaller numbers.
  • PowerPoint is “a corrupt method of displaying information”. PowerPoint presentations set up a dominance relationship with extreme information denial (“a long and winding road”).
  • Integrity, relevance, and interest are content properties that design will not correct.
  • Find good reports and copy them (but have good taste); “stay out of the design business. Don’t get it original; get it right”.
  • For intellectual models, avoid marketing speak and corporate pitches; you want “non-fiction credibility”.
  • Use wall charts in project management. Make comparisons over space vs. a sequential series of slides (“stacked in time”).
  • Letter codes, legends, keys, etc., are impediments to learning. They are not universal, but instead “one-off” creations that are good for only one instance. Get viewers out the decoding business: use direct labels.
  • There two issues in information design: multivariate problem: the dimensions of data need to be communicated on a two-dimensional display (“flatlands”). Every interesting analytical problem is more than one to two dimensions or factors. Information resolution: A way to measure progress in communication and presentations. Think: what is the rate of information throughput in my presentation?
  • Use the “brute force” method: build a model by getting a real object in the room.
  • The segregation of information by modes of production is a conceptual error.
  • Don’t insult or fail to respect your audience. Maintain intellectual integrity without patronizing. It’s not considered “dumbing down” to remove jargon for dispersal to a larger audience.
  • Give users the freedom to consume the material how they want.
  • For the opening screens (home pages) of websites, show off what people can learn there. People are good at scanning: they will scan, then scroll, then click; keep it flat and rich. 90% of every screen, excluding navigation, should be content.
  • Sparklines reduce “recency bias” by showing changes over a larger span of time.
  • When giving presentations, remember the following: Work on content. Practice. Show up early. Use handouts and Word documents (never PowerPoint slides). Leave more than one copy of technical reports. Define what the problem is, who cares, and what the solution is.

Here are several key quotes I jotted down during the lecture:

  • “Do whatever it takes to display something.”
  • “Document everything and tell people about it.”
  • “The metaphor is the map.”
  • “A feature that is buried is not a feature.”
  • “Talent imitates, but genius steals.”
  • “The person who heads up web design is a content expert.”

The course was more lecture than seminar, but Tufte kept me interested and engaged throughout the day. A bit prickly in person, he’s nevertheless an excellent presenter. I would highly recommend the course as a “professional development opportunity” (i.e.: training) for those interested in how to present content and data in pretty much any form, not just visual representations. Plus, you get all four of his books to add to your library, which is an excellent take-away… more so than a flash drive or fancy badge clip.

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