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Apr17
Presenting Data Visually
NextStage: Predictive Intelligence, Persuasion Engineering, Interactive Analytics and Behavioral Metrics Thanks to the readers who are sending me their thoughts on my email marketing, newsletters and related metrics posts. Please feel free to post your thoughts directly as blog comments.

I also appreciate people sharing various formulae they've developed with me. I'd like to make some suggestions about formulae and presenting data.

First, I appreciate involved computations, I truly do. You should see some of the math behind what we do. It is beautifully elegant only to people who do math for a living and then only a subset of them.

Sadly, elegant mathematics and involved computations aren't useful to most people. This is one reason NextStage uses such simple charts when we present results to clients and such. Let me give you an example (and recognizing there's a size limitation to what I can show you here):

male-female-legend.jpgLook at the image on the right. What information is being provided to you? I'll offer that the only information being presented is some colors, some numeric values and some words. Anything stated beyond that is a demonstration of someone (you, in this case, dear reader) adding context to the information.

People adding context to minimal information is very common. Most everyone does it. It's one of the reasons visual information needs to be designed to convey things quickly, easily and correctly. You always want the viewer to understand the information being presented, never to interpret the data behind the information because the moment interpretation begins information is lost.

It's wonderful when someone can look at visual information, describe exactly what is there, then recognize that they're going into an interpretation mode and state that what they are now offering is their interpretation of the data. Not everyone recognizes when they do that so it's best to remove all extraneous information from the visual presentation so the viewer's opportunities for interpretation are minimized.

Adding Content

male-female-small.jpg Now look at the figure on the right (you should be able to click on it to get a larger image). Now and only now is there enough information to state that we're looking at a chart of a male-female ratio. However, we have no idea what the chart is about. All we know at this point is that the male:female ratio is 78:22.

We've added content, more visual information. We still have no idea what the context of this information is.

Adding Context

male%20female%20ratio%20080410-small.jpg This last image (again, click on it for a larger image) is where everything comes together. The chart's title provides context for the information presented. It essentially answers the journalist's Who, What, When, Where and Why questions.

  • Who? Thirty randomly chosen NextStage client sites.
  • What? Website visitor gender breakdown.
  • When? Seven day period covering 3-10 Apr 08.
  • Where? Again, thirty randomly chosen NextStage client sites.
  • Why? To show the percentage of male to female visitors.
What to do with that information? Now you're dealing with interpretation and that depends on business goals. But (and it's an important But) anything added to the above graphic that biases the interpretation is not serving a business goals of those sponsoring the information.

Yes, I do appreciate the material readers have been sending me. My strong suggestion is that your computations can be as complex as you'd like, just make sure your presentation of end result of those calculations is simple and simply actionable.

 

Please contact NextStage for information regarding presentations and trainings on this and other topics.

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