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Better Graphics

storytelling market researchMany researchers are by nature math geeks. We are comfortable with numbers and statistical methods like regression or max-diff. Some find the inclusion of fancy graphics as just being a distraction...just wasted space on the page that could be used to show more numbers! I've even heard infographics defined as "information lite". Surely top academics think differently!
No doubt if you asked top academics they might well tell you that they prefer to see the formulas and the numbers and not graphics. This is no different than respondents who tend to tell us that things like celebrity endorsements don't matter until we use an advanced method like discrete choice conjoint to prove otherwise.
Bill Howe and his colleagues at the University of Washington in Seattle, figured out a way to test the power of graphics without asking. They built an algorithm that could distinguish, with a high degree of success, between diagrams, equations, photographs and plots (bar charts for example) and tables. They then exposed the algorithm to 650,000 papers with over 10 Million figures in them.
For each paper they also calculated an Eigenfactor score (similar to what Google uses for search) to rate the importance of each paper (by looking at how often the paper is cited).
On average papers had 1 diagram for every three pages and 1.67 citations. Papers with more diagrams per page tended to get 2 extra citations for every additional diagram per page. So clearly, even among academics, diagrams seemed to increase the chances that the papers were read and the information was used.
Now we can of course say that this is "correlation" and not "causation" and that would be correct. It will take further research to truly validate the notion that graphics increase interest AND comprehension.
I'm not waiting for more research. These findings validate where the industry has been going. Clients are busy and their stakeholders are not as engaged as they might have been in the past. They don't care about the numbers or the formulas (by the way, formulas in academic papers reduced the frequency with which they were cited)...they care about what the data are telling them. If we can deliver those results in a clear graphical manner it saves them time, helps them internalize the results and because of that increases the likelihood that the results will be used.

So while graphics might not make us feel smart...they actually should.

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Numbers That Don't Add Up

Posted by on in Better Graphics

In my last blog I talked about a simple chart on Morning Joe, which was presented by Steven Rattner. I submitted that when we see data presented in the media or especially by politicians, we should judge it in terms of how a researcher would have presented the same data (because of course researchers are free of bias...well let's leave that for another blog). I gave Mr. Rattner a pass last time, but his presentation of a chart on infrastructure was misleading and would only have pleased a client who wanted misleading data to prove a point.

In this case he presented a chart showing infrastructure spending as a percentage of GDP . It showed a massive drop from the high in the 1950's to the low of today. The chart had a y axis that went from 0% to 1.5% which made the drop easier to see. Nothing wrong with that (assuming those viewing the chart understood that it was not based on 0-100%).

A  few blogs back I talked about how the political season would bring on a rash of misuse and abuse of numbers. I've had my ears open for examples and a couple that came up recently got me to realize that a more nuanced view is necessary here. The real rule should be that pundits and politicians should be held to the same standards as we are by our clients. Namely, the numbers should help in the decision making process...not mislead or confuse the facts.

In the next two blogs I'll use some charts presented by Steven Rattner on the Morning Joe television program. For those of you who don't know, Mr. Rattner was the President's Car Czar. While this probably means he comes with his own bias, I have generally found that when he presents data he does so in a pretty fair way.

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