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Nisan Leaf Ad: Misleading Information Design?

June 13, 2011

I recently saw this ad for Nisan’s new electric car showing the “miles per dollar” you get with various popular cars:

See if you can spot the misleading info-design.

The MP$ is shown on a horizontal axis on a linear scale and cars are called out at their relavent markers. That’s fine. However, they’ve added an arch from 0 for each car which seems to be a way of visually implying the route you could travel with that car: start at 0, follow your color in the rainbow and you’ll end up as far as you can get on a single dollar. The distance traveled following the arch is still relatively the same as the distance from start to finish. But the area of the semi-circle under the arch is now growing at a much faster rate than the distance travelled — in favor of the leaf.

For example, the ratio of the MP$ of the prius to the leaf is approximately 0.72:1. But if you compare the areas under each one’s arch, the ratio is now about 0.52:1 prius to leaf — a 38% gain for the leaf. And it gets more exaggerated as the initial distance grows: the civic to leaf ratio is 0.42:1 whereas the ratio of their areas is about 0.18:1 — a 130% gain for the leaf.

Instead of comparing MP$a to MP$b, your brain is probably comparing (MP$a)² to (MP$b)². Although nobody is sitting down and figuring out ratios like this when they glance at the ad in a magazine, your brain can easily take into account the relative areas of   overlapping circles. It shouldn’t be much harder than comparing positions on a number line.

One Comment leave one →
  1. July 5, 2011 12:21 am

    Yes Ariel, I do agree. This ad is misleading.

    Second the arc design is a serious problem. If a scientist did this, his reputation would be in jeopardy. In design, are standards for the truth existent? Are people held accountable?

    Information design can be very dangerous and misleading, because each design must reach a definitive conclusion for the client. Whereas in science reaching a definitive conclusion is elusive.

    An example, scientists must list their sources and label their graphs’ purpose so the viewer does not infer wrong information.

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