You are currently browsing the tag archive for the 'data' tag.
We see a lot of data and present it in a lot of different ways, so when someone is out there analyzing the analysis it brings out the research geek. I tripped across Junk Charts today, a site dedicated to highlighting some of the worst in infographics. You can also follow the site on twitter, here.
Photographer and mathematician Nikki Graziano overlays graphs and their corresponding equations over full color nature photography. This set of engaging compositions reminds us of the elegance and “art” of math, and its essential function as a descriptor of natural phenomena. Click through the image below (and keep clicking) to check out the full “Found Functions” set.
Kudos to The Awl for two fairly recent charts featuring publishing statistics from the past decade. The images are too tall to just recopy in a single post here, but click through to check them out. This trend data, sourced from the Magazine Publishers of America and Audit Bureau of Circulations, respectively, is very interesting, but I’m particularly fond of how they’ve crafted the charts – in a tall, blog-friendly format rather than on a standard wide frame:
Steve and I have been exploring the online reference site, The Book of Odds. Some of the site’s key functionalities are still in Beta, but for over three years they’ve been compiling odds to create a large database of “the odds of everyday life.” You can sign up for free and provide a little profiling information to begin exploring statements of probability related to your profile, or to anything you want to look up.
The idea is to explore the odds of something happening, and then to calibrate the probability in a comparison. If the topic you explore is included in the database (the four main current topic portals are Health & Illness, Accidents & Death, Relationships & Society, and Daily Life & Activities), you’ll get confirmed probability data on that topic, but you’ll also get leads on unexpected connections, as you compare unrelated events by their likelihood of occurring.
The site also has social and learning functions, and content aside from the odds database (newsletters, blogs, related links, etc.) We’re just getting started exploring this resource, and brainstorming about how we can apply it to our day-to-day reference needs. It’s actually pretty challenging to think about life in terms of probability statements – thinking up queries to get started. But once you dig into the site, there’s quite a bit to learn – not only the small bites of data, but how to calibrate probability, and new approaches to classifying and comparing phenomena.
At what price would you consider this product to be cheap?
At what price would you perceive this product to be too expensive?
At what price would you consider this product to be priced so cheaply that you would worry about its quality?
At what price would you consider this product to be too expensive to even consider buying it?
These four very direct and intuitive questions form the basis of the Van Westendorp pricing exercise – a quantitative research technique that can actually yield robust and compelling data reflecting consumer demand. We’ve been thinking about the wide variety of quantitative analytical techniques we use in our work, and thought we’d provide a quick overview on this one.
The Van Westendorp pricing exercise is a price sensitivity measurement devised by a Dutch psychologist, Peter van Westendorp. This technique uses four questions about a product or service (drafted more or less like those above) and requires the respondent to gauge prices that are too cheap and too expensive in context with the product or service’s offerings and perceived benefits.
Frequency distributions from these questions are derived and plotted, yielding the range of pricing options for the product. As the final step in this process, purchase intent is measured at the highest and lowest prices in the range of pricing options. The optimal price (i.e., the price which maximizes market share while generating the highest possible revenue) can then be computed, along with the precise range of acceptable pricing.
The data points on the example chart are plotted a little loosely, but the point at which the Too Cheap and Too Expensive responses intersect is considered the Optimal Price Point (OPP). The intersection of Expensive and Too cheap yields the Point of Marginal Cheapness (PMC). At this price point, the number of people considering the product to be too cheap is the same as the number considering it to be expensive.
The intersection of Cheap and Too Expensive yields the Point of Marginal Expensiveness (PME). At this price point, the same number of people regard the product to be too expensive as regard it cheap. The range from PMC to PME is the Range of Acceptable Prices (RAP), or the Optimal Price Band.
We also conduct pricing studies using conjoint and discrete choice designs, but the Van Westendorp pricing method is the most efficient way to evaluate price sensitivity itself, as the resulting data resulting is easy to interpret, identifies an entire range of acceptable price points, and provides a solid basis to assess future pricing strategies, ensuring that the optimal price-value balance is established. Contact us if you’d like to learn more about this research technique.

I love sports. I love infographics. Therefore, this site, FlipFlopFlyBall really hit the spot. It offers several dozen, fresh, beautifully-designed infographics that show you a side of sports that you don’t usually see. Take the above graphic, for example. It’s a lovely poster that shows the relative size and shape of the thirty MLB parks.
While it focuses heavily on baseball, the site seems to be delving into other sports. Note the “size comparison of lots of sporty balls” towards the bottom of the page.
Enjoy.







