MOTION CHARTS SHARPEN FOCUS

Hi All, this is MediaPost News Item, which talks about what Google Analytics Motion Charts that gives analysts the ability to give data "point pattern analysis." The visualization tool offers a wealth of insight at one glance, but a newsreporter has noticed the Google's feature hasn't gained much traction. She attempts to analyze why, suggesting that many marketers' and SEO professionals' relative lack of experience graphing data could contribute to the problem.

Nawal.



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Did Google goof, Hullman asks. "Despite the focus on the graphs themselves, thinking about the audience is a huge part of the successful application of a visualization tool," she writes. "A user's 'graph sense' is the knowledge that develops gradually as a result of creating and using graphs in variety of problem contexts."




Motion Charts are Hard”
Posted by jhullman at 11:33 am | Filed In Analytics, Design

Two months ago, Google Analytics Motion Charts were hot. Now, they’re not, at least if we trust the amount of traffic coming to this blog looking for information on the charts and the amount of new content being produced around this feature. Is this a natural consequence of time since the feature was released, or is there something about the Motion Charts that make them less-than-user friendly? Did Google possibly goof?


When Google Analytics released Motion Charts several months ago to the public, a brief flurry of excitement ensued over the moving bubble graphs, amid so many static line and pie charts. Traffic to this blog, for example, increased substantially based on content around the charts, both here and linking here. The excitement seems to have died down, though, at least if we can trust the decrease in visitors reaching the Pure Visibility blog using a query containing “motion charts”: 64% less visits have come in the last month on such queries, compared to two months prior.

It’s my hunch that the natural fading of interest in the time passed since the feature’s launch is only one factor in the decrease in popularity. The other factors relate to a more general observation that information visualizations, meaning tools and graph builders like Motion Charts, have become available to much wider audience than was previously the case. Once, seasoned statisticians and some medical and other hard science researchers used sophisticated graphics tools. Now, every one, and their mom, literally has dabbled with graph creation. Problem is, there are dangers associated with putting powerful tools in the hands of novices, problems that more than one researcher in the field of InfoVis has noted.

The first, illustrated by the Motion Chart depiction of search traffic on the query “motion charts are hard”, is that the audience of many such visualizations does not know how to use them. Consequences? Lost time, predictions made based on scanty understanding, not to mention the creation of many hideous graphics.

Motion Charts are Hard

The overall trend toward ‘Visualization for the masses” may be a result of the fact that it has become easier to design graphic tools. Once, only the hardcore computer scientists tackled graphical programming challenges. Today, a number of user-friendly languages like Flash, Flex, and actionScript make it possible for more people to design. A result of more focus by more designers on infovis applications is tool proliferation. Suddenly, we have a tool for everything, and if we don’t there is likely one that can be tweaked to fit where there is a need. Motion Charts are an example of a tool designed for a more specific purpose (Gapminder) being repurposed for a wider audience. Feature proliferation is a related problem that is very observable in jsut the short time that Motion Charts have existed. Now, Motion Charts offer several view choices, including a jarring ’switch to bar graph’ tab, as well as check boxes and drop downs galore.

The question is, how much thought went into this particular tool in the context of web analysis? How much thought went it to the level of complexity it introduced into an analytics package that already provides a great deal of data, perhaps more than the average user can meaningfully process in the time they have? Should Google have not introduced Motion Charts at all?

Despite the focus on the graphs themselves, thinking about the audience is a huge part of the successful application of a visualization tool. A user’s ‘graph sense’ is the knowledge that develops gradually as a result of creating and using graphs in variety of problem contexts. Graph sense can vary considerably between individuals, even in the same population. A relative lack of experience graphing data in many dimensions may be one reason for the Motion Charts downfall. I don’t doubt there is a correlation between finding the graphs useful and having past experience with tools like Gapminder and ManyEyes, which offer similar charts.

I, for one, though, do not believe that the charts themselves are a failure. They offer analysts the ability to analyze data in a new way that has proven successful in other populations such as statistics, by making it possible to do point pattern analysis. This hinges, of course, on whether the analysts are ready to receive them and have time to learn their features. And this is where Google’s responsibility comes in.

Leland Wilkinson, in a grammar of graphics, writes that “the obvious problems caused by [the proliferation of visualization tools] do not justify blunting our tools, however. They require better education in the imaginative and disciplined use of these tools. And they call for more attention to the way powerful and sophisticated tools are presented to novice users.” So the real question is, has Google done enough to ease the Motion Charts into the overall Analytics package, not only on the surface but when it comes to the user models that accompany it? To give Google some credit, they did devote multiple examples within the help documentation to explaining how to use the charts. But is it enough to put documentation out there? Its my belief, though, that a more concerted effort might be required. For example, continuing creation of content that provides flexible examples and answers FAQ, videos, even short tutorials that go beyond just making the graph to include zeroing in on whether it worked or not given an analyst’s question.