Survey Results: Are the Viz-Pundits Really Helping?

A few weeks ago Juice asked our readers to give us a few insights into whether or not we and other info-viz sites are actually helping them and their organizations be more effective at communicating information.

Well, the time has come to take a look at the results (oooh - pins and needles). The survey was way more popular than we expected, receiving well over 500 responses.

We had a few questions that were of the form "select the answer that best describes you" but, for the most part, we focussed on text based answers so that we could try to avoid directing the answers and could demonstrate some non-traditional visualization styles to explore results. As a side note, the open ended answers to the text based questions were truly intriguing to read - hopefully the presentation of the results below will give you a small insight to what we learned.

So, here are the results.


Survey Results

The first section of questions dealt with getting some context about our readers. Since the questions were multiple choice, we're showing the results in traditional bar chart format.

Question 1

In terms of size, which of the following is your company most like?

  • A one man band
  • The Dirty Dozen
  • The University of Rhode Island
  • Microsoft

Q1: Company Size

Question 2

In terms of information presentation expertise, who do you see yourself as?

  • The Excel Chart Wizard incarnate (I'm happy with the quickest route)
  • Harold and the Purple Crayon (I'm pretty good, but not too finicky)
  • A Tufte clone (every chart is carefully and lovingly crafted with intention)

Q2: Expertise

Question 3

If your company were stuck on Gilligan's Island, would you be able to use information presentation to get rescued?

  • No, Gilligan keeps using our Tufte books to prop up the break room table.
  • Maybe. The Skipper rigged up this island beacon system using coconuts, vines, and tiki torches.
  • You betcha! The Professor could build a huge island sized information display that could be seen, understood, and acted upon by the astronauts on the International Space Station.

Q3: Escape from Gilligan's Island

Question 4

What two information sources do you most frequently use for information presentation tips, trends, and best practices?

  • BI Vendor's website (e.g., Business Objects, Tableau, Cognos, etc.)
  • The Dashboard Spy
  • Dashboards by Example
  • FlowingData
  • Infographic News
  • Information Aesthetics
  • Jorge Camoes' Charts
  • Juice Analytics
  • Junk Charts
  • Tufte's web Site
  • Visual Business Intelligence (Stephen Few's site)
  • VizThink
  • Other

Q4: Popular Sites

However, What we really want to know is what sites are most closely related. So we tried looking at them with a phrase net from ManyEyes:

Q4: Phrasenet

( You can experiment with it yourself here. )

This is a great way to demonstrate how sites are "connected". We see a very strong relationship between Juice and the other non-Juice sites, but not a strong relationship between the non-Juice sites, themselves. In retrospect, the question would have been more effective had we asked respondents for their "top three or four" sites (approximately: total number of options รท 3).


The next group of questions were crafted to help us understand the problems our users and their organizations are encountering when it comes to presenting information to stakeholders and users. For most of these questions we broke the number one rule in surveys: stay away from text based answers.

Question 5

Using one word for each, list three things that you most frequently find useful from these sources?

Q5: Tag Cloud

( You can experiment with it yourself here. )

This was one of the most useful result sets and clearly shows that people like examples and new ideas for visualizations, followed by tips on how to get it done. (I'm hoping this post meets all of those criteria to some level.)

Question 6

Within your organization, would you say the understanding of information visualization best practices is:

  • Staying the same
  • Improving

Q6: Improving?

Question 7

What one word describes the biggest barrier to improved information presentation at your company?

I selected a Wordle (as opposed to a tag cloud) for questions 7 and 8 because I wanted to see the results in a way that would give me the general feeling of the barriers and benefits - I wanted the answers to spur some sort of emotive response. I think a Wordle does this better than a tag cloud.

Q7: Barriers

( You can experiment with it yourself here. )

Question 8

What one word describes the biggest boon to improved information presentation at your company?

Q8: Benefits

( You can experiment with it yourself here. )

While the "barriers" answers were interesting, there are some real nuggets hidden in these "benefits" results.

Question 9

Finish this sentence: "My company would be oh so much better at information presentation if we just had..."

What we really want to know is what are the patterns and relationships between words. Having said that, the most common words are still interesting to see:

Q9: What would be better?

( You can experiment with it yourself here. )

But, we are really interested in the word patterns. So, we used the Juice search patterns tools Concentrate to identify patterns. The top patterns were

Pattern Count
more X 76
more time X 30
better X 29
X data 15
X time 15
more time to X 14
time X 12
a better X 11
X data. 9
X more time 9
people X 8
more people X 7
more resources X 6
the right X 6
more people who X 5
people who X 5
time to X 5
more time and X 4

Now, if we look at how the "non-common" words relate visually, here's what we get:

Q9: Phrasenet

( You can experiment with it yourself here. )

Question 10

Finish this sentence: "If I were to advise someone on how to best improve your capability to create really useful information presentation solutions, I'd say don't forget..."

Again, it's interesting to see the most commonly used words:

Q10: How to improve

( You can experiment with it yourself here. )

But the most value again comes from looking at the phrase net:

Q10: Phrasenet

( You can experiment with it yourself here. )

Question 11

Finally, we're going to post results on our blog for free download. However, if you want us to notify you when the report is ready, please provide your email address below. (And because we have a large international following, please add your country as well, if you don't mind. Why? 'cuz we're just curious. Thanks!)

So, we're going to show only the countries here, no email addresses (whew!). Let's start with looking at the standard distribution:

Q11: Respondent Countries

And here's the geographic representation from Many Eyes:

Q11: Many Eyes Map

( You can experiment with it yourself here. )

But, having looked at that, I thought it might be a little more interesting to look at the country locations like this (text sized based on number of participants):

Q11: Country Cloud


Additional Insights

And that was all of the questions that were in the survey. However, I thought some of the multiple choice "context" question required just a bit more analysis; there were some questions I still had that weren't yet answered. So, I loaded the data into Tableau's Public version of their application to give a little more analysis flexibility. Here is the dashboard I created to better understand expertise:

What this shows is that organizations that are more capable of responding to tough information presentation challenges have a substantially higher ration of "Tufte Clones".

And this made me wonder how skills basis might be impacting different sizes of companies:

A pretty nice linear correlation between company size and improvement trends, don't you think?


You made it to the end!

This post turned out to be much longer than I wanted it to be, but hopefully you found it interesting and learned a few things about your fellow readers and how to display different kinds of survey responses. If you have other insights you think you see, please comment below! Thanks for participating!

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 United States License. All source code is released under a BSD License unless otherwise specified.

3 comments


March 3, 2010
derek said:

Have you considered one spot matrix as an alternative to the two stacked barcharts in "where are the experts?" and "what is the expertise blend in companies?"


March 12, 2010
Amaresh said:

Great post. Really liked the style of examples and tips you report the survey results.


May 17, 2010
Rina Bongsu-Petersen said:

Very interesting and insightful. I use other text analytics software but the one you used seems to be much more appealing & easier to use. Thank you for sharing.

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Chart Selection, Art and Science

Choosing the right chart for data presentation isn't easy -- even if you do it for a living. For those with less practice, it may resembles the flash of confusion I experience when my wife asks "Which of these outfits looks best on me?"

"...uhhhhhhh, both?"

And like that answer, there isn't any safety in sitting on the fence.

Wouldn't it be nice if there was a formula for choosing the right chart? The fact that there isn't suggests it is a mix of art and science. There are plenty of examples of people who have taken a crack at this problem:

  • Andrew Abela created a diagram that categorizes chart types.
  • In Stephen Few's book Show Me the Numbers, Chapter 5 provides an overview of graph fundamentals. Bonus: I received the following Graph Selection Matrix (PDF) from Steve.
  • In Stephen Kosslyn's book Graph Design for the Eye and Mind, Chapter 2 is entitled "Choosing a Graph Format"
  • Sanket Nadhani shared this short tutorial which tackles the basic choices.
  • From NC State, a flow diagram  for chart selection
  • An Oracle-financed white paper entitled: "Selecting the Best Graph Based on Data, Tasks, and User Roles" (PDF)
  • BonaVista Systems has an Excel add-in for choosing the right chart.

(If you know of any others, put them in the comments and I'll add to this list.)

While these are all great resources, I thought it could be instructive to walk through a sample chart selection process, starting simple then gradually adding more complex requirements. The focus of this post is on 'wireframing' the correct presentation techniques; in a follow-up we'll replicate these same charts noting best practices with refined aesthetics and layout.

I typically ask four questions in choosing how to present data:

1. What data is important to show? Specifically, which dimensions and metrics need to be shown at the same time.

2. What do I want to emphasize in the data? For example, do I want to compare different values, show relationships, or present changes over time? What story am I trying to tell?

3. What options do I have for displaying this data? Your Excel chart menu is a start, but don't forget options such as tables, sparklines, small multiples, and advanced visualizations like treemaps. Many Eyes' list of visualizations can spark additional ideas.

4. Which option is most effective at communicating the data? Which chart or visualization emphasizes what's important in the most direct and readable way?


Imagine a sales organization where two metrics matter most: activity (as measured by call volume) and sales (as measured by dollars sold). The simplest place to start with this data is to present aggregate performance for those two measures. Even with this most basic situation, you have a few options:

Step 1, All Options

Conclusion:Data doesn't always need visualizing. The common and dreadful example of this mistake is when people use a speedometer-style gauge to show a single number (option 3). It is a lot of work, pixels, and distraction for no user value. In this example, we have just a single data point for each measure and no comparisons (e.g. to goals, to last year's performance, the values against each other), so it's best to keep things clean with option 1.


Next, let's look at options for showing activity and sales data by product. In this case, the emphasis should be on the relative performance of each product.

Step 2, Option 1 Step 2, Option 2 Conclusion: Option 1 is the winner. We prefer a vertical layout of labels (bar chart) to a horizontal (i.e. column chart - not shown) because the labels are more readable and the horizontal layout can suggests a time element in the graph. As has been thoroughly documented, a pie chart doesn't allow you to see differences in values as effectively as a bar chart.


What if we wanted to understand these two metrics by time?

Time needs to be displayed horizontally. We've seen ambitious examples from Trend.ly and Axiis that attempt to break this mold, but they more often confuse than enlighten.

Step 3, Option 1 Step 3, Option 2 Step 3, Option 3 Conclusion:I've backed away from using dual axis charts after experiencing too many situations where people are confused by which line goes with which axis, no matter how clearly labeled. Because the emphasis for the data needs to be the trend over time, I would recommend option 2 over option 3's sparklines.


Now it gets interesting: What if we wanted to understand these two metrics by product and by time?

Step 4, Option 1 Step 4, Option 2 Step 4, Option 3

Conclusion: The best option for this case depends on the importance of clearly communicating the detailed trend for each product. In most cases, the "essence" of the trend is good enough, i.e. Is the trend up? Down? Erratic? Smooth? Under that assumption, option 3 provides a nice comparison of the relative product performance and trend.


A few final observations:

  • Labeling matters. How labels are laid out in a chart can be a big difference in readability. It is almost always better if the label text can be written horizontally and be closely tied to the value (rather than in a disconnected legend).
  • Multiple areas of emphasis. There will be compromises when you need to emphasize two things simultaneously (trend, relative values). Pick which one matters most.
  • Know your options. the more types of charts you know of and understand how to apply, the better set of options you'll be able to come up with.
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 United States License. All source code is released under a BSD License unless otherwise specified.

12 comments | Show all comments only the last 5 are shown


February 18, 2010
James said:

Zach's response to Hadley interests me. Is there a difference between analysis and reporting? And if so, wouldn't the term analytics refer to analysis?


February 18, 2010
Zach said:

James, I'm glad you asked. My view is that analytics covers the full spectrum of reporting to analysis, where those terms are explained as follows: Reporting is used to track and evaluate the performance of an understood process. Analysis helps develop an understanding of new processes, erratic and shifting behaviors. See this blog post: http://www.juiceanalytics.com/writing/business-intelligence-isnt-a-technical-problem/ In large part, the difference is based on flexibility and repeatability. Analysis is about being able to rapidly iterate on views of data to explore and find answers (what Hadley was looking for). For reporting, it is more critical to find and stick to particular views of the data.


February 22, 2010
Jen said:

Sorry for a silly comment on another seriously great post, but ... someone seems like an Archie McPhee fan! ;D


February 24, 2010
Dr House said:

for the dual axis option using a bar graph and a line graph for the secondary axis works well instead of using to line graphs. It's still not effortless to figure out which graph is for which axis but it's much easier to see a trend in the relationship between the two metrics.


March 24, 2010
John B said:

I know this post is rather old, but here is a tip that i use on dual axis line charts. Change the font color of the axis values to the color of the line in the chart, I never have a problem anymore with people wondering which axis which line belongs to.

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