Mad Libbing your way to Purposeful Visualizations

Good data communication hinges on picking right chart. The patterns and insights almost magically emerge when you choose a chart or visualization that emphasizes the important elements in your data. Unfortunately, this is one of the biggest struggles for inexperienced presenters of data. I don't like to knock our own stuff, but a little healthy introspection is always a good thing. Consider our popular ChartChooser tool. In spite of it's carefully crafted name (it was core of an ad campaign akin to peanut butter: Choosy chart choosers choose ChartChooser -- no, not really), we've come to believe that ChartChooser isn't so useful for the "Chooser" part; it is useful because the "Chart" part is nicely formatted, downloadable PowerPoint and Excel charts.

Here are the filtering choices for ChartChooser:


I've been at this a while and I still don't always know how to connect what I'm trying to express with words as vague and broad as 'Composition' or 'Relationship'.

It isn't entirely ChartChooser's fault. Basic chart types are by nature broad and flexible in their usage. How can we make it easier for someone to make that leap from their question to a visualization that best answers it?

We believe one part of the solution is to make visualizations more purposeful. That is, create re-usable ways of expressing data that are carefully designed to answer common questions that people pose about their data.

While it's true that everyone's data is unique, what we've learned is that in most cases, the things they want to know about their data aren't so unique. The same sets of question patterns show up time after time. It's almost like a game of Mad Libs:

  • Which are my top performing _plural noun_?
  • Which _plural noun_ are the most significant outliers when measured by _ measure_ and _ measure_?
  • Which _plural noun_ have improved or declined the most over the last _time period_?
  • How does _singular noun_ compare to _singular noun_ across my important performance measures?

Our goal is to draw straight, obvious lines between questions like these and a visualization that directly and simply expresses an answer.

If you consider the last data Mad Lib question above, our match-up visualization is a good example: compare two things side by side to see relative performance. The Match-up was inspired by the traditional tale-of-the-tape graphics that you used to see in boxing matches.


Like a lot of our visualizations in Slice, we've added a number of key features that really help the user quickly understand and explore the data. Here are a couple examples:


We've put together a whole collection of these purposeful visualizations, such as a funnel visualization for sales conversions and other processes; a leaderboard for ranking top items across a bunch of measures (try it free here), and a comments visualization for reviewing and exploring survey verbatims, tweets, and other descriptions. And we'll be making more. What questions do you ask of your data?

Slice is data presentation for the rest of us


Ok, we're gonna take an informal survey. Raise your hand if you've ever experienced this:

You’re sitting through yet another dull, data-heavy presentation packed full of repetitive charts. A question gets raised, and the presenter flips furiously to find a relevant chart on page 53. A colleague squints at a dense table of numbers, wondering what it all means.

We've all been there. And oh! how painful. Too many times we've seen the aftermath of the indiscriminate boardroom presentation bore-athons. Well, it's time to make it stop!

As a result, we at Juice challenged ourselves to find a way for ordinary business folks to create engaging, interactive presentations that leave the dreary days of Death by PowerPoint behind and bring new life to the data-presentation experience. Our solution is called Slice.

Slice reporting solution
Slice reporting solution

Over the last year we’ve worked with dozens of organizations to refine and enhance how Slice works. Our customers come from a diverse array of industries, from research organizations to healthcare service providers to advertising agencies.

Here's what we learned. There are many great data analysis tools out there like Tableau for ad hoc analysis, SAS and R for statisticians, and a myriad of others. However, we've heard repeatedly from real users that these tools fall flat on helping people become data presenters.

Slice solves that data presentation problem.

Once you've done the analysis and you know what to communicate, packaging the results in the proper way is critical. But, to do it right

  • You want the design to be striking, but you're not a designer;
  • You want engaging interactivity, but you're not a developer and the IT wait list is overflowing;
  • You might cobble something together using Excel and PowerPoint, but mediocrity is not what you're looking for.

Slice removes these constraints by focussing on the last mile of business intelligence: presenting data with the visual precision, interactivity and excellence in a way that sparks engagement.

We are really excited about how Slice makes a difference for people who have struggled too long with delivering data-rich presentations or reports. Interested in seeing the advantage Slice can give you? We've just released a new version and we’d be happy to set you up with a 30-day trial. Go to our Slice page, fill out the form, and we'll be in touch.