Packaged View Plus: Presentation Analysis

In an effort to understand which visualizations and insights are most frequently included in client-facing work, I did an analysis of presentations created by the commercial team as part of a larger research initiative focused on re-shaping Quid for use by the TOHU. I examined a sample of 9 total presentations created by the commercial team for clients, taken from the repository of presentations called “Quid’s Quest for Quintessential Content." All 9 were classified as “News Narrative” because these are exclusively based on the news and blogs dataset, which is the dataset used by the most users and has the fewest data quality challenges. I wanted to make sure a mix of different industries were represented, so there are at least two each for Consumer Products (3), Tech (2), Travel (2), and Communications / PR (2). For the purpose of the analysis, I used the commercial team not as a proxy for all end users but as a proxy for an expert Quid analyst.

My goal was to see which combinations of configurations appeared most frequently at a high level, but using something like a coded spreadsheet was insufficient for these purposes because each visualization has so many configuration variables. Instead I used a data visualization system inspired by a project called "Dear Data" to code each slide in the presentations. Below you'll find an example, a full list of coded presentations and individual slides, and the coding key.

 

Example Coded Presentation

Internet of Things Narrative


This set of characters represents the slides in a News Narrative about the Internet of Things. Each of the shapes and it’s vertically stacked elements represent a single visualization. Each of these shape groups represents a single slide. So, as you can see, some slides contained multiple visualizations.

 

Coding Key

I ended up choosing this coding method because there were so many variables to encode that using a traditional method, like a spreadsheet or list, was more confusing than it was helpful. Using visual iconography allowed me to process and find patterns in robust amounts of information about multiple objects at the same time.

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Individual Presentations

Each of the following images represents a full presentation's worth of visualizations, shown in the order in which they appear in each presentation. Looking at a presentation's slides in order allowed me to understand the narrative arc of each and compare narrative arcs across presentations.

 

Aggregated Slides

Aggregated by Visualization Type


Aggregating the visualizations by type across all presentations allowed me to identify patterns in the most frequently used visualization types. (For views of the same type that appeared back-to-back within a presentation, I maintained their ordering in the aggregation and represented this relationship with a bracket. This occurred frequently enough to call it a pattern; this pattern helped me understand that often users were drawing a single point across multiple slides by changing a single configuration element from slide to slide.)

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Aggregated set of visualizations

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List of most frequently used slides

 

Key Takeaways

  • Summary slides at the beginning of the presentation. 5 presentations began with a slide that contained a bulleted list of overall takeaways or recommendations from the analysis. They varied in name— “Executive Summary,” “Key Insights and Recommendations,” “Summary”—but served the same purpose.
     
  • Multiple Quid visualizations on the same slide. 6 presentations had 1+ slides with multiple (2-3) Quid charts on the same slide to show a comparison of some kind. Of 79 total slides coded, 17 slides (21.5%) fall into this category. All but one of these slides contained multiples of the same viz type: bar charts (6), networks (6), or timelines (4)
     
  • Custom visualizations. 3 presentations had 1+ slides with text or a visualization (Excel chart, flowchart made of boxes, etc.) based on Quid data, but not using a Quid data visualization. Of 79 total slides coded, 10 slides (12.7%) fall into this category.