My colleagues and I have written about data visualization in the past and I have more to say about it. Coming from someone who churns out several event marketing recaps in a given month, I’m always learning new data visualization techniques. My goal is to improve ease of understanding, partly due to people telling me they aren’t following what I’m saying. Event marketing data can be difficult to put on paper, especially when you’re trying to tell a concise story and have to fit several variables in a short amount of space. I’m going to share some new practices I’ve taken on to help with this.
I used to think the only way to report field staff metrics in a recap was to arrange all of the numbers in a chart and hope readers see the key findings right away. Then I had a rude awakening in one recap presentation to a client. They told me that they had no idea what to take away from the page after our presentation. I found that moving the data-heavy tables to an appendix and pulling the most important data into charts or infographics up front to be an effective approach.
Highlight The Key Factors of the Report
An example of this is in a recent spirits brand recap. I put samples distributed per hour and bottle sales per hour up front in bar charts. Then I segmented these figures by market and ranked them to show which ones were trending above or below program KPI.
The reader didn’t have to glance at the page for more than 10 seconds to see which markets were outperforming others. This is handy for readers in executive positions who may only have time to skim the recap. With this setup, I could spend more time talking about insights instead of directing the reader to where they have to look.
Format for Readability and Visualization Purposes
A technique I’ve adopted with survey data pages is a scorecard-style format. This is a relatively simple approach. For this format the top-line findings are in a chart or infographic on one part of the page, then any pertinent segmented results are in a table to the side of the page. (e.g., overall purchase intent in a chart and a separate table shows purchase intent between men and women).
This may sound like it contradicts the idea of reducing data overload, but I’ve found it’s not a problem. I like to place charts to the left and tables to the right because we read left-to-right as humans. Your first inclination is to see the aggregate survey results in the chart on the left to have a baseline. The segmented results to the right point out the key findings on the page. Aesthetically pleasing and very informative.
What do you think? Are there techniques you consider effective? Am I blowing smoke?