In this final assessment, you will work individually on a data visualization exercise to put into practice principles and concepts.
Imagine you work as an analyst on the customer insights team in your organization, which has three primary products. There is a monthly update meeting where the product team reviews data related to one of the products (cycling through so each product is focused on once per quarter). Your team has a dedicated 15-minute spot on the agenda to present voice of customer data related to product of focus for the given month. This is done through the Customer Feedback Analysis slide deck, which always follows the same format: a slide each for title page, data and methodology, analysis, and findings.
As a bit of background on the customer insights-related data you track, customers rate your products on a 5-star scale. You categorize 1-3 stars as “detractors” (those not likely to recommend the product); 4 stars are “passives”; 5 stars are “promoters” (those likely to recommend the product to others). The primary metric of focus is Net Promoter Score (NPS), which is the percent of promoters minus the percent of detractors, expressed as a number (not a percent). You typically look at NPS over time and compared to your competitor set for a given product. Customers rating your products also have the option of leaving comments, which your team categorizes into themes.
The product you focus on—an app—is on the agenda this month. You’ve updated the data and have found something interesting: while NPS has generally increased over time, underlying feedback has become increasingly polarized, with both promoter and detractor populations increasing as a proportion of total over time. Analysis of customer comments indicates a theme of latency and speed concerns among detractors. You’d like to bring this to light and use it to frame a recommendation to prioritize latency improvements for the product. This seems like the perfect situation in which to employ the various lessons we’ve reviewed and practiced over the course of this book!
The graphs presented on the Analysis slide of your typical deck are shown in the data in the Lesson Materials. Study it in light of the scenario described, then complete the following steps.
STEP 1: Form your Big Idea for this situation. Remember the Big Idea should (1) articulate your point of view, (2) convey what’s at stake, and (3) be a complete sentence. Write it down. If possible, discuss it with someone else and refine. Create a pithy, repeatable phrase based on your Big Idea. Please use the Big Idea template provided in the Lesson Materials.
STEP 2: Let’s take a closer look at the data. Write a sentence or two about each graph that describes the primary takeaway.
STEP 3: Time to get sticky! Get some sticky notes. In light of the context described, the Big Idea you created in Step 1, and the takeaways you outlined in Step 2, brainstorm the pieces of content you may include in your slide deck. After you’ve spent a few minutes doing this, arrange the pieces along the narrative arc. What is the tension? What can your audience do to resolve it? Once you have developed your narrative arc, please write the parts of it down in a document.
STEP 4: It’s time to design your graphs. Download the original graphs and underlying data. You can either modify the existing visuals or create new ones. Put into practice the lessons we’ve covered on choosing appropriate visuals, decluttering, and focusing attention. Be thoughtful in your overall design. Please copy and paste the charts into the same document of your narrative arc.
STEP 5: Create the deck you will use to present using the tool of your choice. Also, outline the accompanying narrative of what you’ll say for each slide. Even better: present this deck, walking a friend or colleague through your data-driven story. Upload the slidedeck as a separate file below.
Attribution of exercice: Knaflic, Cole. Storytelling With Data: Let’s Practice! Wiley, © 2019.