Storytelling With Data

I don’t know how to handle this Marketing question and need guidance.

visually telling a story with data can help your audience understand your message and be a powerful tool.

For the purpose of this project, pretend you are a marketing analyst consultant and your client is an ecommerce website that sells sells unique all-occasion gifts. The client wants to make sure it understands their data. They are relying on you to help understand their data to inform their decision making. They’ve asked you to have a look at their sales history and provide some insights.

  • Step 1: Have a look over the data and decide on a question or questions to explore. Here are a few options you may consider:
    • What product or products sold the best?
    • What product or products might they want to discontinue selling?
    • Was there any data that suggested seasonality?
  • Step 2: Using the Ecommerce data set provided below, explore the data in Excel or Google Sheets, and create a visual story using a graph that answers the question(s) you’ve selected to answer.
  • Step 3: Take a screenshot of your graph and any supporting information that is part of your story and submit your Story as a PDF.

Ecommerce data set:…

Here is an example of a story using the data set:

“If you are like me, you find yourself spending a lot of time looking for your TV remote. You might be surprised to find that the most likely place to find your remote is… Your Hand!

“If you remote is not in your hand, the next place to check is In or Under the Couch.”

“And a close third place to look is Next to the TV.”

If you still can’t find your remote, have a look in the Fridge, in Your Shirt Pocket, or Under the Rug.

Telling stories with data follows these steps:

  1. Start with a Question
  2. Repetition is a Good Thing
  3. Highlight the Answer
  4. Call Your Audience To Action Before you start diving into the data and creating your story here are few things to keep in mind:

Visuals can be bad if they:

  1. Don’t convey the message.
  2. Are misleading. This seems straightforward, but often visuals are created that do one or both of these unintentionally.

Data-ink Ratio:

The data-ink ratio, credited to Edward Tufte, is directly related to the idea of chart junk. The more of the ink in your visual that is related to conveying the message in the data, the better.

Color can both help and hurt a data visualization. Three tips for using color effectively.

  1. Before adding color to a visualization, start with black and white.
  2. When using color, use less intense colors – not all the colors of the rainbow, which is the default in many software applications.
  3. Color for communication. Use color to highlight your message and separate groups of interest. Don’t add color just to have color in your visualization.


– The visualization centers on a specific, clear finding in the data.

– The selected finding is clearly communicated. Design choices foster communication between the reader and the visualization.
Visualization does not add additional colors, shapes, or other design elements in an unnecessary way. Rather, each additional element should add to the insight being made.

– Color choices must accurately reflect the data and be chosen with accessibility in mind. For example, values that span from negative to positive numbers should be encoded with a diverging palette. Also, the color palettes should work for colorblindness.