{"id":867,"date":"2019-12-23T11:32:00","date_gmt":"2019-12-23T16:32:00","guid":{"rendered":"https:\/\/treehousetechgroup.com\/?p=867"},"modified":"2021-05-20T11:07:34","modified_gmt":"2021-05-20T15:07:34","slug":"using-different-types-of-data-visualization-to-tell-a-story","status":"publish","type":"post","link":"https:\/\/treehousetechgroup.com\/using-different-types-of-data-visualization-to-tell-a-story\/","title":{"rendered":"Using Different Types of Data Visualization to Tell a Story"},"content":{"rendered":"\n

There are many data visualization types that can be used to tell your company’s data story. Storytelling is now recognized as a powerful way to communicate in the business world. In the course of their work, business people turn to expert trainers, workshops, and books to learn how to use the power of storytelling.  <\/p>\n\n\n\n

Why is storytelling so powerful? As humans, we are different from other species in the way that we try to make meaning of events. Stories are created to narrate events in a way that helps us see a larger meaning in them. That’s why we remember stories even though we have difficulty remembering facts, dates, etc. We love to share stories so that we can share the meaning that we received from them to others. Most stories are about difficulties that need to be overcome,  heroic deeds and the courage to face those challenges, and finally a resolution — hopefully one that is happy.<\/p>\n\n\n\n

When applying storytelling to business, the objective is often persuasion. We can structure our communication or pitch along the lines of a story. Let’s look at what makes up a story that is persuasive in a business environment.  How can various types of data visualization help to create that story or bring it to life? <\/p>\n\n\n\n

When visualizations and dashboards are strung together into a narrative arc they provide the audience a series of thoughts that can be followed in a clear and compelling way — sometimes called a data story. <\/strong>These data stories can be used across all industries and are particularly effective for discussing data analytics for strategic decisions, conference presentations,  sales meetings and more. <\/p>\n\n\n\n

What\u2019s the difference between a data visualization and a story?<\/strong><\/p>\n\n\n\n

A data visualization helps viewers to explore data but does not present a specific point of view.  On the other hand, a data story is used when the researcher has already found certain patterns that she would like to highlight to the audience.  She now uses a sequence of data visualizations in order to lead viewers through a tour of the data, with a view of reaching a specific destination.  <\/p>\n\n\n\n

How data visualizations tell a story that helps a retail chain make data-driven decisions<\/strong><\/p>\n\n\n\n

Let’s consider an example of a retail chain looking to add more services at each retail outlet based on customer needs.  The company conducts a customer survey which shows the socio-economic distribution of the residential areas where different outlets are located,  buyer behavior at various outlets, and additional services desired based on location and socio-economic factors.  When the research team needs to present this study to stakeholders and decision-makers, storytelling can help everybody see trends, share reasoning, and arrive at a consensus.  <\/p>\n\n\n\n

The first visualization in the story could show the location of different outlets on a map along with the income distribution as a histogram. The outlets plotted on a map based on geolocation could be grouped into different income strata and color-coded accordingly. In this way, the presenter has set the stage for the data story by helping all stakeholders to see locations and socio-economic data. <\/p>\n\n\n\n

In the next visualization, she could show the average purchase value for each income band at each location. This can lead to discussions, such as why buyers of a certain income profile are spending more at certain locations and less at others.  How can the outlet where they are currently spending less better serve those buyers? Which locations and which income profiles are the most valuable for the company? What differentiated strategies are required based on socio-economic groups?<\/p>\n\n\n\n

Next, we have the consumer responses to a survey where respondents have been asked what additional services they would like to have at the outlets. These responses, seen by location and income bands — and in light of previous discussions about spending habits — provide a range of insights. Which additional services are needed by consumers who are already spending the most at our outlets? Or which additional services may motivate low spending consumers to shop more with us? Are certain services required more in certain locations? For example, we may find that buyers from a particular locality say they need an ATM machine at an outlet because there isn’t one conveniently available in their neighborhood.<\/p>\n\n\n\n

This data story, made up of a sequence of visualizations, is extremely valuable for decision-makers to discuss which new services added at what locations will help add the most revenues. More importantly,  this data story can prevent the company from investing in facilities and services that will not be perceived as valuable by consumers and will not generate optimum returns. Various types of data visualization such as heat maps, scatter plots, bubble charts, histograms and pie charts can be used to bring out each aspect of this story.<\/p>\n\n\n\n

How to use storytelling with data visualizations<\/strong><\/p>\n\n\n\n

You can apply the power of storytelling in data visualizations with the right planning, techniques, tools, and structure. Start by considering in what situations storytelling with data visualizations will serve you best. Consider your audience; are they senior executives who are more likely to look at the bigger picture or are they managers focused on detail and practical aspects? Once you have considered these aspects you can move on to storytelling using the following structure and elements:<\/p>\n\n\n\n