Context is critical in just about every aspect of our lives. From a young age we teach children to use “context clues,” when first learning to read. When making a major purchasing decision, such as buying a car, we use the context of how many miles it has and whether it’s been in an accident to guide our choices. Context is no less important for businesses looking to leverage data visualization to guide and inform decision making. As with the examples above, context helps us understand the full significance of data and sheds clarity on information that would otherwise mean nothing. Adding context transforms data from decimals and percentages to actionable information and, ultimately, decisions that affect your organizations’ bottom line.
What Happens When Data Lacks Context?
On the surface, data is just a collection of numbers and oftentimes, complex information. Only when data is provided in context does it become relevant. Take, for example, an online search in the U.S. for the word “Pie.” If we look at the results, we see that this search spikes considerably during the month of November every year. At this point, you may be thinking to yourself, “obviously, searches for pie will surge around Thanksgiving.” However, this is where context comes into play. If you grew up in the United States, you probably know that Thanksgiving occurs in November and that pie is frequently served as part of the celebration. Therefore the increase in pie searches is directly related to individuals planning their Thanksgiving festivities. However, if you were raised outside the United States, you may lack the cultural reference to understand why pie searches in the United States surge around November and reach an entirely different conclusion (and decision) on why that spike happens.
With the proper context, choices may be made based on the data and what the data means. In our pie example, the CMO of a fictional pie producer would be armed with data on traffic behaviors (data) and topical interests connected to those habits (context). Taken as a whole, this data can support an ad campaign in which data dictates when and how to contact customers and context informs what they may find relevant and intriguing.
Visualize Data With the Big Picture
When it comes to business choices, the best and most accurate decisions result from having the correct data, which should be contextualized.
Text is instrumental to context, from naming your axes and giving color keys to using data point labels and annotations on the visualization or adding explanatory paragraphs in an article. Without these, data visualizations might be challenging to understand at best or misleading at worst.
Context allows you to accurately interpret the facts, flesh out the broader picture, emphasize key points, direct the reader to the correct inferences, and allow accurate comparisons. They can also anticipate the reader’s interest in an outlier or trend.
So, the next time you want to offer up an effective data visualization, stop and consider the following:
- Can I clarify the information I’m presenting by emphasizing or repeating a point?
- Do I need to further explain less obvious details?
- Is there an anomaly or a pattern that external data can explain?
- Most importantly, can the data help stakeholders make vital business decisions?
Context is critical because it distinguishes between a superficial presentation and genuine data understanding that motivates readers to action.
Visualization is a significant part of any data presentation, but any data presented without context loses most of its meaning. Data is more than simply a collection of numbers. People may draw insights from several sections of a data set or incorporate information from various sources to form an action plan. However, without the capacity to understand the rationale behind data, stakeholders could find it difficult to make informed insights.
If your business is looking to better understand what your data is saying, schedule a call or start your free trial of Gemini Explore today! We can help you connect the dots, tell data stories better, and get to valuable (and actionable) insights faster.