Among the multiple valuable skills to possess in the modern-day world, one of the most sought-after options is the ability to visualize data. Data from everywhere surrounds us – from business statistics to consumer behavior analysis and global healthcare to financial numbers.
However, raw data, all by itself, offers agony rather than information. Here is where data storytelling comes into play: turning complicated information into a story that inspires people to act.
The desire to combine and complement numbers, visuals or pictures, and scripts in a manner that reaches the audience and influences them in some way is the foundation upon which data storytelling is built. Marketers, analysts, and business owners can emphasize the importance of data storytelling as it assists in turning ideas into firm decisions and enhancing the effectiveness of the data.
One of the best tools to aid you in the success of data storytelling is Google Data Studio, a free, user-friendly, and powerful data visualization tool. Here is a demonstration of how data storytelling can be visualized with the help of Google Data Studio.
Source: Loves Data
In this article, we’ll explore how you can utilize Google Data Studio to analyze data and tell different stories coupled with meaningful insights.
The term ‘data storytelling’ denotes the usage of data to depict a narrative. Practicing data storytelling requires the blended use of the following three elements:
While business storytellers are in an overwhelming majority, most businesses for the longest time only resort to presenting data components rather than telling data stories. It’s about forming a plot around the data so that it is not just a collection of figures in tables but helps people see the bigger picture, track developments and forecasts, and reach conclusions.
Examples of Data Storytelling:
For instance, in a National Geographic published data story, they went on to draw relevance to the number of COVID-19 deaths in the US (roughly 500,000) with a relatable data stat.
Source: Viseven
Well-prepared data stories do a lot more. The explanation coupled with the analysis will help to make vital decisions that could not be made based on numbers alone.
Data storytelling is increasingly becoming essential in the modern-day world; this is the reason why one will find several tools that assist in creating such storytelling. In this case, we explore Google Data Studio – one of the most popular tools for a number of reasons.
Google Data Studio is one of the most popular tools in this regard and its wide adoption can be attributed to several factors:
Take a look at this Google Analytics acquisition report, for instance, created using Google Data Studio.
Source: Hevo
Comparison with Other Tools:
Here is a representation of worldwide oil usage, represented using Tableau.
Source: Tableau
It is a lot more expensive than costs associated with Google Data Studio although more complicated features can be installed on Tableau. Google Data Studio, on the other hand, sounds a bit simplistic, offering excellent potential for most data visualization requirements without the premium.
Now, let’s take the first steps of setting up Google Data Studio and arranging the data you will use to tell and sell your story.
Here is a simple representation of how you can get started with Google Data Studio.
Make sure that the data you retrieve is appropriate, organized, and focused on the insights to be derived.
It is not enough to just create visuals out of data sets when it comes to developing a data story. A data story usually consists of the following elements:
To begin, make a description of the subject or the problem being addressed.
If for instance you are preparing a report and analyzing an eCommerce website performance, one of the key aspects to be considered in the introduction would be: “How do you think the recent marketing campaign impacted the sales?”.
Provide background context and information. Include pertinent data which is historical relevance or comparative industry data. This will allow the readers to draw in and locate the baseline of sorts in the data story that follows.
Get to the core of what the data suggests or what obstacles must be addressed. For example, even when user traffic is higher than average, you might observe that very few leads are actually being converted into paying customers.
This clash generates a source of conflict that will be tackled in the course of the narrative.
Suggest possible solutions, proposals, or decisions. Offer how particular actions or processes might resolve the issues raised in the conflict. That resolution should be evidenced in the data visualization that you provide, wherein the audience is simply left with clear takeaways.
One of the challenges of effective data storytelling is knowing what kind of visualization is to be presented and how it should be presented. The choice of graph or chart affects the outcome of data interpretation.
Line Charts are more suitable to display the movement of one or more factors over time, thus it would best show changes in website traffic, for instance, on a monthly interval.
Bar Charts are useful in determining the proportions of various categories within a single valuation, for instance, sales turnover by a number of regions.
Pie Charts are used to bring out proportions and distributions, for example, the percentages of revenue growth from some classes of products manufactured by the production center.
This is how one looks on Google Data Studio.
While nearing the conclusion concerning the use of visual aids, it is important to remember a simple and obvious rule: simplification, however ridiculous may this sound. Most websites have two objectives to convey and at the same time implement as much useful data as possible in the timeline.
Google Data Studio allows the use of advanced visual tools including:
Several methods can be employed to structure your data story effectively, clarifying and reinforcing your argument along the way.
Organically structure your rationale so that it flows from one reason to one opposing reason, then move on to reason two, and then back to their counter-argument. Maintain the same layout, color patterns, and data nomenclature throughout your report.
For instance, this report depicts clearly how consistency in representation can seamlessly keep users engaged.
You should exercise care and attention to this part of the data story. Your audience should not be flooded with too much information or data for no good reason. Concentrate on important conclusions.
Add text boxes and images that explain aspects of your visuals. A few words or sentences act like a thumbscrew, for instance, the importance of why the data is worth the viewer’s attention may be outlined.
Use callouts or other features to call out key points and analyze specific data (spike in traffic activity).
Know your audience and prepare your presentation accordingly. In the case of top management, stress the main insights and the key decisions. In the case of operational teams present more descriptive information and what they should do with that information.
Don’t forget to dazzle your willingness to tell a story with the data such that the way you present the story makes it easy for the people to grasp each verbal strand.
In an era where decisions are primarily driven by data, being able to tell stories with data can place you at a significant advantage. With the ability to visualize information and especially transform data into insightful information, Google Data Studio can help you make your storytelling much more impactful.
Through data visualization, you can elevate your content while steering clear of the potential of putting off your audience with dry numbers. Whether it is luxury brand marketing or impact storytelling for non-profits – the key to engaging content is to harness the power of data to show, not just tell.
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Written By: ISHAN BARMAN
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