MakeOverMonday: Nintendo Switch #45

Paridhi Yadav
8 min readNov 13, 2020

MakeOverMonday is a weekly event hosted by Eva Murray and Andy Kriebel to invite a community of people who are interested in data and its visualizations. Each week (current being week #45) a data viz is selected which is critiqued, analyzed, and redesigned by people all over the globe.

Check them out here: https://www.makeovermonday.co.uk/

Critique

Original Visualization created by Euroland.com

The visualization aims to display the sales of software (denoted by the lines) and hardware (denoted by the bars) where the symbol and color respectively are to denote the region. The regions are classified into Japan, Europe, the Americas, and Others. However, because the symbol/colors for the same region isn’t fixed and changes (symbols in Softwares, bars in hardware), it adds to the complexity of understanding the data viz. Additionally, the color interaction between the two data sets adds to this very confusion.

For the year 2017, where the consolidated data is set in mainly Europe (or that is what it looks like), one has no way to practically figure out which software was sold (and by how much) in Europe in the respective year. To add to the misery of reading and understanding the data, the Y-axis has two different scales. So if not consciously paid attention to, one is most likely to confuse which scale to read for which data set.

The scale (Y-axis) for software and hardware has an increment of 2000 and 600 (ten thousand units) respectively. This makes it difficult to track the growth or put a finger on how many units were sold a particular year, or by how much. It would help if the number is mentioned on the data set or around it.

No rectangle has a common baseline, which is why it's practically impossible to figure out if the growth took place and if yes, then by how much. Thus, the confusion stays in the red rectangle is a standalone value (~400) or from the baseline (on the x-axis)

Additionally, both the line graph and the stacked bar graph are to be read differently by the viewer. Where bars give us the total sale for each other, the line graph can’t. Secondly, the left y-axis isn’t exactly helpful (because to calculate individual values, one has to subtract), whereas the same is not true for the right y-axis.

Visually, a heading and a subheading to give context to the viewer will add to the data viz. Also, annotate on the chart itself to give a better understanding would be helpful.

Background info/context

The Nintendo Switch is a video game console, developed by Nintendo and released worldwide in most regions on March 3, 2017. It is a hybrid console that can be used as either a home console or a portable device.

Nintendo had seen record revenues, net sales, and profits in 2009 as a result of the release of the Nintendo DS and Wii in 2004 and 2006, respectively, but in Nintendo’s subsequent years, its revenues had declined. The company had posted its first loss as a video game company in 2012 before the Wii U’s introduction that year and had had similar losses in the following years due to the console’s poor uptake.

The New York Times attributed Nintendo lowering financial forecasts in 2014 to weak hardware sales against mobile gaming. Previously, the company had been hesitant about this market, with then-president Satoru Iwata considering that they would “cease to be Nintendo” and lose their identity if they attempted to enter it.

(source: https://en.wikipedia.org/wiki/Nintendo_Switch#Background)

Proto Persona & their problems

Who do I see using this data and will be benefitted from the visualization?

  1. Nick, the marketing head [person, role] must create a region-wise analysis [problem] to better target the audience. A clear and extensive region-wise sales of Switch [solution] will help him increase the sales [impact].
  2. Felix, a professional gamer and enthusiast is interested in buying a new gaming console. A visualization of the growth of Switch in different regions and it’s analysis will help him make an informed decision.
  3. Paula, the software design team head must create software and region-wise analysis of the past sales to better the team’s design and for future updates. A report of the same will help her roll out better-targeted updates for Switch.
  4. Matthew, the hardware design team head must create hardware and region-wise analysis of the past sales to better the team’s design and plans for better hardware. A report of the same will help him take calculated decisions on what hardware to go ahead with.

Understanding the type of data

The data vis has a broad category dividing it into Software and Hardware data, and each has the following data types:

Years of sale: Quantitative (Discrete)

Number of Units Sold (in ten thousand): Quantitative (Continuous)

The region in which they are sold: Categorical (Nominal)

*Years of sale and Regions are common for both Software and Hardware sales, however, the number of units is different (the current data vis resolved this by using dual axis).

Data and Trends

The process started with cleaning and arranging data in an excel sheet. The two broad categories in the data are Hardware and Software, due to which I decided to segregate them and generate separate graphs.

Hardware Data

Graph 01: The hardware Sales (all units were in Ten Thousand) region wise.

Even though Nintendo had overall higher sales with each year, it was difficult to see the growth region-wise (due to the scale catering to total sales as well)

02: Hardware sales without the Total Sale; 03: Absolute change in Sales (calculated by Subtracting the current year with the previous year, eg. sales of 2018–2017=Absolute Change)
04: Annual Growth Rate region-wise; 05: Compound Annual Growth Rate (in %) for each region

All the regions saw a growth dip from the year 2017–18 (launch year) to 2018–19, however, regions like Japan and Others saw a higher annual growth rate than the Americas and Europe. The latter regions saw a stagnant annual growth rate in the last 2 years.

Software Data

The software sales have consistently increased for each region, which is contrasting to the hardware sales where the increase wasn’t uniform for all regions.

The software sales are also roughly 4x the hardware sales.

02: Absolute change with each passing years; 03: Growth rate (region wise) for software sales

Even though the sales have increased over years, the growth rate has decreased with each year. This decrease is most visible in the first year for ‘Others’ which had the highest sales in 2017–18, but the lowest growth rate in the consecutive year.

04: Compound annual growth rate; 05: The total CAGR and Growth rate of the software, irrespective of regions

Evaluating insights

What is it that we want to communicate and how? What trends are interesting that we might want to highlight, and what isn’t surprising and can be ignored?

  • Softwares have been consistently selling but the growth rate has lowered each year. Hardware, though with not as a consistent increase in sales as Software, has a higher growth rate in the past year.
  • Americas and ‘Other’ have the highest sales in both Software and Hardware, in 2020 both had the lowest growth rates.
  • The Software growth rate has decreased each subsequent year, but the Hardware saw a dip in 2018–19, with an increase in 2019–20 (for each region)
  • Even though ‘Other’ is the lowest consumer of Hardware and Software, their growth rate was the highest in Hardware and second highest in Software in 2020.
  • The CAGR is the highest for ‘Other’ (with lowest sale units) and lowest for the Americas (with highest sale units)
  • Japan showed the highest improvement in Growth rate from 2018–19 to 2019–20, where it improved from lowest to highest (in Software) and lowest to second highest (in Hardware)

Different ways of visualizing it

Nick, the marketing head [person, role] must create a region-wise analysis [problem] to better target the audience. A clear and extensive region-wise sales of Switch [solution] will help him increase the sales [impact].

Softwares have been consistently selling but the growth rate has lowered each year. Hardware, though with not as a consistent increase in sales as Software, has a higher growth rate in the past year.

01: Graph that shows Hardware and Software sales (or any other category that I might want to show like CAGR) alongside keeping a common y-axis (for years) and the x-axis with different scales on either side; 02: To show the difference in sales between Hardware and Software sales, keeping them on the same scale. It could be used in addition to a separate graph which would get into the details of both.

The CAGR is the highest for ‘Other’ (with lowest sale units) and lowest for the Americas (with highest sale units)

Both visualizations will need a separate map for Software. How to visualize CAGR?

Another idea, which became the final visual I decided to work on, was of simple charts displaying crucial information on a flat Nintendo switch vector.

I could then choose to show additional radial charts on the sides to help the viewer.

Shortlisted approach

The following became my shortlisted approach, which would be interactive. The cumulative hardware and software will be shown, with an option to see the region-wise details along with comparisons between the hardware and software sale rations.

Final Visualization representing cumulative sales along with individual region-wise sales.

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Paridhi Yadav

A budding Graphic Designer, 7th semester student at NID Ahmedabad.