Custom Data Visualization: An Insight into Ourselves
Data, specifically our data as content consumers, is often used on social media sites to hand-feed us exactly the type of content they know we like. For example, Twitter’s “For You” section uses data like our own tweets, posts that we’ve liked or reposted, and the people we follow to create an alternative timeline with people they think we might like to follow and Tweets we might want to engage with. Instagram’s “Explore” page does something similar, and TikTok’s algorithm is based on the same concept. But when I think of visual representation of my data, my mind does not immediately go to these pages of content specifically tailored for me. When I think of a visual representation of my data, the first thing to come to mind is the yearly drop of Spotify Wrapped.
While Spotify itself is not necessarily a social media site, every year, millions of people wake up, open up the app, see a colorful animated display of graphs and charts with all the data Spotify gathered on their listening habits throughout the year, then proceed to share it with their friends and followers on various social media sites. From a marketing point of view, Spotify Wrapped is a brilliant idea; if you’re on Instagram and you’ve never heard of Wrapped before, you most certainly will know that at least a dozen of your closest friends have posted their stats on their stories. If you actively participate in the yearly craze, you know you look forward to it and often think, “Will this show up on my Spotify Wrapped?”
Spotify is not the only company that does this. One that comes to mind is Letterboxd. More popular among film fanatics, myself included, Letterboxd offers a similar “year in review” feature to those of us who pay for their service. Like Spotify, Letterboxd shows its users the hours spent watching films, likes, comments, etc. But a more in-depth collection of data is shown here as well, with graphs displaying several logged films categorized into genres, countries of origin, and language, and graphs representative of movies that were either this year’s releases or older, watches or re-watches, whether the user reviewed them or didn’t. Lists of your most watched actors (and how many films you watched them in), directors, and even crew members like production designers and cinematographers, all in one easy-to-scroll-through place.
More and more companies have started doing something similar with user data. Even JetBlue sent me an email detailing my travel stats with infographics for 2022. But I have to wonder, what about seeing our data displayed in such a way that makes us okay with all these different companies collecting it? Why do we willingly share our data with third-party apps like Receiptify throughout the year to visually represent our listening habits every month? And why do we feel so compelled to share it on social media?
In some way, seeing our data represented in easy-to-read graphs and charts makes us feel good. It makes us feel important, and it makes us feel productive.
You can look at a graph of your spending habits on an app like NerdWallet, and feel a sense of accomplishment about how much less you spent this month compared to the last. Or perhaps use your data to motivate you to do better next month. You can see the fitness tracker rings on your Apple Watch and feel good about yourself for completing your workout goals for that day. You can screenshot and share your Letterbox year in review and pat yourself on the back for having your “most obscure” film be a black-and-white Italian movie from the 60s. You can experience Spotify telling you that you’re in the top 0.001% of listeners and feel confident that…you are that artist’s biggest fan.
Visual representations of our data have become so common in the last couple of years, whether it’s an effective marketing strategy or just a helpful way to keep track of our day-to-day lives, I have no doubt that in the upcoming years, more companies will come up with more fun and effective ways to show us exactly who we are through the use of data visualization.
