Every day, our community uses Raycast multiple times, to launch the app, perform actions, search, or check key information, using the app potentially a thousand times per day.
When we think about Raycast being used, you might think of it as being opened, and searching; using ⌘K; viewing a command, or using it to search with a quicklink. However, using Raycast can be considered to the granular level of simply performing a hotkey they’ve set up inside Raycast.
With the data we capture, we currently do nothing with it.
Leveraging usage analytics, we want to show users how they’ve used Raycast throughout the year, and throughout each month and showcase it in a well-presented way that can be shared on socials and beyond, with shareable media.
Your activity should be viewable in the app and on the web, with a URL to be able to share the link with others.
You should be able to share media of individual statistics, ie. Top 10 Used Commands.
Throughout the year, Raycast users will perform a wide-range of actions; open numerous commands; hit multiple hotkeys; and install various extensions. However, there’s no way to visualize this in a fun, engaging way – or at all right now.
At the end of the year, companies like Spotify have summarized a users behaviour in to groups of digestible pieces of information, with shareable media for people to post on social media and spread the word. They call it, Spotify Wrapped.
In December of each year, you can go to Spotify mobile app, desktop app, or website, and see what artists you listened to the most; the genre of music you enjoyed, compared to others; and see what songs you played more frequently than others. This is presented and consumed in a story-like way, and you can share each metric.
What this has evoked, is a beautiful way to look at an overview of the last year and how you listened to music and podcasts from January to December – comparing how your taste in music changed, or stayed the same, and your relationship with music as a whole. To some, it comes as a surprise that your most listened to song is actually a resurrected 80’s classic, despite your favourite genre actually being Grime (for example). Then, you’re more likely to share and “boast” about what you’ve listened to that year, and share with others.
In 2022, I used the Center Window Management command 1,728 times. I seriously have OCD when it comes to my windows and desktop!
From a product-perspective, the sharing mechanic allows people to post and essentially market the product by way of sharing how you’ve used the app.
The local data we have stored for each user is from the first time of installation, up until the most recent date. Despite having quite generic data, we can dive deep in to it and make it more granular – for example, a user uses the app X times in the morning, which is more times than Y in the afternoon, therefore we highlight the metric that is greater, and profile the user as a “morning person”, but then if we see most of their activity is between 6-8am, we call them an early-riser. Whereas, if their behaviour is late-afternoon, maybe they’re the time of person to wait for the caffeine to hit.
We also have Developer data, so we can see how well their extensions performed, and develoeprs can almost use the summary as a data hub/analytics. This won’t be visible to everyone, just those that have a developer account and have activity as a developer author or contributor.