Made For You: A Two-Week Observation of My Spotify Recommendations

I tried comparing two weeks of different musical selections. Let’s have a look at what came out of it.

Spotify’s Release Radar updates every Friday and introduces news songs from artists or genres that users frequently listen to. In this article, I’ll be showing the recommendations Spotify gave me for the past two Fridays.

Just a disclaimer: I only included the recommended songs, and not podcasts, in this article.

Below is a screenshot of the Release Radar Spotify collated for me for Friday last week.

A screenshot of Spotify’s recommended songs to me Friday last week.
A screenshot of Spotify’s recommended songs to me Friday last week.
I remember listening to a wider range of genre last week, and it definitely shows.

I love listening to Little Mix and Selena Gomez. Their songs are either boppy or sexy and, at the same time, their voices exude delicious women empowerment. Spotify nailed it in recommending those top two songs.

I’m not religious, but I enjoy listening to some Hillsong music. I don’t listen much to local music but the recommendations make sense because Savage Love had been popular in my country in the past few months. Also, in the rare chances that I listen to local songs, these are usually love ballads. Lastly, I am a Disney fan and Spotify “knows” me well enough to include a medley of Prince of Egypt songs in the list.

The next image is a screenshot of the Release Radar Spotify created for me for Friday this week.

A screenshot of Spotify’s recommended songs to me Friday this week.
A screenshot of Spotify’s recommended songs to me Friday this week.

There’s still Little Mix at the top. (I’ll never get tired of listening to them!) Interestingly, there’s this children’s song and a J-pop song added to my recommendations. It’s probably because I’ve been listening to some anime songs this week. Well, it’s mostly One Piece’s Dreamin’ On. The rest of the songs quite describe the kind of music I enjoy in general — jazzy or acoustic tunes with feel-good lyrics.

Did you find these relevant? Why do you think these were recommended to you?

Targeted marketing makes advertising/messaging relevant to me, as a consumer. Since some data about me, as the user, has been acquired and analyzed to match my preferences, companies can make recommendations customized to my tastes. As intended, the ads definitely catch my interest and make me more responsive to the offering.

It makes me feel good that companies like Spotify pay attention to the kind of content I enjoy consuming. It makes me feel important. This feeling among customers or users — if well-tended — can greatly drive the number of sales or market share of products and services upwards.

What are the differences/nuances in the messaging when the recommendation was fed to you e.g. people who liked X also liked Y, people who bought X also bought Y, people from the PH watched this, etc.

There are several characteristics of each consumer that must be taken into account when making targeted recommendations. This is where analytics really shines. Imagine creating a customer profile that summarizes that person’s shopping, watching, listening behaviors.

Given that most people continuously change their preferences through time, businesses need a sophisticated way of tracking their interests. This is not possible without data science. I believe that it is one of the best tools that companies can use to effectively reach out and communicate with their clients. There’s also a sense of community and growth whenever something new but related is being recommended.

What is your personal opinion on the relevance of the ads that was fed to you, and how these ads influenced your next action.

If I am a boxer who’s currently trying to gain more weight for my upcoming fight in the next weight category, I don’t think I’d be searching for weight loss products in my shopping app. Given my profile, I’ll ignore ads about these because to me, they’re just noise. They don’t matter to me so I’d skip through those seemingly annoying invitations to join weight loss classes.

It would be wiser for my shopping app to create recommendations based on the products I’ve been searching for since I started training to beef up. Most likely, these would be protein supplements, books on muscle-building, or maybe even some exercise equipment to help me bulk up. Why? Because clients would only pay for things they see value in, whether those values are literal or apparent. And as a boxer looking for muscular gains, I see value in products that would enhance my lifestyle.

Show me what I want, and I’ll show you money.

Shut up and take my money meme.
Shut up and take my money meme.
The ideal client every business wants. (Image source: Imgur)

If you want to see what other kinds of music I’m into, follow me on Spotify, and let’s explore more music genres!

A Linux user currently exploring the wonders of data science. Curious as a cat and sleeps like one. She’s also into skygazing, anime, and gamification.

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