Recommendation System in E-commerce — Helpful or Not?

E-commerce platforms feed on our search history to provide us the most relevant recommendations. Last week, I went crazy about Detail Cosmetics’ new Powder Pout collection and Colourette’s new Easy Matte collection; This week, I realized I needed new clothes for when I get back to work in the office, so I searched for what I wanted in Lazada and now my ‘Just For You’ page looks like this:

I remember searching for an oversized polo that gives a K-style vibe, now it shows me a Korean Off Shoulder Chiffon Top and I think I like to have one.

This recommendation system not only leads consumers such as myself in finding the most relevant products I want; it also helps businesses find the perfect consumers for their products. Now, the question is: was this system helpful to me or not? In terms of finding the right products, yes. In terms of saving money, clearly a no. Oh well, it cannot hurt you if shopping is done in moderation, right?

Aside from Lazada, Netflix and Spotify also use this system. I checked my Netflix account and realized that I had been into feel-good comedy series lately. These recommendations below are proof.

This recommendation system is helpful if I am searching for a certain genre to watch. However, I am pretty sure that if I pick one from these, it will be stuck as usual in my list for several months before I get to watch it.

Moving on to my Spotify account, I am amazed of how accurate these recommendations are.

Daily Mix 1 contains songs I usually listen to when doing chores. These are upbeat songs that help boost my energy for the day. Daily Mix 2 contains songs from a completely different genre, soft pop. I listen to these when I try to rest after a long day or during road trips. I mostly listen to classical music (Daily Mix 3) when studying if I badly need help to keep my focus, A.K.A. always. Daily Mix 4 (songs from classic bands) and Daily Mix 5 and 6 (songs from musicals) are my go-to songs based on my mood regardless if I am studying, resting, or doing household chores.

I think these playlists are as accurate as I would imagine since I always use my Spotify account; I even create my own playlists from different albums to filter out the songs I do not like. Next time I play my go to albums/playlists, I will try these recommendations and see if they are better than the playlists I made.