Leonardo Menezes’ Post

Spotify is making it's internal experimentation tool public. That's right, it's now FREE. "It's become clear to us over the years that there's not a one-size-fits-all approach to experimentation. Needs are different, and you likely don't face the same requirements in all parts of your organization. To adopt an experimental mindset where your business evolves into an experiment-first culture, you need to set yourself up for success by being able to meet these different requirements. To make things even more challenging, your needs are going to change. This means that you shouldn't go looking for a tool that's perfect for you now. You need a tool that you can make perfect for you, and that you can grow with." https://lnkd.in/eKnxXN69

🔓 Unlocking the Secrets of Spotify's Algorithms for Artist Growth 🔓 Spotify's recent fan study reveals that most new artist discoveries stem from algorithmically programmed playlists like Discover Weekly, Release Radar as well as mixes, radio and autoplay. The study also highlights that since 2019, there's been a 62% increase in the average number of countries where artists are streamed via these playlists, indicating that a global audience is more accessible than ever Despite the significant opportunities recommender systems offer, there's a widespread lack of understanding among artists, managers, labels and distributors about how these algorithms function, how they categorise artists and their music, but most crucially, how to influence them to maximise benefits. Over the past two years, we have devoted ourselves to deciphering these complexities. Our research and testing have led to data-driven strategies that enhance artists' algorithmic health, attract new global listeners who become fans and provide teams with the confidence to boost streaming revenue with predictable ROI 📈 Now is the time to take control of your streaming potential, if you’d like to learn more, get in touch: [email protected]

One of the trends our R&I lab is tracking is "De-siloing People functions." The benefits created by cross-functional collaboration models enable us to keep pace with employee needs and deliver a more seamless, end-to-end employee experience. McKinsey CLO, Heather Stefanski, goes deeper on this topic in the latest episode of the Learning Geeks podcast. Links below to listen #learning #collaboration #HR #learning #recruitment #integration #breakingdownsilos Dana Alan Koch Bob Gerard Jake Gittleson

Have you heard about the Spotify model? There was information published about a model that Spotify used for their engineering teams that talked about mixing in horizontals effectively. It was incredibly effective and many different engineering organizations decided they'd go chase a similar pattern. Except... The information published *wasn't* that it was being used successfully! It was aspirational! While we think there are some very interesting takeaways from the model, it's a good reminder to not blindly copy+paste! ---- 👀 Check out the full video on our channel! 🗣️ Share with your network! #softwareengineering #engineeringmanager #engineeringmanagement

Have you heard about the Spotify model? There was information published about a model that Spotify used for their engineering teams that talked about mixing in horizontals effectively. It was incredibly effective and many different engineering organizations decided they'd go chase a similar pattern. Except... The information published *wasn't* that it was being used successfully! It was aspirational! While we think there are some very interesting takeaways from the model, it's a good reminder to not blindly copy+paste! ---- 👀 Check out the full video on our channel! 🗣️ Share with your network! #softwareengineering #engineeringmanager #engineeringmanagement

🎶 Breaking Insights from the Latest Spotify Fan Study! 🎶 Did you know? Spotify's mixes, radio, and autoplay features drive over a quarter of all new artist discoveries, totalling a whopping 26.3%. And that's not even counting high-profile playlists like DW and RR. With these included, algorithm-mediated discovery could be as high as 40%! As of 2024, recommender systems have become indispensable tools, helping users navigate an expansive musical landscape. However, many artists teams are still in the dark about how these algorithms view their music, who their algorithmic audience is, or why some tracks receive more algorithmic support than others. 🔍 This is where Music Tomorrow comes in. Our analytics tools empower artist teams with detailed insights into their algorithmic positioning, enabling you to craft actual data-driven optimization strategies — far removed from the myths and opaque "best practices" that claim to game the system. 🚀 Take charge of your algorithmic profile today! Go to music-tomorrow.com/seo to start making informed decisions that will help you broaden your algorithmic footprint

Lost in Backstage Updates? Let Spotify's Maintainers Be Your Guide! https://lnkd.in/dJ9bEehf Is your Backstage instance stuck in 2023? Discover how the latest updates can supercharge your developer portal! 🚀 📽️In this video, Ben Lambert and Patrik Oldsberg from Spotify reveal: ✨The new Backend System ready for production ✨Exciting Declarative Integration features ✨The Community Plugins repository for easier contributions ✨A peek at upcoming Dynamic Features Watch the video to see how these Backstage updates can become your dev team's roadmap to enhanced productivity. P.S. Already using Backstage? Share your upgrade experiences in the comments! 💬 #lowops #backstage #DeveloperPortal #PlatformEngineering #OpenSource

Have you heard about the Spotify model? There was information published about a model that Spotify used for their engineering teams that talked about mixing in horizontals effectively. It was incredibly effective and many different engineering organizations decided they'd go chase a similar pattern. Except... The information published *wasn't* that it was being used successfully! It was aspirational! While we think there are some very interesting takeaways from the model, it's a good reminder to not blindly copy+paste! ---- 👀 Check out the full video on our channel! 🗣️ Share with your network! #softwareengineering #engineeringmanager #engineeringmanagement

Have you heard about the Spotify model? There was information published about a model that Spotify used for their engineering teams that talked about mixing in horizontals effectively. It was incredibly effective and many different engineering organizations decided they'd go chase a similar pattern. Except... The information published *wasn't* that it was being used successfully! It was aspirational! While we think there are some very interesting takeaways from the model, it's a good reminder to not blindly copy+paste! ---- 👀 Check out the full video on our channel! 🗣️ Share with your network! #softwareengineering #engineeringmanager #engineeringmanagement

Have you heard about the Spotify model? There was information published about a model that Spotify used for their engineering teams that talked about mixing in horizontals effectively. It was incredibly effective and many different engineering organizations decided they'd go chase a similar pattern. Except... The information published *wasn't* that it was being used successfully! It was aspirational! While we think there are some very interesting takeaways from the model, it's a good reminder to not blindly copy+paste! ---- 👀 Check out the full video on our channel! 🗣️ Share with your network! #softwareengineering #engineeringmanager #engineeringmanagement