Spotify Recommendations (Spotify AI) - Detailed Review
Media Tools
Spotify Recommendations (Spotify AI) - Product Overview
Spotify Recommendations
Spotify Recommendations, driven by Spotify’s AI, is a sophisticated feature within the media tools category that significantly enhances the user experience on the platform.Primary Function
The primary function of Spotify Recommendations is to provide users with personalized song and podcast suggestions based on their listening habits, preferences, and patterns. This feature aims to connect users with content they are likely to enjoy while also helping them discover new music and podcasts.Target Audience
The target audience for Spotify Recommendations includes all Spotify users, but it is particularly beneficial for premium users who have access to more advanced features. However, some AI functionalities are occasionally available to all users, regardless of their subscription status.Key Features
Personalized Playlists and Song Recommendations
Spotify’s AI generates personalized playlists and song recommendations using a combination of content-based and collaborative filtering algorithms. These algorithms analyze users’ listening history, preferences, and the characteristics of the content itself, such as genre and release date, to suggest tracks that fit the user’s taste profile.Enhance Feature
The “Enhance” feature allows users to easily add personalized recommendations to their playlists. Users can toggle this feature on and off, and it integrates suggested songs into the playlist, with one recommendation after every two tracks, up to a maximum of 30 recommendations.AI DJ
Spotify’s AI DJ feature uses AI technology to curate playlists in real-time based on users’ listening habits, providing a continuous and personalized listening experience.Voice AI
The voice AI feature enables users to interact with the app using voice commands, allowing them to play specific songs, podcasts, or access other content with ease.Algorithmic Recommendations
Spotify’s algorithms consider various inputs, including user actions like searching, listening, skipping, or saving tracks, as well as trends and the general tastes and behaviors of other users. This ensures that recommendations are relevant, unique, and specific to each user.Generative AI
Spotify also uses generative AI for innovative content creation, such as unique ad formats, personalized playlists, and even generating AI-assisted music and podcast content in partnership with entities like OpenAI. By leveraging these features, Spotify Recommendations ensures that users have a tailored and engaging listening experience, making it easier to discover new content and enjoy their favorite tracks. Spotify Recommendations (Spotify AI) - User Interface and Experience
User Interface and Experience of Spotify’s AI-Driven Recommendations
The user interface and experience of Spotify’s AI-driven recommendations are crafted to be intuitive, personalized, and engaging. Here are some key aspects that highlight its ease of use and overall user experience:
Personalized Recommendations
Spotify’s AI algorithms analyze a wide range of data points, including a user’s listening history, favorite genres, mood, and external factors like weather and time of day. This data is used to curate personalized playlists such as Discover Weekly, Release Radar, and Daily Mix, which are seamlessly integrated into the user interface. These playlists are updated regularly to reflect the user’s evolving musical preferences.
Intuitive Design
The app features a consistent design language that makes it easy for users to navigate. For example, artists are displayed in circular frames, while albums and songs are in square frames, allowing users to quickly distinguish between different types of content. This consistency helps users make decisions intuitively, enhancing the overall user experience.
User Feedback and Adaptation
Spotify’s AI system continuously learns from user interactions. It considers both explicit feedback (such as saving tracks, adding to playlists, and skipping songs) and implicit feedback (like listening session length and repeat listens). This feedback is used to refine recommendations, ensuring that the system adapts to the user’s preferences over time.
Contextual Recommendations
The AI takes into account the context in which users listen to music. For instance, it suggests upbeat songs in the morning and calming tracks in the evening. This contextual approach enhances the user experience by providing music that is relevant to the user’s current situation.
Human Curation
While AI drives the recommendation system, human music curators play a crucial role in adding a touch of serendipity. They curate playlists, identify emerging artists, and ensure that recommendations reflect the diverse tastes and preferences of Spotify’s global user base. This blend of AI and human expertise enriches the musical experience and introduces users to unexpected gems they might not have discovered otherwise.
Engagement Features
Spotify’s annual “Wrapped” playlist is a standout feature that personalizes the user experience. It provides a Year in Review for users, reflecting their musical journey throughout the year. This feature encourages users to share their personalized playlists on social media, transforming data harvesting into an enjoyable and informative experience.
Seamless User Experience
The integration of AI-powered algorithms with the app’s design ensures a seamless and intuitive experience. Users can easily find and enjoy their favorite music, and the app continuously optimizes its functionality based on user behavior and feedback. This results in higher user engagement and satisfaction, as users feel that Spotify understands and caters to their musical tastes.
Overall, Spotify’s user interface is designed to be user-friendly, with a focus on delivering personalized and contextual recommendations that enhance the music listening experience. The combination of AI-driven algorithms and human curation ensures that users have a rich, engaging, and satisfying experience on the platform.
Spotify Recommendations (Spotify AI) - Key Features and Functionality
Spotify’s AI-Driven Recommendations
Spotify’s AI-driven recommendations are a cornerstone of its music streaming service, offering several key features that enhance the user experience through advanced machine learning and artificial intelligence.
Personalized Playlists: Discover Weekly
One of the most popular features is Discover Weekly, launched in 2015. This playlist uses AI algorithms to recommend new music based on a user’s listening history. It gathers data on the music you play, skip, save, and how long you listen to it. The AI then employs collaborative filtering to compare your choices with those of similar users and content-based filtering to analyze the musical properties of songs, such as genre, tempo, and mood. This combination helps introduce users to new artists and songs that align with their tastes.
AI DJ
Introduced in February 2023, the AI DJ is a personalized AI guide that selects music based on each user’s specific likes and listening patterns. This feature combines Spotify’s personalization technology, generative AI, and a dynamic AI voice. The AI DJ creates a playlist interspersed with comments and background information about the tunes and artists, using OpenAI technology to provide culturally relevant natural-language comments. This feature constantly refreshes the lineup based on user feedback, ensuring a dynamic and engaging listening experience.
AI Playlist Function
Debuted in beta for Premium members in April 2024, the AI Playlist function allows users to create playlists using written descriptions, emoticons, or abstract notions. This technology, driven by enormous language models and Spotify’s vast music collection, examines the user’s listening history, global patterns, and the semantic meaning of the prompt. Users can modify the playlist by providing input, which helps the AI learn and improve its suggestions. This feature enables users to generate playlists that match various moods, activities, or topics.
Collaborative and Content-Based Filtering
Spotify AI employs two main types of filtering to refine recommendations:
- Collaborative Filtering: This compares your listening habits to those of other users with similar tastes, recommending songs enjoyed by these users that you haven’t heard yet.
- Content-Based Filtering: This analyzes the actual musical properties of songs, such as genre, tempo, instrumentation, and mood, to recommend similar songs based on the characteristics of the music you like.
Daylist and Other Personalized Features
Spotify also uses AI to improve its array of recommendation features, including Daylist, Blend, and Made for You Mixes. The Daylist function, for example, helps balance familiarity and originality in suggestions by understanding user preferences across multiple circumstances and moods throughout the day. This ensures that users get a mix of familiar and new music tailored to their current mood or activity.
Customization and User Interaction
Users have the power to fine-tune their listening experience by adjusting various settings and preferences. For instance, you can tweak your preferences to favor new releases or use mood filters to find the perfect emotional soundtrack. The AI also allows for a collaborative effort between the user and the algorithm, enabling users to create a playlist of their favorite songs and let the AI suggest similar tracks to expand their collection.
Benefits for Users and Artists
Spotify AI enhances music discovery by constantly suggesting fresh tunes that users might not have found otherwise. It breaks down genre barriers by identifying subtle connections between different styles, promoting a greater appreciation for musical diversity. For artists, AI-driven playlists offer significant exposure opportunities, allowing emerging talents to reach new audiences alongside established acts.
Conclusion
In summary, Spotify’s AI recommendations are built on a sophisticated network of machine learning algorithms that analyze user data, employ various filtering techniques, and integrate with user input to provide a highly personalized and engaging music experience.
Spotify Recommendations (Spotify AI) - Performance and Accuracy
Spotify’s AI-Driven Recommendation System
Spotify’s AI-driven recommendation system is renowned for its performance and accuracy in personalizing music and podcast recommendations for its vast user base. Here are some key aspects of its performance and any identified limitations:
Layered Algorithm Approach
Spotify’s recommendation engine relies on a multi-layered approach, combining collaborative filtering, content-based filtering, and reinforcement learning. Collaborative filtering analyzes user listening behavior to identify patterns and similarities, creating “music maps” that cluster songs based on how often they are played together.
Content-Based Filtering
Content-based filtering adds depth by analyzing metadata, performing raw audio analysis, and considering cultural context. This includes metrics like danceability, loudness, and lyrics to capture the sonic characteristics and cultural insights of each track. This layer helps recommend songs with similar attributes, even if they are not commonly paired by other users.
Reinforcement Learning
Reinforcement learning is the newest and increasingly important layer, enabling the recommendation engine to learn and improve based on user feedback. This model optimizes recommendations to increase user engagement, such as likes, saves, and overall time spent on the platform.
Performance and Accuracy
The combination of these layers results in highly accurate and personalized recommendations. For example, features like “Discover Weekly” and “Spotify Wrapped” are highly praised for their ability to surface music and podcasts that align closely with individual user preferences.
AI-Powered Features
Spotify’s AI DJ is another notable feature that curates music based on real-time user feedback, using a hyper-realistic voice generated by generative AI. This feature adjusts the playlist dynamically based on user interactions, ensuring a continuous and engaging listening experience.
Limitations and Areas for Improvement
- Algorithmic Bias: Content-based filtering can reinforce existing musical and cultural biases, creating a feedback loop. This can limit the discovery of new and diverse music.
- Cold Start Problem: New artists often lack sufficient data, which can make it difficult for the algorithm to recommend their music accurately. Here, human curators play a crucial role in identifying and promoting new music.
- Contextual Limitations: While collaborative filtering is powerful, it can sometimes fail to account for contextual preferences. For instance, a song might be paired with holiday music due to seasonal listening patterns, even if it doesn’t match an individual’s preferences.
Engagement and Factual Accuracy
Spotify’s AI-driven recommendations are highly engaging, as they are based on a comprehensive analysis of user behavior and preferences. The system captures all aspects of user interaction, from the songs they like and skip to the time of day they listen, ensuring that the recommendations are both accurate and relevant.
In summary, Spotify’s AI recommendation system is highly effective in providing personalized and engaging music experiences. However, it faces challenges related to algorithmic bias and the cold start problem, which are mitigated through the involvement of human curators and continuous improvements in the algorithmic models.
Spotify Recommendations (Spotify AI) - Pricing and Plans
Current Premium Plans
Spotify’s existing Premium plans vary in price and features:
- Premium Individual: $11.99 per month, offering ad-free music, offline listening, playing songs in any order, high audio quality, and other features.
- Premium Duo: $16.99 per month, similar to the Individual plan but for two accounts.
- Premium Family: $19.99 per month, covering up to six accounts with additional features like family-friendly content and parental controls.
- Premium Student: $5.99 per month, available for students at accredited higher education institutions, including access to Hulu (With Ads).
Rumored Supremium Tier
There is a rumored new tier called “Supremium” that may be introduced:
- Supremium: Potentially priced at $19.99 per month, this tier is expected to offer 24-bit Lossless music and AI playlist creation capabilities. However, this tier has not been officially announced by Spotify yet.
AI Features in Current Plans
Spotify already uses AI in various features available to its Premium subscribers:
- AI DJ: An AI-powered disc jockey that curates personalized music based on user preferences and listening behavior. This feature is part of the current Premium offering.
- Discover Weekly and Other Recommendations: AI models use user data to predict and recommend music, podcasts, and other content. These features are included in the current Premium plans.
Free Options
For those who do not have a Premium subscription, there are alternative ways to generate AI playlists:
- Using ChatGPT with a plugin, users can create personalized playlists based on their preferences without a Spotify Premium subscription. This method involves installing a ChatGPT plugin and interacting with the AI to generate playlist recommendations.
Summary
In summary, while the current Premium plans offer various AI-driven features like AI DJ and personalized recommendations, the rumored Supremium tier could introduce additional features like Lossless music and enhanced AI playlist creation, but at a higher price point. For non-Premium users, using external tools like ChatGPT with plugins can provide similar AI-driven playlist generation capabilities.
Spotify Recommendations (Spotify AI) - Integration and Compatibility
Integration with Other Tools
Spotify’s AI recommendations can be integrated with other tools and services using platforms like Latenode. This integration allows users to create custom workflows that combine Spotify with AI models like ChatGPT or its alternatives. For example, you can automate playlist creation based on AI-generated suggestions, enhance music discovery through interactive bots, or create dynamic playlists that reflect user moods or conversation themes. Spotify’s API also enables developers to access its extensive music library, allowing for the creation of applications that interact with user accounts, playlists, and music recommendations. This integration can be achieved through no-code platforms, making it accessible to both developers and non-technical users.Compatibility Across Devices
Spotify is highly compatible across various devices and platforms. Here are some of the supported devices and systems:Mobile Devices
Spotify supports iOS 15 or above and Android OS 7.0 or above. Users can download the app for both smartphones and tablets.Desktop
The app is available for Mac (OS X 11.0 or above) and Windows (Windows 10 64-bit, Windows 11 or above).Web Player
Users can access Spotify through web browsers like Chrome, Firefox, Edge, Opera, and Safari.Other Devices
Spotify is also available on cars, TVs, gaming consoles, smart watches, and more, often through wireless connections such as Spotify Connect, Bluetooth, Apple AirPlay, Chromecast, Alexa, and Google Assistant.AI-Driven Features
Spotify’s AI models play a crucial role in enhancing user engagement. Here are a few notable features:AI DJ
This feature uses generative AI to curate tracks based on user listening behavior and provides a hyper-realistic voice narration. Users can interact with AI DJ in real-time to change the music selection.Discover Weekly and Other Recommendations
Spotify’s AI models analyze user behavior, including what they listen to, how long they listen, and their playlist creations, to predict and recommend music, podcasts, and other content.AI Playlist
This beta feature, available to Premium users in several countries, combines Spotify’s personalization technology with generative AI to create playlists based on user prompts. Users can input specific ideas or moods, and the AI will curate a personalized playlist.Troubleshooting and Support
For any issues with integrations or device compatibility, users can check the network connection, ensure necessary permissions are granted, and review the documentation provided by the integration platform. Additionally, support from the platform, such as Latenode, is available for more complex issues. In summary, Spotify’s AI-driven recommendations and features are highly integrable with other tools and services, and the platform is compatible with a wide range of devices, making it a versatile and user-friendly music service. Spotify Recommendations (Spotify AI) - Customer Support and Resources
Customer Support Options
Messaging Support
Spotify does not offer phone support, but you can send a message to their customer service experts through their support page. This is a direct way to get help with any issues you might be facing.
Spotify Community
The Spotify Community is a forum where users can post questions, share ideas, and get help from other listeners. The most knowledgeable members are called “Stars,” and you can also reach out to them via Twitter @AskSpotifyStars.
Facebook Support
You can send a direct message to Spotify’s Facebook page, SpotifyCares, for assistance.
Additional Resources
Help Center
Spotify has a comprehensive help center that includes articles and guides on managing your account, payment, and privacy settings. It also covers topics related to using the app and troubleshooting common issues.
Spotify for Artists
For artists, there is a dedicated help center that provides information on managing artist profiles, uploading music, and other related topics.
AI-Driven Features Support
While the AI-driven features such as AI Playlist, AI DJ, and personalized recommendations do not have specific support channels, any issues or feedback related to these features can be addressed through the general support options mentioned above.
Personalized Recommendations
If you have feedback or want to influence your recommendations, you can use the app’s features to give feedback on what shows up in your recommendations. You can also organize and filter your recommendations based on your preferences.
Overall, Spotify’s support system is geared towards providing help through various channels, ensuring that users can get the assistance they need efficiently.
Spotify Recommendations (Spotify AI) - Pros and Cons
Advantages of Spotify Recommendations (Spotify AI)
Spotify’s recommendation system, driven by AI, offers several significant advantages that enhance the user experience and foster a vibrant music ecosystem.Personalization
Spotify’s AI algorithms create highly personalized music recommendations by analyzing user behavior, including listening history, preferences, and even skips. This personalization increases user satisfaction by introducing listeners to new tracks and artists they are likely to enjoy.Discovery of New Music
The system supports the discovery of niche genres and up-and-coming musicians. By using collaborative filtering, content-based filtering, and advanced audio models, Spotify can recommend songs that might not be commonly paired together by other users, thus expanding the user’s musical horizons.Comprehensive Data Analysis
Spotify’s recommendation engine integrates various data filtering techniques, including collaborative filtering, content-based filtering, and advanced audio analysis. This comprehensive approach ensures that recommendations are accurate and aligned with the user’s musical preferences. For example, the audio model breaks down music into components like tempo, pitch, and timbre to capture subtle nuances.Real-Time Learning and Adaptation
The system continuously learns from user interactions in real-time, allowing recommendations to evolve with the user’s taste. This dynamic learning process ensures that the recommendations remain relevant and engaging over time.Cultural and Emotional Nuances
Natural language processing (NLP) plays a critical role in capturing cultural and emotional nuances, improving the accuracy and personalization of recommendations. This helps in suggesting music that resonates deeply with individual users.Editorial Curation
In addition to algorithmic recommendations, Spotify also employs editorial curation by music experts who use data insights and cultural knowledge to recommend content. This blend of human and AI-driven curation enhances the overall user experience.Disadvantages of Spotify Recommendations (Spotify AI)
Despite its many advantages, Spotify’s recommendation system also has some drawbacks.Overemphasis on Popular Artists
Spotify’s AI tends to prioritize popular and trending artists, which can sometimes limit the discovery of lesser-known or niche artists. This can result in recommendations that are less diverse and more focused on mainstream hits.Repetitive Recommendations
Some users have reported experiencing repetitive recommendations, where the same songs are suggested repeatedly despite user feedback indicating dislike. This can be frustrating and may not fully reflect the user’s evolving tastes.Limited Response to User Feedback
There have been instances where the algorithm does not adequately respond to user feedback, such as skipping songs or marking them as “do not play again.” This can lead to a less satisfying user experience if the algorithm does not adapt quickly enough to user preferences.Influence of Commercial Considerations
Spotify’s recommendations can be influenced by commercial considerations, such as the cost of content or the ability to monetize it. For example, the Discovery Mode feature allows artists and labels to prioritize certain songs, which may affect the recommendations users receive.Potential for Misalignment with User Preferences
In some cases, the algorithm may misalign with user preferences, especially if the user’s listening habits are diverse or if they listen to music from different genres or eras. This can result in recommendations that are not as relevant or enjoyable as expected. By acknowledging both the strengths and weaknesses of Spotify’s recommendation system, users can better understand how to maximize their experience and provide meaningful feedback to improve the service. Spotify Recommendations (Spotify AI) - Comparison with Competitors
Unique Features of Spotify AI Recommendations
Spotify’s use of AI is highly personalized and multifaceted:AI DJ
AI DJ: Spotify’s AI DJ feature curates music based on individual user preferences and listening behavior, using a hyper-realistic voice generated by generative AI to narrate the selections.Discover Weekly
Discover Weekly: This feature creates custom-made playlists every Monday, using AI algorithms to introduce users to new music based on their streaming history, likes, and dislikes.AI-Powered Recommendations
AI-Powered Recommendations: Spotify’s AI models recommend music, podcasts, and playlists based on user behavior and preferences, optimizing for user engagement and satisfaction.Natural Language Search
Natural Language Search: Spotify employs AI to power natural language search, making it easier for users to find content using natural queries.AI Playlist
AI Playlist: A beta feature that allows users to create personalized playlists using creative prompts, combining genres, moods, artists, or decades to generate a unique musical mix.Comparison with Competitors
Apple Music
Apple Music: – Apple Music also uses machine learning for music recommendations, but it lacks the same level of personalization and interactive features like Spotify’s AI DJ. Apple Music’s recommendations are more integrated with other Apple services, providing a seamless experience for users within the Apple ecosystem. – While Apple Music has a large music library, its recommendation algorithms are not as highly personalized or dynamic as Spotify’s.Amazon Music
Amazon Music: – Amazon Music uses AI for recommendations, but it is more focused on integrating with Amazon’s broader ecosystem, such as Alexa and other smart devices. Amazon Music’s recommendations are based on user listening habits, but they do not have the same level of interactivity as Spotify’s AI features. – Amazon Music’s X-Ray feature provides additional content like lyrics and artist information, but it does not match the personalized playlist generation and AI-driven narration found on Spotify.Tidal
Tidal: – Tidal focuses more on high-quality audio and exclusive content from popular artists. While it uses some AI for recommendations, it does not have the extensive AI-driven features that Spotify offers. Tidal’s recommendations are more based on explicit user feedback and less on implicit behavior.Potential Alternatives
For users looking for alternatives with strong AI-driven recommendations, here are some options:YouTube Music
YouTube Music: YouTube Music uses AI to recommend music and videos based on user viewing and listening history. It has a strong focus on video content and can recommend music videos and live performances in addition to audio tracks.Deezer
Deezer: Deezer’s Flow feature uses AI to create a personalized playlist that combines favorite tracks with new discoveries. While it is not as extensive as Spotify’s AI features, it provides a continuous playlist experience based on user preferences. In summary, Spotify’s AI recommendations stand out due to their high level of personalization, interactive features like AI DJ, and the ability to generate unique playlists based on creative user prompts. While competitors offer some AI-driven recommendations, they do not match the breadth and depth of Spotify’s AI ecosystem. Spotify Recommendations (Spotify AI) - Frequently Asked Questions
Frequently Asked Questions about Spotify Recommendations
How does Spotify use AI to recommend music and podcasts?
Spotify uses AI in several ways to recommend music and podcasts. The AI models analyze your listening behavior, including what you listen to, how long you listen, what you skip, and what you save. This data helps create a detailed profile of your musical preferences. Spotify employs both collaborative filtering, which compares your habits to those of similar users, and content-based filtering, which analyzes the musical properties of songs like genre, tempo, and mood.What is the AI DJ feature on Spotify?
The AI DJ feature is an AI-powered disc jockey that curates music based on your specific tastes and listening behavior. It selects tracks, narrates its choices in a hyper-realistic voice, and adjusts the playlist in real-time based on your feedback. This feature combines personalization technology, generative AI, and a dynamic AI voice to create a more interactive listening experience.How does Spotify’s Discover Weekly feature work?
Discover Weekly is a popular feature that generates a personalized playlist for each user every week. It uses AI algorithms to analyze your listening habits and recommend new music that you might like. These playlists are updated weekly and reflect your current listening preferences, helping you discover new artists and songs.What are Daylists on Spotify?
Daylists are algorithmically-generated playlists that Spotify offers to its users. These playlists are created daily and have unique, quirky titles that reflect different genres, moods, and themes. They are generated based on thousands of descriptors and aim to provide hyper-personalized and dynamic playlists that match users’ unique audio identities.Can I influence and give feedback on Spotify recommendations?
Yes, you can influence and give feedback on Spotify recommendations. Your interactions with the app, such as liking, saving, or skipping tracks, help the algorithms refine your recommendations. You can also filter your Home page to see specific types of content, like only podcasts or music, and provide feedback directly through the app to adjust the recommendations further.How does Spotify ensure the recommendations are relevant and enjoyable?
Spotify ensures recommendations are relevant and enjoyable by using a combination of algorithmic recommendations and editorial curation. The algorithms consider your taste profile, general trends, and the characteristics of the content itself. Additionally, Spotify has dedicated teams of music editors who use data insights and cultural knowledge to curate content that resonates with listeners.What is the AI Playlist feature, and how does it work?
The AI Playlist feature, currently in beta for Premium users, allows you to create personalized playlists using written descriptions, emoticons, or abstract notions. You can input prompts like “indie folk playlist to give my brain a big warm hug” or “relaxing music for allergy season,” and the AI engine will generate a playlist based on your input and listening history. You can refine the playlist by providing additional feedback.How does Spotify balance familiarity and originality in its recommendations?
Spotify balances familiarity and originality by using reinforcement learning models that optimize recommendations based on user-centric metrics like increased likes or saves of tracks and increased user engagement. The algorithms aim to introduce new music while also incorporating familiar tracks to keep the listening experience engaging and satisfying.Can artists and labels influence Spotify recommendations?
Yes, artists and labels can influence Spotify recommendations through features like Discovery Mode. When an artist or label enables Discovery Mode for a song, Spotify’s algorithms are more likely to recommend that song, although this does not guarantee it will be recommended. The system ensures that the recommended songs are likely to be enjoyed by listeners.How does Spotify ensure safety and prevent exposure to harmful content in its recommendations?
Spotify has strict Platform Rules that apply to all content on the platform, including recommended content. When potentially violating content is identified, it is reviewed against these policies, and appropriate action is taken. Spotify collaborates with internal teams, external experts, and the Spotify Safety Advisory Council to ensure safety measures are in place.Are Spotify recommendations affected by commercial considerations?
Yes, commercial considerations can influence Spotify recommendations. For example, Discovery Mode allows artists and labels to prioritize certain songs, and Spotify charges a commission on streams of those songs in areas where Discovery Mode is active. However, Spotify ensures that these recommendations are still likely to be enjoyed by listeners and do not compromise the user experience.