TuneCore Algorithm Guide: Accelerator, Pitching & Pre-Saves

Part I: The Gateway: Understanding TuneCore’s Role in Your Algorithmic Strategy

The modern music landscape is governed by algorithms. For an independent artist, navigating this complex digital ecosystem requires a strategic partner capable of delivering music not just to stores, but to the very machine learning models that drive discovery. This guide deconstructs the role of TuneCore, moving beyond the common misconception of a singular “TuneCore algorithm” to reveal its true function: a critical data conduit and service provider that prepares, delivers, and promotes music for the algorithmic gatekeepers of Spotify, Apple Music, and beyond.

Deconstructing TuneCore: More Than Just a Distributor

At its core, TuneCore is a digital music distribution service designed for Do-It-Yourself (DIY) artists, labels, and managers. Its primary function is to deliver an artist’s music to over 150 online digital stores and streaming services, reaching audiences in more than 200 countries. These platforms include the most influential players in the industry, such as Spotify, Apple Music, Amazon Music, Deezer, TikTok, and Tencent.

It is essential to clarify that TuneCore does not operate a public-facing recommendation algorithm in the way that Spotify or YouTube does. Its internal “algorithm” is a logistical process encompassing content review, metadata validation, and delivery to digital service providers (DSPs). After an artist submits a release, it undergoes a content review process that typically takes one to two business days. Once approved, the release is sent to the selected stores, which are then responsible for making it live. TuneCore’s platform then aggregates the sales and streaming data from these disparate sources into a centralized dashboard for the artist.

A foundational element of TuneCore’s model is its artist-centric approach to ownership and revenue. Unlike some distributors that take a commission, TuneCore allows artists to retain 100% of their sales revenue and 100% of their copyrights. The service operates on a low annual flat-fee structure, ensuring that as an artist’s earnings grow, their distribution costs remain fixed.

TuneCore’s operational capabilities and industry influence are significantly amplified by its corporate structure. Since 2015, TuneCore has been a part of Believe, a leading global digital music company based in France. This relationship places TuneCore within a powerful ecosystem, alongside other major distributors owned by major labels, such as Sony’s The Orchard and Universal’s INgrooves. This affiliation provides TuneCore with the institutional leverage and deep-seated industry relationships necessary to offer services, such as direct editorial pitching channels, that may be inaccessible to smaller, fully independent distributors. An artist choosing TuneCore is therefore not just selecting a distribution tool, but also gaining access to the broader industry network and resources of the Believe group.

Choosing Your Toolkit: Selecting the Right TuneCore Plan for Your Career Stage

TuneCore offers a variety of pricing plans designed to accommodate the diverse needs of the independent artist community, from a musician releasing their first single to a label managing a large roster. The selection of a plan is not merely a financial decision but a strategic one that directly determines an artist’s access to the advanced promotional tools necessary to influence streaming algorithms.

For instance, eligibility for TuneCore’s proprietary “Artist Pitch Forms”—a service that submits new releases directly to DSP editorial teams—is exclusively available to artists subscribed to the Professional Unlimited Plan who have also opted into the TuneCore Accelerator program.⁷ This direct link between a specific subscription tier and a powerful promotional feature underscores the importance of viewing plan selection as an investment in an algorithmic toolkit. Artists must assess their career stage and release strategy to determine which plan provides the necessary features to achieve their discovery and growth objectives.

Beyond Distribution: An Overview of Publishing Administration and TuneCore Accelerator

TuneCore’s services extend far beyond the simple delivery of music files, offering crucial tools for revenue collection and audience development.

Music Publishing Administration

This service addresses a critical and often-overlooked revenue stream for songwriters: publishing royalties. When a song is streamed, sold, or publicly performed, it generates two types of royalties: one for the sound recording (master) and one for the underlying musical composition (publishing). TuneCore’s Music Publishing Administration service works in conjunction with an artist’s local Performing Rights Organization (PRO), such as ASCAP or BMI, to collect a wider range of royalties that PROs cannot.

Specifically, TuneCore registers compositions globally and collects mechanical royalties generated from every stream on platforms like Spotify and Apple Music, as well as micro-sync royalties from user-generated content on YouTube, TikTok, and other social media platforms. Furthermore, the service actively pitches an artist’s catalog for synchronization (sync) licenses in film, television, commercials, and video games, opening up significant revenue opportunities. This service operates on a one-time setup fee for unlimited song submissions, with TuneCore taking a 15% commission on collected royalties and a 50% commission on sync placement revenue.

TuneCore Accelerator

Positioned as a “powerhouse program,” TuneCore Accelerator is designed to proactively help artists find new audiences and propel their fandom at each stage of development. It functions as an artist development partner, leveraging an arsenal of promotional teams, marketing programs, and innovative products to drive the discovery of an artist’s music. By opting into this program, artists signal their readiness for growth, allowing TuneCore to identify and elevate their tracks for greater reach. This service transforms TuneCore from a passive delivery platform into an active promotional partner, a critical distinction for artists seeking to gain traction in a saturated market.

Plan Name	Cost Structure	Key Distribution Features	Access to Publishing Admin	Access to TuneCore Accelerator & Pitching	Best For (Artist Profile)
New Artist	Free	Unlimited releases to social platforms (TikTok, YouTube, etc.)	Additional Fee	Limited	Artists starting out, focusing on social media presence.
Rising Artist	Annual Fee	Unlimited releases to 150+ DSPs (Spotify, Apple Music)	Additional Fee	Opt-in available	Artists consistently releasing music and building a streaming presence.
Breakout Artist	Annual Fee	All Rising Artist features + advanced analytics	Additional Fee	Opt-in available	Artists with growing momentum, needing deeper data insights.
Professional	Annual Fee	All Breakout Artist features + premium support & exclusive opportunities	Additional Fee	Included with Opt-in	Professional artists, labels, and managers seeking maximum promotional support and direct pitching access.

Part II: The Pre-Release Playbook: Engineering Your Music for Discovery

The four-week period leading up to a release is not merely a marketing exercise for fans; it is a structured audition for the streaming platform’s algorithms. Every action taken during this time—from metadata entry to a fan’s pre-save—is a data point that builds a case for a song’s viability. A meticulously executed pre-release strategy primes the algorithmic pumps, ensuring that on release day, the song is positioned for maximum discovery and momentum.

The Foundation of Discovery: Mastering Your Metadata

Accurate and comprehensive metadata is the bedrock of algorithmic discovery. It is the language that allows platforms like Spotify and Apple Music to understand, categorize, and correctly recommend a track. Providing clean, standardized data to TuneCore is the first and most critical step in the entire process.

Essential metadata includes correct song and album titles, the primary artist name, and the correctly spelled names of all collaborators and contributors. This information must be paired with precise technical assets. Audio files must be uploaded as high-quality, 16-bit, 44.1 kHz stereo WAV or FLAC files; compressed formats like MP3 are not accepted and will halt the distribution process. Similarly, cover artwork must adhere to a strict 3000×3000 pixel dimension and be in JPG or PNG format. Beyond these technical requirements, artists should prepare a compelling artist biography, high-resolution publicity photos, and a comprehensive Electronic Press Kit (EPK) to ensure a professional and consistent presence across all platforms.

New to codes? Read our deep-dive on music metadata (ISRC, ISWC, UPC, DDEX) so your release is algorithm-ready from day one.

The 4-Week Countdown: A Strategic Release Timeline

A successful release requires a minimum lead time of four weeks. This window is essential not only for ensuring timely delivery to all digital stores but also for executing the crucial pitching and pre-save campaigns that feed the algorithms.

• 4 Weeks Out: The process begins with uploading the mastered audio, artwork, and all metadata to TuneCore. Once the release is submitted and processed, the artist should immediately claim and verify their artist profiles on platforms like Spotify for Artists and Apple Music for Artists. This is also the moment to pitch the release directly to editorial playlists via the Spotify for Artists and Amazon Music for Artists dashboards. For eligible TuneCore users, the Artist Pitch Form should also be submitted at this time.
• 3 Weeks Out: With the release secured in the DSPs’ systems, the public-facing campaign begins. Artists should start rolling out visual content such as new photos, music video teasers, or behind-the-scenes clips on social media. This is the ideal time to launch the pre-save campaign using a third-party service, providing fans with their first major call-to-action.
• 2 Weeks Out: The focus shifts to external press and playlisting. Artists should begin pitching their release to independent blogs, publications, and third-party playlist curators, often using platforms like SubmitHub to streamline the process. It is also a good time to refresh artist biographies and featured photos across all streaming platforms to reflect the upcoming release.
• Release Week: Promotion intensifies with a final push for pre-saves and a build-up of anticipation for release day. Artists should continue teasing song clips and share the cover artwork across all social channels. Planning for post-release engagement, such as scheduling live streams on Instagram or TikTok, is also critical to maintain momentum after the song drops.

Building Momentum Before Day One: Executing Effective Pre-Save Campaigns

A pre-save (or pre-add on Apple Music) campaign allows fans to authorize a streaming service to automatically add an upcoming release to their library and/or a personal playlist on release day. The algorithmic significance of this action is profound. A high volume of pre-saves acts as a powerful signal of high demand to the platforms, directly increasing the probability of the track being featured on influential algorithmic playlists. For Spotify, it is a key driver for placement on each pre-saving follower’s personalized Release Radar playlist.

To execute an effective campaign, artists must use a third-party service such as Linkfire, Feature.fm, or Hypeddit to generate a pre-save landing page. This requires the song’s Uniform Resource Identifier (URI), a unique code that can be obtained from the distributor (TuneCore) once the track has been successfully delivered to the streaming services.

This pre-save link should then be promoted relentlessly across all of the artist’s digital properties: in social media bios, as a pinned post on Twitter/Facebook, in email newsletters, and on the artist’s official website. To maximize conversion, it is crucial to give fans a compelling reason to click. This can be achieved by offering incentives like exclusive access to behind-the-scenes content, merchandise discounts, or entry into a contest. The promotion should be wrapped in a narrative, using storytelling to build a connection with the audience and generate genuine excitement for the release.

Crafting for Consumption: Song Structure and the Critical First 30 Seconds

The economics of attention in the streaming era have fundamentally reshaped effective song structure. A stream is typically only counted for algorithmic purposes and monetized for royalty payments if a listener plays past the 30-second mark. A listener skipping the track before this threshold is registered as a strong negative signal to the platform’s algorithm, indicating a poor user experience and reducing the song’s likelihood of being recommended further. This reality means that creative choices in songwriting and production now carry direct algorithmic and financial weight. A brilliant song with a 45-second atmospheric introduction may fail, not because it lacks artistic merit, but because it is structurally misaligned with the medium’s consumption patterns.

Best practices for song intros in the streaming era include:

• Shorten the Intro: The average length of an instrumental introduction has decreased dramatically. The goal is to get to the main vocal or hook as quickly as possible to capture listener attention.
• Front-Load the Catchiest Element: Introduce the song’s most memorable part—be it a vocal line from the chorus, a unique instrumental riff, or a compelling rhythmic pattern—within the first 30 seconds. This provides an immediate payoff and reduces the incentive to skip.
• Create Intrigue with Dynamics: Rather than a flat, static intro, use dynamic builds, unexpected sounds, or abrupt pauses to create a sense of anticipation and curiosity that pulls the listener in.
• Maintain Authenticity: While the intro must be engaging, it should also be an authentic representation of the song to follow. A “clickbait” intro that doesn’t correlate with the body of the track may hook a listener for a moment but will likely lead to a skip later if the transition is jarring or disingenuous.

Table 1: The Ultimate 4-Week Pre-Release Checklist & Timeline

Timeline	Key Action	Strategic Goal	Algorithmic Impact
Week -4	Upload music & metadata to TuneCore. Claim artist profiles (Spotify/Apple).	Secure URI for pre-save link. Ensure timely delivery to all stores.	Makes release eligible for pitching deadlines. Provides DSPs with metadata for initial categorization.
	Pitch via Spotify for Artists, Amazon Music for Artists, and TuneCore Artist Pitch Form.	Get on the radar of editorial teams early.	Provides crucial metadata (mood, genre, etc.) to content-based algorithms. Fulfills lead-time requirement for Release Radar.
Week -3	Launch pre-save campaign with a third-party link.	Start collecting high-intent signals from superfans.	A high volume of pre-saves signals strong demand, boosting chances of algorithmic and editorial playlisting.
	Begin rolling out visual content (teasers, photos) on social media.	Build awareness and drive traffic to the pre-save link.	Off-platform social buzz can be a positive signal for some platforms’ trend-detection algorithms.
Week -2	Begin pitching to independent blogs and third-party playlist curators.	Secure external press and playlist placements to coincide with release week.	Blog features and playlist adds drive external traffic to DSPs, a positive signal. Increases initial stream velocity.
	Update bios and photos across all DSPs.	Ensure a professional and consistent artist brand for the new release.	A complete and updated profile encourages fan follows and engagement.
Week -1	Intensify pre-save promotion with countdowns and new content.	Maximize the number of pre-saves before the release goes live.	Cements the signal of high demand right before release day.
	Share cover art and final teasers.	Create a final surge of anticipation.	Primes the audience for immediate engagement on release day.
Release Day	Share direct streaming links across all channels. Engage with fans in real-time.	Drive a concentrated burst of streams, saves, and playlist adds in the first 24 hours.	Strong day-one engagement is a critical signal for all algorithmic playlists (Release Radar, Discover Weekly, etc.).
Week +1	Analyze initial data in Spotify/Apple Music for Artists. Thank fans and share milestones.	Maintain momentum and encourage further sharing.	Post-release engagement (repeat listens, shares) continues to feed and train the algorithms.

Part III: Decoding the Digital Gatekeepers: A Deep Dive into Streaming Algorithms

To strategically influence music recommendation systems, an artist must first understand their fundamental architecture. While the specific code is proprietary, the underlying principles of machine learning that power platforms like Spotify and Apple Music are well-established. These systems operate as sophisticated, multi-stage engines designed to filter a near-infinite catalog of music down to a single, personalized recommendation.

The Three-Stage Recommendation Engine: From Catalog to Your Ears

Large-scale recommendation systems typically follow a three-stage architecture to efficiently process vast amounts of data while delivering highly personalized results.

1. Candidate Generation: This is the broad, initial filtering stage. The system sifts through millions of tracks to select a few hundred that are potentially relevant to a user. This is achieved using computationally efficient models like collaborative and content-based filtering. For an artist, having accurate metadata is paramount to ensure their music is correctly categorized and included in this initial candidate pool.
2. Ranking/Scoring: In this second stage, the smaller set of candidates is meticulously scored and ranked for the specific user. This phase employs more complex and computationally expensive models, such as Deep Neural Networks (DNNs) or Gradient Boosted Trees (GBTs), which analyze hundreds of features to predict the probability of a positive user interaction, like listening to a song for more than 30 seconds.
3. Re-Ranking/Post-Processing: The final, ranked list is not always what the user sees. In this crucial third stage, the list is adjusted to enforce business rules, promote diversity, and ensure fairness. For example, a song ranked highest by the scoring model might be moved down to prevent recommending too many songs from the same artist, to insert a newer track, or to ensure a more diverse representation of genres or genders. This stage explains why a song that seems like a perfect algorithmic fit may not always appear, as the system optimizes for long-term user satisfaction and platform health, not just immediate relevance.

The Spotify Ecosystem (BaRT): A World of Implicit Signals

Spotify’s recommendation engine, powered by an AI system nicknamed BaRT, is a masterclass in interpreting implicit user behavior. It is architected for a “lean-back” listening experience, aiming to create a seamless flow of music that requires minimal active user input. Its success hinges on accurately predicting the next song a user will enjoy, or at least not skip.

• Core Technologies:
  • Collaborative Filtering: This is the foundation of Spotify’s personalization. By analyzing over 2 billion user-created playlists and listening histories, the system identifies relationships between songs based on the principle that “users who like X also like Y”.
  • Content Analysis: BaRT employs two forms of content analysis. First, it analyzes the raw audio of every track to extract acoustic features like danceability, energy, tempo, and valence (the musical “positiveness”). Second, it uses Natural Language Processing (NLP) to scan lyrics, online articles, blog posts, and playlist titles to understand a song’s lyrical themes, cultural context, and associated moods.
  • Embeddings: Both songs and users are converted into complex numerical vectors, or “embeddings.” This allows the system to represent them in a multi-dimensional space where distance equates to similarity, enabling more nuanced comparisons than simple genre tags allow.
• Key Algorithmic Playlists & Surfaces:
  • Release Radar: This weekly playlist delivers new music from artists a user follows or listens to frequently. The most reliable way to secure placement on all of a user’s followers’ Release Radar is to pitch a track through Spotify for Artists at least seven days before its release. For a deeper breakdown of how Release Radar and Discover Weekly evaluate saves, skips, and replays, see our Ultimate Spotify Algorithm guide.
  • Discover Weekly: This is Spotify’s primary engine for pure discovery. It is driven almost entirely by collaborative filtering, analyzing a user’s unique taste profile and comparing it to those of other users to find songs they have in common that the target user has not yet heard. Strong positive engagement signals—such as a low skip rate, high save rate, and repeat listens—within the first one to two weeks after release are critical for a track to be considered for inclusion.
  • Exploitation vs. Exploration: Spotify’s algorithm operates in two modes. Exploitation mode serves users music it is confident they will like based on past behavior (e.g., Daily Mixes, Artist Radio). Exploration mode tests out new or lesser-known tracks on small audience pools to gather data on their performance. An artist’s goal is to generate enough positive data signals during the exploration phase to convince the algorithm that their track is “safe” to be exploited across a much wider audience.

The Apple Music Ecosystem (Algo-Torial): A Hybrid of Man and Machine

Apple Music operates on a distinct “algo-torial” philosophy, blending powerful machine learning with a strong layer of human editorial curation (full Apple Music Algorithm guide). Stemming from its iTunes legacy of music ownership and collection, the platform is optimized for a “lean-in” experience, encouraging users to actively build and manage a personal library.

• High-Intent Signals: Consequently, Apple’s algorithm places a significantly higher value on active, deliberate user actions that signal long-term investment in a track. While passive listening data is collected, the most powerful positive signals an artist can generate are when a user adds a song or album to their library or explicitly marks a track with the “Love” (❤️) icon. These actions are interpreted as a stronger endorsement than a simple stream.
• Key Recommendation Surfaces:
  • Listen Now: This is the personalized home screen, which exhibits a strong recency bias. It dynamically updates to reflect what a user has been listening to in the last 24-72 hours, creating a powerful but short-term opportunity for new releases that generate an initial burst of streams.
  • Personal Mixes: These are weekly updated playlists tailored to the user. The Favorites Mix leverages deep historical data, including iTunes play counts and ratings, to serve familiar favorites. The New Music Mix delivers new releases from artists a user follows, supplemented by human-curated picks that are stylistically similar to the user’s taste profile. Other mixes like the Chill Mix are mood-based but still personalized to the user’s genre preferences.
  • Discovery Station and Autoplay: These radio-style features are designed for pure exploration. They serve a continuous stream of unfamiliar tracks that are algorithmically selected based on their stylistic similarity to the music in a user’s library and listening history^{. Learn how Shazam data populates in your dashboard here: Shazam in Apple Music for Artists.}

Table 2: Algorithmic Signal Showdown: Spotify vs. Apple Music

Signal Category	Spotify	Apple Music
Overall Philosophy	“Lean-Back” (Passive Consumption)	“Lean-In” (Active Curation)
Primary Positive Signals	Playlist Adds, Low Skip Rate, Full Listens (>30s), Saves, Repeat Listens	Library Adds, ‘Loves’ (❤️), Full Listens (>30s), High Play Counts
Primary Negative Signal	Skip within the first 30 seconds	Skip within the first 30 seconds
Key Algorithmic Playlist Driver	Collaborative Filtering (listening habits of similar users)	Content-Based Analysis (stylistic similarity to user’s library) & Human Curation
Most Important Fan Action	“Add this to your workout playlist and let it play!”	“Add this to your library and hit the Love button!”

Part IV: The Artist’s Toolkit: Actionable Strategies for Algorithmic Growth

Understanding the inner workings of streaming algorithms is only the first step. The next is to translate that knowledge into a concrete set of actions. This section outlines actionable strategies for pitching, promotion, and fan engagement, designed to generate the specific data signals that each platform’s algorithm values most.

The Art of the Pitch: A Step-by-Step Guide to Editorial Consideration

Pitching for editorial playlist consideration is a critical component of any release strategy. It is a direct line of communication to both human curators and the platform’s own machine learning models.

• Spotify Pitching:The process is managed directly through the Spotify for Artists dashboard and must be completed at least seven days prior to the release date.18 Artists can only pitch one unreleased song per release. The pitch form is a vital data-gathering tool for Spotify; it requires detailed information about the song, including genre, sub-genre, mood, instrumentation, and culture tags. It also provides a 500-character space for the artist to tell the story behind the song. This metadata is not just read by human editors; it is ingested directly by Spotify’s content-based filtering algorithms and used to categorize the track. A well-written, descriptive pitch therefore serves a dual purpose: it makes a case for human consideration while simultaneously providing the algorithm with clean, accurate data, improving the song’s chances of algorithmic discovery regardless of editorial placement. Best practices include writing in the third person and using objective, descriptive language rather than subjective hype.
• Apple Music & Independent Pitching:Unlike Spotify, Apple Music does not offer a public-facing pitching portal for independent artists.61 Instead, submissions must be routed through a distributor that has an established, direct relationship with Apple’s editorial team. This is a key area where a distributor like TuneCore, particularly through its premium services, provides a distinct advantage.For independent blogs and third-party playlist curators, the approach must be personalized and professional. Thorough research is required to identify outlets that cover the artist’s specific genre and level of development. A successful pitch is tailored to the recipient, referencing their previous work or similar artists they have covered to demonstrate genuine interest. The communication should be concise and provide all necessary information upfront, including direct links to stream the music (on platforms like SoundCloud or a private Spotify link) and a link to a comprehensive EPK.14

Leveraging TuneCore’s Pitch Forms: Maximizing Your Accelerator Opportunities

For artists on TuneCore’s Professional Unlimited Plan who have opted into the TuneCore Accelerator program, the platform offers an exclusive and powerful tool: the Artist Pitch Form. This internal system serves as a direct conduit to both TuneCore’s own curated playlists (such as “TuneCore New Music Friday”) and the editorial teams at major DSP partners.

To be eligible, an artist must have a complete and up-to-date TuneCore Artist Profile for the primary artist on the release. The form can be submitted even before the release has been fully approved by TuneCore’s content review team. It is highly recommended to submit the pitch at least four weeks before the release date to allow ample time for review and consideration by all parties. This feature represents a significant value proposition, granting DIY artists a level of direct editorial access that is typically reserved for artists with label representation.

Post-Release Promotion: Fueling the Algorithm with Off-Platform Activity

The first 24 to 48 hours after a song is released are the most critical period for its algorithmic trajectory.²¹ The primary goal of all post-release promotion should be to drive a concentrated wave of traffic from off-platform sources (like social media) to the streaming services. This initial burst of activity provides the algorithm with its first and most important training dataset.

The behavior of this initial audience—whether they are highly engaged fans who save, share, and replay the track, or casual listeners who skip it—teaches the algorithm who the song is for. A strong, positive initial reaction from a core audience signals that the song is high-quality and should be tested on a wider group of similar listeners.

An effective social media strategy is essential for driving this initial traffic. This includes:

• Leveraging Short-Form Video: Creating and sharing engaging content on TikTok, Instagram Reels, and YouTube Shorts that features a compelling snippet of the new song.
• Using Platform Tools: Creating and sharing assets like Spotify’s Promo Cards to spotlight the new release and drive clicks.
• Direct Fan Engagement: Hosting live Q&A sessions, performing the song live, running contests, and actively sharing user-generated content that features the new track.
• Collaboration: Partnering with other artists or influencers for cross-promotion to tap into their audiences and expand reach.

Engaging Your Audience: Converting Listeners into High-Value Data Signals

General promotion is important, but strategic promotion is more effective. Artists should guide their fans with specific calls-to-action designed to generate the most valuable data signals for each platform. It is not enough to simply say “Listen to my new song.” Artists should explain how to listen and why it helps, much like a YouTuber asks for likes and subscribes.

• For Spotify: The ideal calls-to-action are:
  1. “Add this song to your personal playlist.” (A very strong signal of user affinity).
  2. “Listen to the whole track.” (Helps lower the skip rate).
  3. “Follow my artist profile.” (Ensures future releases land on their Release Radar).
• For Apple Music: The calls-to-action should focus on active library curation:
  1. “Add this song (or album) to your library.” (The platform’s most heavily weighted positive signal).
  2. “Hit the ‘Love’ (❤️) button on the track.” (An explicit and powerful endorsement).

By tailoring these requests to each platform, artists can mobilize their fanbase to function as an initial algorithmic training set, providing clean, positive data that encourages wider discovery.

Part V: Measure & Adapt: Mastering Your Analytics Dashboards

Data is the language of the algorithmic age. For an artist, the analytics dashboards provided by TuneCore, Spotify, and Apple Music are not just scorecards of past performance; they are strategic tools for understanding an audience, refining marketing efforts, and making informed decisions about the future. However, it is crucial to understand that this data is often lagged and asynchronous. Different platforms update on different schedules, and acting on incomplete information can lead to flawed conclusions. Patience and a clear understanding of data latency are key to effective analysis.

The TuneCore Dashboard: Your Distribution Hub

TuneCore’s Trends & Analytics Dashboard serves as a centralized hub for monitoring the performance of a release across multiple platforms. It is important to note that the “Trends” data is unofficial and serves as an early indicator of activity from select stores like iTunes, Amazon Music, Spotify, and TikTok. It is not the final, official sales report from which royalties are paid.

Key features of the dashboard include:

• Streams & Earnings Trends: Provides a high-level overview of streaming and download activity over various time periods.
• Audience Map: A visual representation of where listeners are located by country and state, offering invaluable data for planning tours or targeting regional marketing campaigns.
• User Generated Content (UGC) Widget: A standout feature that provides exclusive analytics from TikTok and its Chinese counterpart, Douyin. It tracks the number of likes, comments, and video “creations” using an artist’s track, offering a direct measure of its viral potential on these critical platforms.
• Insights Tool: An automated feature that analyzes monthly trends to highlight an artist’s top-performing songs and most popular countries, simplifying the process of identifying key growth areas.

Spotify for Artists: Granular Audience Insights

The Spotify for Artists (S4A) dashboard offers the most detailed and granular data on listener behavior available to artists. Mastering this platform is essential for understanding the nuances of algorithmic performance.

• Key Data Sections:
  • Audience Data: This section provides a timeline of core metrics: Listeners (unique individuals), Streams (total plays over 30 seconds), and Followers. It also offers demographic breakdowns by age and gender, as well as geographic data on top countries and cities. Critically, it includes the Source of Streams chart, which reveals how listeners are discovering the music—whether from active sources like an artist’s profile and a listener’s own library, or from programmed sources like editorial and algorithmic playlists.
  • Music Data: Here, artists can track the performance of individual tracks, including total streams and, importantly, total saves. This metric is a direct measure of how many listeners have added a song to their library, a strong positive signal for the algorithm.
  • Playlist Data: This tab provides a comprehensive list of every public playlist a song has been added to—including editorial, algorithmic, and user-generated playlists—along with the number of streams generated from each source.
  • Audience Segments: This advanced tool categorizes an artist’s audience into three groups: Active audience (listeners who intentionally streamed from active sources in the last 28 days), Previously active audience, and Programmed audience (listeners who only streamed from programmed sources). This segmentation helps artists understand the journey from passive discovery to active, intentional fandom.

Apple Music for Artists: Tracking High-Intent Actions & Offline Impact

The Apple Music for Artists (AM4A) dashboard provides a different, yet equally valuable, set of metrics that reflect its unique algorithmic priorities and its integration with the broader Apple ecosystem.

• Key Metrics:
  • Plays and Listeners: Similar to Spotify, a “play” is registered when a user listens for more than 30 seconds.
  • Shazam Count: This is arguably the most powerful and unique metric offered by Apple. It tracks the number of times a song has been identified using the Shazam app, providing a direct measurement of real-world, offline discovery. When someone in a coffee shop, retail store, or listening to the radio is compelled enough to pull out their phone and identify a song, it represents an incredibly strong signal of organic interest. The AM4A dashboard provides geographic data for these Shazams, pinpointing exactly where a song is generating buzz in the physical world.
  • Purchases: The dashboard also tracks traditional sales of songs and albums from the iTunes Store.
  • A Note on “Loves” and Library Adds: It is critical for artists to understand that while adding a song to a library and marking it as “Loved” are the most important positive signals for the Apple Music algorithm, the AM4A dashboard does not currently provide a direct, quantifiable metric for these actions. Artists must infer this deep engagement by analyzing trends in overall plays, daily listeners, and the growth of their audience in the “Trends” tab, which allows for filtering by demographics and location.

The Metrics That Matter: Calculating Your Key Performance Indicators (KPIs)

To move from passively viewing data to actively analyzing performance, artists should calculate several key performance indicators (KPIs). These ratios and rates provide a much deeper understanding of audience engagement than raw stream counts alone.

• Save Rate (Spotify): This KPI measures the efficiency of converting listeners into engaged fans. A high save rate is a powerful positive signal for Spotify’s algorithmic playlists.
  • Formula:
• Listener-to-Follower Ratio (Spotify): This ratio indicates how effectively an artist is converting their overall reach (listeners) into a core, subscribed fanbase (followers) who will be automatically served new music via Release Radar.
  • Formula:
• Play-Through Rate (PTR) / Completion Rate: While Spotify no longer provides a “Starts” metric, the underlying principle of minimizing early skips remains paramount. A high PTR (or low skip rate) is one of the most fundamental signals of a positive user experience.
  • Conceptual Formula:
• Shazam Velocity (SV): This metric, derived from principles of physics, measures the rate of change or acceleration of Shazams over a period. A sudden spike in Shazam Velocity in a specific city is a powerful leading indicator of emerging viral potential, a new radio add, or successful sync placement, providing a highly actionable signal for targeted promotion.
  • Formula:

Table 3: The Artist KPI Dashboard

KPI Name	Platform	Formula	Data Needed	Why It Matters (Algorithmic Significance)
Save Rate	Spotify		Saves (Music Tab), Listeners (Audience Tab)	High save rate indicates strong user intent to revisit; a key positive signal for Discover Weekly and other algorithmic playlists.
Listener-to-Follower Ratio	Spotify		Followers (Audience Tab), Listeners (Audience Tab)	Measures conversion of casual listeners to core fans. Followers are automatically served new music on Release Radar.
Play-Through Rate (PTR)	All	Concept:	Streams, Starts (where available). In S4A, this is inferred from a low skip rate.	A low skip rate (high PTR) is a fundamental positive signal. A high skip rate (<30s) is a strong negative signal.
Shazam Velocity (SV)	Apple Music		Shazam Count (Trends Tab) at two different time points.	Measures the acceleration of real-world discovery. A spike in a specific city is a powerful leading indicator of viral potential.

Table 4: Analytics Platform Latency Guide

Platform	Metric	Update Frequency	Typical Delay
TuneCore Trends	Streams / Sales	Daily	24-72 hours (unofficial data)
Spotify for Artists	Listeners / Streams	Daily (approx. 3 PM EST / 8 PM UTC)	~24-48 hours
	Live Stream Count	Every 2 seconds	Real-time (for first 7 days of a new release)
Apple Music for Artists	Plays / Listeners / Shazams	Daily	24-48 hours
Royalty Payments	All Platforms	Monthly/Quarterly	2-6 months

Conclusion

The era of passive music distribution is over. For the modern independent artist, success is not determined by a single “TuneCore algorithm,” but by a sophisticated, multi-platform strategy designed to feed and influence the complex recommendation engines of the world’s largest streaming services. This guide has deconstructed this ecosystem, revealing a clear path forward.

The strategic imperatives are clear:

1. Reframe Distribution as Data Preparation: An artist’s relationship with TuneCore is not merely transactional; it is the foundational step in packaging musical assets and metadata into a clean, algorithm-friendly format. The choice of a distribution plan is a strategic investment in the tools required for this process.
2. Treat the Pre-Release Phase as an Algorithmic Audition: The four weeks prior to release are a critical period for building a data-driven case for a song’s viability. Through meticulous planning, pre-save campaigns, and platform-specific pitching, an artist can generate the signals of high demand that prime a release for both editorial and algorithmic success.
3. Tailor Fan Engagement to Platform Architecture: Spotify’s “lean-back” and Apple Music’s “lean-in” ecosystems reward different user behaviors. Artists must move beyond generic calls-to-action and guide their fanbase to perform the specific actions—playlist adds on Spotify, library adds on Apple Music—that each platform values most.
4. Measure What Matters to the Machine: Raw stream counts are a vanity metric. True performance is measured by analyzing engagement ratios and leading indicators. By calculating KPIs such as Save Rate and Shazam Velocity, artists can transform themselves from passive observers of data into active analysts, capable of adapting their strategies in real-time to capitalize on momentum and drive sustainable growth.

Ultimately, the algorithms are not inscrutable black boxes; they are systems designed to interpret human behavior. By understanding the data they seek and the signals they value, artists can transform their distribution strategy from a simple act of delivery into a powerful engine for discovery.

---

References:

• TuneCore – A worldwide digital music self-distribution service – Believe, accessed on October 5, 2025, https://www.believe.com/tunecore
• What is TuneCore?, accessed on October 5, 2025, https://www.tunecore.com/what-is-tunecore
• Why Choose TuneCore as Your Music Distributor? – SoundOn, accessed on October 5, 2025, https://www.soundon.global/forum/tunecore-platform-overview?lang=en
• How Does TuneCore Work for Distribution? – SoundOn, accessed on October 5, 2025, https://www.soundon.global/forum/tunecore-music-distribution?lang=en
• Does TuneCore Own Your Music? Discover The Truth Now! – House of Tracks, accessed on October 5, 2025, https://houseoftracks.com/faq/does-tunecore-own-your-music
• DistroKid vs. Tunecore vs. CD Baby vs…Distribution Reviews for 2025 – Ari’s Take, accessed on October 5, 2025, https://aristake.com/digital-distribution-comparison/
• Artist Pitch Forms – TuneCore, accessed on October 5, 2025, https://support.tunecore.com/hc/en-us/articles/17878146830228-Artist-Pitch-Forms
• Music Publishing Administration Services – TuneCore, accessed on October 5, 2025, https://www.tunecore.com/music-publishing-administration
• TuneCore: Digital Music Distribution Services | Start Now!, accessed on October 5, 2025, https://www.tunecore.com/
• Independent Record Labels: Succeeding with AI & Algorithms – Forward Digital, accessed on October 5, 2025, https://fwdmusic.com/en/news/independent-record-labels-succeeding-with-ai-and-algorithms
• The Auditory Algorithm: Unveiling How Music Streaming Algorithms Impact Independent Artists | Indiefy Blog, accessed on October 5, 2025, https://indiefy.net/blog/the-auditory-algorithm-unveiling-how-music-streaming-algorithms-impact-independent-artists
• Music Algorithms for Music Discovery & Getting Discovered | iMusician, accessed on October 5, 2025, https://imusician.pro/en/resources/blog/how-to-leverage-music-algorithms-for-music-curation-and-getting-discovered-as-an-artist
• Unlimited Guides: Release Planning 101 – TuneCore, accessed on October 5, 2025, https://www.tunecore.com/guides/unlimited-guides-release-planning-101
• How To Pitch Your Music to Blogs and Spotify Playlist Curators, accessed on October 5, 2025, https://www.tunecore.com/guides/pitching-your-music-101
• Maximize the Impact of Your Music Release with a Pre save Campaign – Wiseband.com, accessed on October 5, 2025, https://www.wiseband.com/blog/maximize-the-impact-of-your-music-release-with-a-pre-save-campaign/
• Pre-Save on Spotify: How to Set Up and Use Pre-Save Campaigns – Musosoup, accessed on October 5, 2025, https://musosoup.com/blog/pre-save-spotify
• The Ultimate Pre-Save Guide for 2024 and Beyond, accessed on October 5, 2025, https://oddlysimpl.xyz/pre-save-campaigns/
• Pitching music to Spotify playlist editors – Spotify, accessed on October 5, 2025, https://support.spotify.com/us/artists/article/pitching-music-to-playlist-editors/
• Pre Save Guide: How to Boost Your Music Launch in 2025 – Smart Noise, accessed on October 5, 2025, https://smart-noise.com/pre-save/
• How to Create and Use a Spotify Pre-Save Link – Xposure Music Blog, accessed on October 5, 2025, https://info.xposuremusic.com/article/how-to-create-and-use-a-spotify-pre-save-link
• How does Spotify’s algorithm work? Streaming hacks for musicians – Ditto Music, accessed on October 5, 2025, https://dittomusic.com/en/blog/how-does-spotifys-algorithm-work-streaming-hacks-for-musicians
• The Only Spotify Algorithm Cheat Sheet You’ll Ever Need – Pitch-Us, accessed on October 5, 2025, https://pitch-us.com/blogs/marketing/the-only-spotify-algorithm-cheat-sheet-youll-ever-need
• Spotify’s Algorithm: Explained – Wiseband.com, accessed on October 5, 2025, https://www.wiseband.com/blog/spotifys-algorithm-explained/
• Don’t bore us, get to the chorus? How streaming is changing songs | CBC News, accessed on October 5, 2025, https://www.cbc.ca/news/entertainment/streaming-songs-changes-1.5002748
• Focus on these 5 metrics on Spotify for Artists – Kabir Sehgal, accessed on October 5, 2025, https://kabir.cc/focus-on-these-5-metrics-on-spotify-for-artists/
• Three Tips for Writing Better Song Intros – Cliff Goldmacher, accessed on October 5, 2025, https://www.cliffgoldmacher.com/three-tips-for-writing-better-song-intros/
• The First 30 Seconds | iMusician, accessed on October 5, 2025, https://imusician.pro/en/resources/blog/the-first-30-seconds
• How to Hook a Listener in the first 30 Seconds of a Song | Music Tips, accessed on October 5, 2025, https://aimm.edu/blog/hook-a-listener-in-the-first-30-seconds-of-a-song
• 5 Tips For Creating Engaging Intros For Your Songs – Supreme Tracks, accessed on October 5, 2025, https://www.supremetracks.com/intro-music-tips/
• Any tricks you like to do for song intros? : r/edmproduction – Reddit, accessed on October 5, 2025, https://www.reddit.com/r/edmproduction/comments/1af4hi9/any_tricks_you_like_to_do_for_song_intros/
• Mastering the Art: How to Create a Compelling Intro for Your Tracks – Slime Green Beats, accessed on October 5, 2025, https://slimegreenbeats.com/blogs/music/mastering-the-art-how-to-create-a-compelling-intro-for-your-tracks
• Spotify Recommendation System and User Engagement Strategies – TechAhead, accessed on October 5, 2025, https://www.techaheadcorp.com/blog/spotify-recommendation-system/
• Beyond Candidate Generation and Ranking: The Missing “Business …, accessed on October 5, 2025, https://medium.com/@thaweewat.data/beyond-candidate-generation-and-ranking-the-missing-business-logic-layer-in-recommendation-4938979ca8b6
• Re-ranking | Machine Learning – Google for Developers, accessed on October 5, 2025, https://developers.google.com/machine-learning/recommendation/dnn/re-ranking
• Vinija’s Notes • Recommendation Systems • Candidate Generation and Retrieval, accessed on October 5, 2025, https://vinija.ai/recsys1/candidate-gen/
• T-RECSYS: A Novel Music Recommendation System Using Deep Learning, accessed on October 5, 2025, https://par.nsf.gov/servlets/purl/10088296
• End-to-End Recommender System with Gradient – Part 1: Posing a Business Problem, accessed on October 5, 2025, https://blog.paperspace.com/end-to-end-recommender-system-part-1-business-problem/
• Aman’s AI Journal • Recommendation Systems • Re-ranking, accessed on October 5, 2025, https://aman.ai/recsys/re-ranking/
• Haven’t I just Listened to This?: Exploring Diversity in Music Recommendations – Antonela Tommasel, accessed on October 5, 2025, https://tommantonela.github.io/umap2022b.pdf
• Are music recommendation algorithms fair to emerging artists …, accessed on October 5, 2025, https://www.music-tomorrow.com/blog/fairness-and-diversity-in-music-recommendation-algorithms
• Inside Spotify’s Recommendation System: A Complete Guide (2025 …, accessed on October 5, 2025, https://www.music-tomorrow.com/blog/how-spotify-recommendation-system-works-complete-guide
• The Role Of Music Streaming Algorithms In The Industry – Boost Collective, accessed on October 5, 2025, https://blog.boostcollective.ca/the-role-of-music-streaming-algorithms-in-the-industry
• Spotify’s Music Recommendation Algorithm: The Complete Guide – Beats To Rap On, accessed on October 5, 2025, https://beatstorapon.com/blog/ultimate-guide-to-spotify-music-algorithm/
• The magic that makes Spotify’s Discover Weekly playlists so damn good – Quartz, accessed on October 5, 2025, https://qz.com/571007/the-magic-that-makes-spotifys-discover-weekly-playlists-so-damn-good
• Best Music Recommendation Algorithm: How They Work? | Attract …, accessed on October 5, 2025, https://attractgroup.com/blog/best-music-recommendation-algorithm-how-they-work/
• “I Built a Music Recommender — Here’s Why It Fails (And What Big Tech Does Differently)” Part 1 | by Bytes of Insight | Medium, accessed on October 5, 2025, https://medium.com/@bytesofinsight/i-built-a-music-recommender-heres-why-it-fails-and-what-big-tech-does-differently-part-1-077ac69bdc92
• 02 – Embedding Songs to Make Recommendations.ipynb – Colab, accessed on October 5, 2025, https://colab.research.google.com/github/jalammar/jalammar.github.io/blob/master/notebooks/nlp/02_Song_Embeddings.ipynb
• Spotify Algorithm 2025: How to Get on Algorithmic Playlists – Loop Solitaire, accessed on October 5, 2025, https://loopsolitaire.co.uk/blog/spotify-algorithmic-playlists/
• Unlocking Spotify Discover Weekly: Tips to Get Your Music Featured | Musosoup, accessed on October 5, 2025, https://musosoup.com/blog/spotify-discover-weekly
• Spotify’s algorithms drives 3-4% of industry revenue – RouteNote Blog, accessed on October 5, 2025, https://routenote.com/blog/spotifys-algorithms-drives-3-4-of-industry-revenue/
• How The Spotify Algorithm Works – Loudlab, accessed on October 5, 2025, https://www.loudlab.org/blog/understanding-how-spotify-algorithm-works/
• What Is Apple Music Algorithm? – MusConv, accessed on October 5, 2025, https://musconv.com/what-is-apple-music-algorithm/
• Apple Music Algorithm Guide 2026: Signals, Surfaces & Growth, accessed on October 5, 2025, https://beatstorapon.com/blog/the-apple-music-algorithm-in-2026-a-comprehensive-guide-for-artists-labels-and-data-scientists/
• Apple Music Algorithmic Playlists: How They Work and How to Get On, accessed on October 5, 2025, https://musosoup.com/blog/apple-music-algorithmic-playlists
• How The Apple Music Algorithm Works – Genera Studios, accessed on October 5, 2025, https://generastudios.com/blogs/music-production/how-the-apple-music-algorithm-works
• How does Apple Music want to be used? : r/AppleMusic – Reddit, accessed on October 5, 2025, https://www.reddit.com/r/AppleMusic/comments/1hqpa9v/how_does_apple_music_want_to_be_used/
• The “For you” and “Explore” tabs are completely useless : r/AppleMusic – Reddit, accessed on October 5, 2025, https://www.reddit.com/r/AppleMusic/comments/fiha32/the_for_you_and_explore_tabs_are_completely/
• Apple reveals algorithm behind Apple Music mixes, execs discuss past and future of service, accessed on October 5, 2025, https://appleinsider.com/articles/16/09/27/apple-reveals-algorithm-behind-apple-music-mixes-execs-discuss-past-and-future-of-service
• Apple Music adds a new personalized daily playlist based on the songs you can’t quit, accessed on October 5, 2025, https://www.techradar.com/audio/apple-music/apple-music-adds-a-new-personalized-daily-playlist-based-on-the-songs-you-cant-quit
• Have you ever successfully pitched your song for a spot on a Spotify Editorial playlist? : r/WeAreTheMusicMakers – Reddit, accessed on October 5, 2025, https://www.reddit.com/r/WeAreTheMusicMakers/comments/10gkbj1/have_you_ever_successfully_pitched_your_song_for/
• CD baby has access to pitching to apple music editorial playlists but distrokid and tunecore don’t ? : r/musicindustry – Reddit, accessed on October 5, 2025, https://www.reddit.com/r/musicindustry/comments/1mqx00l/cd_baby_has_access_to_pitching_to_apple_music/
• How To Feed The Spotify Algorithm To Get More Streams – Symphonic Blog, accessed on October 5, 2025, https://blog.symphonic.com/2024/10/01/how-to-feed-the-spotify-algorithm-to-get-more-streams-2/
• 10 Social Media Strategies to Boost Your Following as an Artist – EngineEars Blog, accessed on October 5, 2025, https://blog.engineears.com/10-social-media-strategies-to-boost-your-following-as-an-artist/
• Preparing for Release Day and Beyond – Spotify for Artists, accessed on October 5, 2025, https://artists.spotify.com/blog/release-guide-preparing-for-release-day
• How to get more SPOTIFY STREAMS without cheating: 7 tips to stand out from the crowd – Groover Blog, accessed on October 5, 2025, https://blog.groover.co/en/tips/spotify-streams/
• Spotify Saves Guide: How to Boost Your Tracks in 2025 – Smart Noise, accessed on October 5, 2025, https://smart-noise.com/spotify-saves/
• How Long Does It Take to Get Paid? The Lag Between Streams and Royalties, accessed on October 5, 2025, https://info.xposuremusic.com/article/how-long-does-it-take-to-get-paid-the-lag-between-streams-and-royalties
• When stats update in Spotify for Artists, accessed on October 5, 2025, https://support.spotify.com/us/artists/article/when-stats-update/
• Apple Music statistics not updated since April 23. Spotify is updated on DK statistics, Apple not. On Apple Music for Artists my streams are up to date. Does anyone has the same problem? Is this a problem of DK or Apple? : r/DistroKidHelpDesk – Reddit, accessed on October 5, 2025, https://www.reddit.com/r/DistroKidHelpDesk/comments/133wks8/apple_music_statistics_not_updated_since_april_23/
• TuneCore’s Trends and Analytics Dashboard, accessed on October 5, 2025, https://www.tunecore.com/trends-and-analytics-dashboard
• What Does the TuneCore Dashboard Offer? – SoundOn, accessed on October 5, 2025, https://www.soundon.global/forum/tunecore-dashboard-overview?lang=en
• Trends & Analytics Reports – TuneCore, accessed on October 5, 2025, https://support.tunecore.com/hc/en-us/articles/115006499207-Trends-Analytics-Reports
• TuneCore Unveils Groundbreaking Advanced Trends & Analytics Dashboard Made Specifically for Self-Releasing Artists, accessed on October 5, 2025, https://www.tunecore.com/press/tunecore-unveils-groundbreaking-advanced-trends-analytics-dashboard-made-specific
• Analytics – Spotify for Artists, accessed on October 5, 2025, https://artists.spotify.com/analytics
• artists.spotify.com, accessed on October 5, 2025, https://artists.spotify.com/en/analytics#:~:text=With%20our%20free%2C%20music%2Dfirst,your%20audience’s%20development%20and%20engagement.&text=Measure%20streams%20and%20saves%20to%20track%20growth%20across%20your%20entire%20catalog.&text=Get%20engagement%20and%20demographic%20insights%20for%20your%20listeners%20and%20followers.
• Understanding your listener and follower stats – Spotify Support, accessed on October 5, 2025, https://support.spotify.com/us/artists/article/understanding-your-listener-and-follower-stats/
• How to Read Your Spotify for Artists Data, accessed on October 5, 2025, https://artists.spotify.com/blog/how-to-read-your-spotify-for-artists-data
• How we count saves – Spotify Support, accessed on October 5, 2025, https://support.spotify.com/us/artists/article/how-we-count-saves/
• Spotify Artists Analytics: Track Playlists, Charts, & Audience Data – Soundcharts, accessed on October 5, 2025, https://soundcharts.com/spotify-analytics
• Understand your analytics – Apple Music for Artists, accessed on October 5, 2025, https://artists.apple.com/support/1105-understand-your-analytics
• Music analytics and insights – Apple Music for Artists, accessed on October 5, 2025, https://artists.apple.com/measure
• Utilizing Apple Music For Artists Analytics To Connect With Your Audience – Promoly, accessed on October 5, 2025, https://promo.ly/utilizing-apple-music-for-artists-analytics-for-growth/
• See how Shazam works for artists – Apple Music for Artists, accessed on October 5, 2025, https://artists.apple.com/support/1109-shazam-in-apple-music-for-artists
• Shazam Stats for Artists – Apple Music Provider Support, accessed on October 5, 2025, https://itunespartner.apple.com/music/support/5235-shazam-for-artists
• How to add and find favorites in Apple Music on your iPhone, iPad, or Android, accessed on October 5, 2025, https://support.apple.com/en-us/111118
• How To Add and Find Favorites In Apple Music on Your iPhone – YouTube, accessed on October 5, 2025, https://www.youtube.com/watch?v=ASe9Z3nT2HY
• See your song stats and listener trends – Apple Music for Artists, accessed on October 5, 2025, https://artists.apple.com/support/1107-see-your-song-stats-and-listener-trends
• Behind the Metrics: What Playlists Do to Your Spotify Profile – IsItAGoodPlaylist, accessed on October 5, 2025, https://www.isitagoodplaylist.com/article/behind-the-metrics-what-playlists-do-to-your-spotify-profile
• Understanding engagement metrics on Spotify, accessed on October 5, 2025, https://support.spotify.com/us/creators/article/understanding-engagement-metrics-on-spotify/
• Instantaneous speed and velocity (video) – Khan Academy, accessed on October 5, 2025, https://www.khanacademy.org/test-prep/mcat/physical-processes/speed-and-velocity/v/instantaneous-speed-and-velocity
• How to Calculate Velocity – YouTube, accessed on October 5, 2025, https://www.youtube.com/watch?v=XfXoU_G6im4