final project of semester 1 analysis of the recommended algorithm which spotify has applied

VIET NAM NATIONAL UNIVERSITY, HO CHI MINH CITY UNIVERSITY OF ECONOMICS AND LAW

FINAL PROJECT OF SEMESTER 1

Course: NEW ICT Course’s ID: 23IBIE105106

ANALYSIS OF THE RECOMMENDED ALGORITHM WHICH SPOTIFY HAS APPLIED

Instructor guides: PhD Nguyén Thôn Dã

Member list:

1 K234040511 - Nguyén Thi Bich Thuy 2 K234040497 - Vũ Nguyễn Yến Nhi 3 K234111350 - Nguyễn Vũ Gia Ngân 4 K234060700 - Nguyễn Như Khải 5 K234060689 - Nguyễn Tô Hoàng Gia

H6 Chi Minh City, 20th December, 2023

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TP Hỗ Chí Minh, ngày 20 tháng 12 năm 2023

Tập thê thành viên nhóm: 1 Nguyễn Thị Bích Thủy 2 Vũ Nguyễn Yến Nhi

3 Nguyễn Vũ Gia Ngân

4 Nguyễn Như Khải 5 Nguyễn Tô Hoàng Gia

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TABLE OF BOARD AND IMAGE

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LIST OF ACRONYMS

UX User Experience SaaS Service as a software CTO Chief Technology Officer LTV Lifetime value

RS Recommender System Al Artificial Intelligence

BaRT Bandits for Recommendations as Treatment APIs Application Programming Interface ACM Association for Computing Machinery

BERT Bidirectional Encoder Representations from Transformers GPT Generative Pre-training Transformer

XML eXtensible Markup Language

mBERT | Multilingual Bidirectional Encoder Representations from Transformers

MUSE — |} Multilingual Universal Sentence Encoder

PART I Overview of technology

@ Recommendation System is the algorithm deploying machine learning (ML) algorithms to recommend new titles for all their users Spotify's recommendation algorithm uses a variety of algorithms to process this data and generate recommendations Some of the key algorithms include:

+ Collaborative filtering: This algorithm identifies users with similar listening habits and recommends songs that those users have enjoyed It's based on the principle that people with similar tastes tend to like the same music

+ Content-based filtering: This algorithm analyzes the musical characteristics of songs to recommend songs that share similar traits with songs the user has already listened to It's based on the idea that users prefer music with similar sonic elements

+ Hybrid filtering: This algorithm combines collaborative filtering and content-based filtering to create a more comprehensive recommendation system It takes into account both user preferences and song characteristics to provide a more personalized experience

Natural language processing (NLP) is an algorithm that provides the ability to understand text and speech Spotify uses NLP to classify their music By searching the web for any text, Spotify can also find out about a specific song Spotify’s NLP then categorized songs based on the language used to describe them Keywords will be picked out and assigned a weight, which can measure how much a song exhibits a particular emotion This helps spotify’s algorithms identify which songs and artists belong in playlists together, which can then be more easily deployed to the recommendation system

Reinforcement learning (RI) is a system produced based on ML methods to understand goals and respond to data through trial and error during interaction Spotify uses the RL system to feature songs and artists From there they will be accurate and meaningful to the home page of subscribers

New content is first delivered to subscribers through additional filtering or NLP Thereby, subscribers can easily interact with the song in many different ways (listen to the song once, play the song multiple times or listen to more songs from other artists) or stop playing by pressing Skip the song In all cases, subscribers send information to the RL algorithm about their desired level of

success

RL offers users to explore other areas of music through knowing their preferences and typical listening history Expanding the range of music subscribers are listening to will expand the range of music consumed within the Spotify app's catalog — benefiting both artists and the Spotify platform New content 1s first served to subscribers using collaborative filtering or NLP The subscriber will then engage with the song on varying levels (listen to the song once, on repeat, listen to more songs by the artist) or disengage by skipping the song In either case, the user is sending information to the algorithm about how successful their prediction was

1.2 Characteristics

1.2.1 Recommendation System

Spotify's recommendation system relies on analyzing various characteristics to personalize your music experience These characteristics can be broadly categorized into three main types:

® User Characteristics:

Listening history: This includes the songs you have listened to, skipped, saved, and added to playlists It provides valuable insight into your musical preferences and listening habits

Saved songs and artists: These represent songs and artists you explicitly show interest in, indicating a strong preference

Followed playlists: This reflects your interest in specific genres, themes, or

curators

Demographic information: Although not directly used for recommendations, information like age, gender, and location can be incorporated for broader targeting

Song Characteristics:

Audio features: This includes musical attributes like tempo, key, energy level, danceability, and acousticness, allowing for categorization and suggestions based on similar sonic qualities

Genre and subgenre: Categorization based on genre and subgenre helps identify songs with similar musical styles and themes

Lyrics and artist information: Analyzing lyrics can reveal themes, emotions, and concepts, while artist information provides context about their musical style and influences

Release date and popularity: Newer releases and trending songs can be factored in for discovering fresh music or exploring popular trends

@ Contextual Information:

- Time of day: Spotify considers the time of day to recommend music suitable for different activities and moods, like upbeat music for mornings or relaxing tracks for evenings

- Location: This can be used to suggest music popular in your region or relevant to specific locations

- Device: Depending on the device you use (phone, laptop, speaker), Spotify might suggest music suitable for different listening environments or activities

1.2.2, Natural Language Process

- With all the data Spotify has collected, the NLP algorithm is capable of classifying songs based on the type of language used in their descriptions and similarity to other songs used for the same purpose Artists and songs will be classified based on data and each term has a certain weight assigned to them Similar to collaborative filtering, a vector representation of the song is created and used for the purpose of recommending other similar songs to the user

- Search and Discovery:

+ Natural Language Search: Search for music using natural language queries instead of exact keywords, allowing for more flexibility and understanding of user intent Personalized Recommendations: Generate "Discover Weekly" and "Release Radar" playlists using NLP to analyze listening history, saved songs, and followed artists

+ Understanding Lyric and Artist Descriptions: Analyze lyrics and _ artist descriptions to categorize music by genre, mood, and theme, improving search results and music discovery

- User Interface and Interaction:

+ Voice Search and Assistant: Interact with Spotify using natural language commands to search for music, control playback, and access features

+ Context-Aware Recommendations: Recommend music based on the time of day, location, and activity level using NLP to understand user context

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+ Generating Captions and Transcripts: Generate captions and transcripts for podcasts and other audio content, making them more accessible and engaging - Content Analysis and Organization:

+ Automatic Song Metadata Generation: Generate song metadata like genre tags, mood labels, and descriptions based on audio features and lyrics analyzed using NLP

+ Music Categorization and Classification: Categorize music by genre, subgenre, mood, and theme based on lyrics, artist descriptions, and audio features analyzed with NLP

+ Identifying Named Entities: Identify and classify named entities like artists, instruments, and locations mentioned in lyrics, enhancing search and organization

- NLP technologies are continually advancing, driven by machine learning and deep learning techniques These advancements enable computers to handle language- related tasks with increasing accuracy and sophistication

1.2.3 Reinforcement Learning (RL)

- The limitation of these collaborative filtering methods is that they rely on explicit or implicit feedback signals to know whether a user likes a playlist or not As a result, they will have difficulty considering other important factors (e.g., the coherence of the song's sound, the context of the music listening session, and the optimal presence of musical item sequences) ) This leads to a mismatch between offline metrics and user satisfaction metrics (which we want to optimize)

- For example, collaborative filtering has the ability to recommend playlists with high ratings but does not classify suitability for users as containing a mixture of adult and children's music This leads to user dissatisfaction Therefore creating a suitable and impressive playlist is a difficult task

- The field of Reinforcement Learning (RL) can be enhanced without explicit feedback signals Instead, RL can learn through interacting with users on Spotify Therefore, RL agents will interact and learn to increase user satisfaction in creating their own playlists

1.3 Current trends/ application in business

Spotify has applied the power of data to personalize customer experience Spotify uses data analysis, user profile mining, and customer experience personalization to launch new features for the paid version

Specifically, with current user data and analysis technology, Spotify implements a strategy including the following 4 main activities:

- Reorganize the music store and optimize the user experience of music playlists - Personalize playlists

- Localization

- Build campaigns connecting local artists with users

e Reorganize the music store and optimize the user experience of music playlists: To suggest the next song to users and play music automatically, Spotify's algorithm is created based on machine learning: This feature analyzes the songs in a certain playlist and tries to predict what music will come next Spotify's Al has studied millions of user-created playlists to understand what a good music playlist is, then provides suggestions that are most similar to user intent

Optimize the UX-UI of the music playback menu: Is an application service on a technology platform (Service as a software - SaaS), as well as other SaaS software Design that ensures optimal UX/UI is one of Spotify's priorities Therefore, the location of menus, buttons, control bars, tabs, pop-ups, etc are designed to be reasonable and most user-friendly for the user's experience

Creates a limited skip feature and only listens to music in random mode in the free version

Spotify's key differentiator is its degree of customization and expansion of musical knowledge offered to customers

Spotify just launched a collection of personalized playlists called Spotify Mixes Built around users' listening preferences, Spotify Mixes starts with each person's favorite songs and continually updates with recommended songs Spotify thinks you'll love

® Localization

Spotify has playlists tailored to your area To promote this feature, Spotify uses code on playlists and their ads are designed based on the playlists that have been shared in each region

To create a difference and attract users to use the paid version, Spotify offers a policy: when traveling abroad (not your home country), Spotify free version will no longer be available You will need to purchase a 14-day music package for your trip

@ Build campaigns connecting local artists with users

They developed a new strategy: supporting and uplifting local artists This strategy has created a connection not only in territory but also in musical thinking between listeners and musicians Local music ads are listed on public transit, airports, or near popular tourist destinations to increase local music awareness as well as Spotify awareness in that location Additionally, advertisements are also posted around local bars or cafes to help promote the artists to their public

1.4, Challenges and impact to different aspect of business

- The music streaming industry is dominated by large, multinational companies that account for the majority of the market share in this field Specifically, Spotify, Apple Music, Amazon Music, YouTube and Pandora are the five big companies They are rivals and there is always great competition in the global music streaming market According to the survey, they hold more than 74% of the global music streaming market share as of April 2020 The companies do not compete on price because they all offer basic services at mid-range prices average about 9.99 USD/month (see

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playlists and exclusive podcasts only available on Spotify Therefore, Spotify has the market share lead in the industry (see Picture 1)

We have reviewed the potential impact of these technologys on the music streaming app The music industry had rapid changes from the physical market to the digital market in the past decades The consumers download and stream music online and mobile during the digital dominant market These technologys can increase revenue, attract more consumers The positive impact to different aspect on Spotify only be possible if there are detailed consideration of the industry and careful understanding

Improved music discovery: By combining these technologies, Spotify recommends music that goes beyond user listening history, introducing them to new artists and genres they might enjoy

Personalized experience: Recommendations are tailored to individual preferences, taking into account user history, cultural context, and even mood Increased engagement: Users are more likely to discover and enjoy music they hadn't heard before, leading to longer listening sessions and higher retention

rates

Enhanced music understanding: NLP and RL help Spotify understand how music is perceived and consumed by its users, contributing to a deeper understanding of music preference and culture

Content Management: Recommendation: Identifies trending artists and genres, helping curators create relevant playlists and editorial content NLP anh RL : Analyzes music metadata and user feedback to categorize and label music accurately, enhancing optimize, search and discovery features, ensuring maximum visibility and engagement

Marketing and Advertising: Recommendation: Personalized recommendations drive advertising campaigns, NLP and RL: Analyzes user data and cultural trends to identify potential target audiences, maximize reach

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=> Overall, in terms of using recommendation algorithms, NLP and RL will have lasting effects on various aspects of the Spotify app Together, these technologies will create a diverse system that will help Spotify deliver personalized, flexible, and high- quality music services to users around the world These technologies create a more personalized, engaging and efficient platform, benefiting users, artists and the music industry as a whole These technologies create a more personalized, engaging and efficient platform, benefiting users, artists and the music industry as a whole

PART II: Technology implementation in business

2.1 Business brief overview

2.1.1 History

On April 23, 2006, Daniel Ek, the former CTO of Stardoll and Martin Lorentzon, a co-founder of Tradedoubler established Spotify as a Swedish audio streaming and music service provider [1] According to Ek, the name "Spotify" was mispronounced as a name that Lorentzon had yelled out Eventually, they combined the terms "Spot" and "Identify" to form their company's title Spotify was developed to address the issue of music piracy.Before music streaming services gained popularity, a lot of people downloaded music files illegally This was an increasing challenge for the whole music industry and served as the foundation for Spotify's establishment Daniel and Martin founded Spotify after realizing the enormous potential of music streaming

With its principal office in Stockholm, Sweden, Spotify offers a vast collection of over 100 million songs and five million podcasts from a wide range of record labels and media businesses On October 7, 2008, Spotify's services were made available to the general public (by invitation only) in Scandinavia, the UK, France, and Spain In the UK, Spotify began providing free, restricted access to its services in 2009 [2]

For the year 2019, Spotify made a profit for the first time ever Currently, Spotify is accessible in the majority of Europe, Africa, the Americas, Asia, and

Oceania It boasts over 574 million users, with 226 million of those being subscribers across 184 regions

2.1.2 VISION

“We envision a cultural platform where professional creators can break free of their medium’s constraints and where everyone can enjoy an immersive artistic experience that enables us to empathize with each other and to feel part of a greater whole.”

2.1.3 MISSION

“Our mission is to unlock the potential of human creativity — by giving a million creative artists the opportunity to live off their art and billions of fans the opportunity to enjoy and be inspired by it.”

2.1.4 OPERATIONS

Spotify operates on a "freemium" strategy, similar to other music streaming services This model states that it makes use of a freemium business model, providing an unlimited premium service for a membership price and a basic, limited, ad- supported service for free The service includes a number of features, including social sharing, offline playback, and high-quality audio It is accessible on multiple platforms, including desktop, mobile, and web

1 Draw a sizable user base by offering a free service

Users of Spotify's free music streaming service can choose from millions of songs in its catalog Users of the free service must listen to advertisements that help to partially fund the service, and it only offers basic functionality

2 Convert complimentary users to a high value offering

Spotify has had great success turning free users into paying customers In addition to more features, its premium subscription does away with advertisements 2018 saw 46% of Spotify's users become premium subscribers, who account for 90% of the service's earnings

3 Control churn and retention

The longer Spotify can keep users, the more money it can get from them over time— the user's lifetime value, or LT V—increases, similar to any other subscription model

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We refer to this as managing customer turnover Spotify's premium customer turnover rate dropped to a record-low 4.6% in the first half of 2019

4, Equalize the cost of premium and free

Record labels receive almost fifty-two percent of Spotify's revenue from each stream Sony, Universal, Warner, and Merlin are the four record labels that own more than 85% of the music that is streamed on Spotify In 2018, Spotify paid out €0.5 billion in royalties to free users and €3.5 billion to premium users, or 74% of total expenses 5 Use your premium revenue stream to finance the entire amount

The unique aspect of the freemium business model is that you have to be able to pay for both free and paid users In 2019, Spotify's user base reaches over 248 million, for which royalties are required Of those, 54% listen to music for free, albeit in moderation [3]

2.2 SWOT/ Market analysis/ Competitor research

2.2.1 SWOT e STRENGTHS 1 Customized Suggestions

Spotify's advanced algorithmic approach, which examines a tonne of user data to comprehend unique preferences and behaviors, is what powers its personalized recommendations The algorithm can provide highly personalized song recommendations and carefully curated playlists based on each user's taste by analyzing listening habits, playlists, and user-generated content

2 Social media integration that is seamless

Spotify creates a lively environment for music discovery and sharing by enabling users to share their favorite songs, playlists, and recently played tracks with friends and followers This not only makes it easier for users to discover new music through social networks, but it also promotes a sense of musical community as users converse, trade recommendations, and find out new artists together

3 Insights based on data

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Spotify's data-driven insights offer artists a detailed and insightful understanding of their fan base Through demographic analysis, musicians can learn more about the age, gender, and interests of their fan base and adjust their music and marketing tactics accordingly

4 Synchronization throughout platforms

The cross-platform synchronization feature of Spotify improves user flexibility and convenience When a user switches between devices during the day or moves from a smartphone to a laptop, Spotify picks up where they left off, saving them the trouble of looking for the last track or playlist they played

5.Upgraded Features for Accessibility

Spotify has demonstrated its dedication to accessibility by offering improved accessibility features By providing support for screen readers, people with vision impairments can use assistive technologies which speak the text on the screen to navigate and interact with the platform

Additionally, text resizing selections enable users with vision impairments to change the font size for improved legibility

e WEAKS

1 Inadequate payment to artists

Both artists and industry insiders have criticized Spotify's artist compensation model, raising issues with the comparatively low royalties that are given to artists Discussions regarding the equitable allocation of earnings in the music industry and the financial viability of musicians have been sparked by this pay gap

2 Insufficiency of Live Content

Users may have to rely on other platforms or services in order to stream live concerts and events or listen to live radio broadcasts due to Spotify's lack of live content Some users may find this fragmentation of content inconvenient if they are used to a single, comprehensive music streaming service

3 Restricted user individualization options

It is a disadvantage if they want more control over how they listen to music Even though Spotify's algorithms are made to offer tailored recommendations, some users

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might want more precise control—like the capacity to adjust their preferences or bar particular musicians or genres

4 Platform compatibility

Any technical problems can make it difficult for users to stream music or access their music library, such as server outages or app crashes Because of this dependence, users’ overall experience may be impacted by outages Or service disruptions Additionally, if Spotify stops supporting particular devices or operating systems, compatibility problems could occur, limiting users' options and requiring them to upgrade or find other music streaming services

e OPPORTUNITIES

1 Application of voice assistants and smart devices

Spotify can take advantage of the expanding market for smart home technology and satisfy users who want voice-activated interactions by integrating with well-known smart devices Through this integration, users can conveniently and intuitively listen to their favorite tracks, playlists, or podcasts by simply using voice commands 2 Experiences with Augmented Reality

Spotify has the potential to completely change the way people interact with music by utilizing augmented reality technology Users can explore more multimedia content related to the album and gain a deeper understanding of the musicians’ artistic vision by utilizing interactive album covers

3 Improved collaboration among artists

Spotify has an exciting opportunity to promote creativity and create original content that connects with users through enhanced artist collaboration As a result, Spotify can present unique and inventive musical collaborations that blur boundaries and combine genres, establishing the company as a platform that actively promotes and fosters artistic cooperation

4 Sharing music on social media

The social features of Spotify can be strengthened and user engagement increased with the aid of social music sharing As a result, users can collaborate to curate and add to a shared musical experience, encouraging a sense of community and teamwork

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e THREATS 1 Increasing license fees

Growing licensing fees pose a serious threat to Spotify's revenue and financial stability The price of obtaining licenses from record labels and other rights holders has gone up in tandem with the growth in popularity of music streaming

2 Data Privacy Issues

As Spotify grows and enters new markets, 1t may encounter various data privacy laws and compliance issues To ensure that user data is protected everywhere, it will need to have strong systems and procedures in place Spotify needs to make sure users have control over their private information and continue to be open and honest about its data handling policies in light of the growing scrutiny surrounding the data practices of tech companies

3 Illegal streaming and piracy

Another concern is illegal streaming and piracy Spotify's ability to make money from its services is hampered and the value proposition of paid subscriptions is undermined if users can readily obtain copyrighted music for free through illegal channels 4 Royalty rate discussions

Since Spotify depends on licensing deals with record labels and other rights holders, a large rise in royalties could have a big effect on the streaming service's bottom line 5 Fierce rivalry

Spotify's market position is seriously threatened by the fierce competition in the music streaming space With their large user bases and financial resources, rivals like Apple Music, Amazon Music, and YouTube Music are able to invest in marketing, original content, and technology improvements [4]

2.2.2 Market analysis

1 Determining customer segments:

The target market for Spotify is global, with the largest concentration of users in the USA and Europe Young adults in their Millennial and Gen Z years are the typical Spotify users, but there is also a sizable population of older adults (55 and over) who

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appreciate the music on the app.The average Spotify user is devoted, spending about 118 minutes a day listening to the service The platform has a higher female user base than male user base (56% female to 44% male)

2 Segmenting the Target Market for Spotify

Spotify analyzes segmentation data based on demographics, geography, behavior, and psychographics It will be able to target your audience more precisely as a result of its improved understanding and insights

- Demographic Segmentation

Even though the brand is well-liked by people of all ages, its appeal is greatest to younger audiences 29% of Spotify's user base consists of millennials, with 26% of them being younger than 24

In fact, among Americans between the ages of 12 and 34, Spotify was the most widely used online music service in 2020 On the other hand, just 19% of Spotify users are over 55 71% of Spotify's free audiences are under 35 years old, indicating that younger people are big fans of the platform's freemium subscription

- Geographic Segmentation

With over 159 million users in Europe compared to 111 million in the North America, 116 million in Latin America, and 551 million worldwide, Spotify's customer segmentation is highest in Europe The target market in the US consists of those who use the music streaming service frequently Over the past ten years, the percentage of US users who use the music app has increased to 28% weekly and 30% monthly

- Behavioral Segmentation

Most Spotify users find pleasure in the platform's customized experience Listening to playlists takes up over one-third of time on Spotify, with 36% of those playlists being made and shared with other users The success of Spotify extends beyond music streaming

- Psychographic Segmentation

The Millennial generation's attitude toward media consumption in general is reflected in Spotify's popularity: 60% of them believe that audio is the most immersive form of media For younger listeners, 14 to 35 years old, Spotify's enormous audio library with 70 million song titles and almost 3 million podcasts is extremely appealing This

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