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If you’ve ever heard a song playing and wondered, “What song is this?”, you’re not alone. Music identification apps like Shazam solve this problem instantly by analyzing a short snippet of audio and matching it to a vast song database.

With the rise of music streaming and AI-powered technologies, music discovery has become easier than ever. If you’re wondering how to make a music identification app like Shazam, the process involves advanced audio recognition, AI-based algorithms, and seamless integration with music streaming services. In this article, we will walk you through the essential steps to develop a Shazam-like app, explore the technology behind it, and discuss monetization strategies to make it profitable.

Creating a music identification app isn’t just about copying an existing model. You must understand the music industry, your target audience, and the gaps in the market to build an app that stands out. But before we dive into the development process, let’s first clarify: What is Shazam? What is its purpose, history, and revenue model?

What is Shazam? Music identification apps

Shazam is one of the most popular music identification apps that allows users to identify songs by simply listening to a short audio clip. The app matches the recorded snippet against a vast music database and provides details about the song, including the title, artist, and album.

The Evolution of Shazam: From a Simple Idea to a Global Music Discovery Platform

According to Wikipedia, Shazam Entertainment Limited was established in 1999 by Chris Barton, Philip Inghelbrecht, Avery Wang, and Dhiraj Mukherjee. Barton and Inghelbrecht, both MBA students at the University of California, Berkeley, joined forces with Mukherjee, who was working at a London-based internet consulting firm, Viant. To bring their vision to life, they enlisted Avery Wang, a digital signal processing expert with a Ph.D. from Stanford University.

Shazam initially launched in the UK in 2002 under the name “2580”, a reference to the shortcode users dialed from their mobile phones to identify songs. The process was simple—users called the number, and after 30 seconds, the call would disconnect automatically. Shortly after, they would receive a text message containing the song title and artist name. Over time, hyperlinks were introduced in these messages, allowing users to download the identified track online.

In 2004, Shazam expanded to the US, partnering with AT&T Wireless and Musicphone to offer its service. Initially, the app was free, but AT&T later announced plans to charge $0.99 per usage. By 2012, Shazam had amassed over 225 million users, solidifying its place as one of the most popular iPhone apps at the time.

Recognizing Shazam’s massive impact on the music industry, Apple acquired the company in 2018 for an estimated $400 million, integrating its powerful music recognition technology into Apple’s ecosystem, including Siri and Apple Music. Today, Shazam remains a dominant force in music discovery, continuously evolving with new features and integrations.

The Purpose Behind Shazam

Shazam was created to bridge the gap between music lovers and song discovery. Before Shazam, users had no way to identify a song playing in a café, on the radio, or in a movie. The app changed the music industry by making music recognition easy and accessible.

Shazam’s Market Share in the Music Industry

Now that we’ve explored what Shazam is, its history, and how it operates, let’s take a brief look at Shazam’s market position in the music industry before diving into the overall music app industry statistics and revenue projections for 2025.

Shazam has grown into a global leader in music identification, with impressive user engagement metrics:

• In 2016, Shazam surpassed 1 billion total downloads.
• By 2020, users were identifying 20 million songs daily using the app.
• As of December 2023, Shazam has over 300 million monthly active users worldwide (Source: D3 Harvard).
• According to a 2020 report from Music Business Worldwide, Shazam had already reached 200 million monthly active users globally.
• In 2018, Shazam reported 478 million active annual users, up from 400 million in 2017.
• According to Musically the latest milestone for Apple’s Shazam is 100bn song recognition in 2024.
• A 2025 study from Musically revealed that artists featured on Shazam’s list for 2024 saw their Shazam tags increase by 34% and their streams on Apple Music grow by 146%.

With such substantial numbers, Shazam remains a key player in music discovery, influencing how listeners engage with music and helping emerging artists gain visibility.

Global Music App Industry Statistics and 2025 Revenue Report

After analyzing Shazam’s market dominance, let’s shift our focus to the overall music app industry and its projected growth in 2025 and beyond.

The global music app market has seen rapid expansion, driven by music streaming services, AI-driven recommendations, and mobile technology advancements. Here are the latest industry insights and revenue forecasts:

1. Music App Market Size and Revenue Growth

• According to Market.us, the global music app market is expected to reach $66.5 billion by 2034, up from $33.2 billion in 2024, with a CAGR of 7.20% from 2025 to 2034 (Source: Market.us).
• The music streaming market alone is valued at $17.5 billion globally and continues to expand.
• A report from The Business Research Company states that the music mobile apps market will grow from $7.11 billion in 2024 to $8.04 billion in 2025, representing a CAGR of 13.0%. By 2029, it is projected to reach $13 billion with a 12.8% CAGR (Source: The Business Research Company).

2. Growth in Paid Music Streaming Subscribers

• Over 600 million users worldwide have paid subscriptions to music streaming platforms, showing the increasing demand for premium music experiences.
• The global music streaming market is projected to be valued at $47.06 billion in 2025, growing to $143.89 billion by 2032, with a CAGR of 17.3% (Source: Coherent Market Insights).

How do Modern Music Mobile Applications Work? A Comprehensive Guide

Music has become more accessible than ever, thanks to modern music mobile applications. Whether it’s a streaming service like Spotify, a music recognition app like Shazam, or a music creation tool like GarageBand, these apps use advanced technologies to deliver a seamless and personalized user experience.

In this section, we will explore how modern music mobile applications work, covering their key components, essential features, and the technology behind them

1. Key Components of Modern Music Mobile Applications

Music mobile applications consist of various interconnected components that enable music discovery, streaming, identification, and interaction.

1.1 Cloud-Based Streaming Technology

Music streaming platforms like Spotify, Apple Music, and YouTube Music rely on cloud computing to store and deliver millions of tracks to users instantly.

How It Works:

• When a user selects a song, the app fetches the audio data from cloud servers.
• The song is streamed in compressed formats like AAC, OGG, or MP3 to minimize buffering and ensure smooth playback.
• Many apps use adaptive streaming, which adjusts audio quality based on internet speed.
• Offline mode allows users to download encrypted songs for playback without an internet connection.

1.2 AI-Powered Music Recommendations

Artificial Intelligence (AI) and Machine Learning (ML) are used to personalize user experiences by analyzing their listening habits and preferences.

How It Works:

• AI algorithms analyze data such as play history, likes, skips, and searches.
• Users are categorized into different listener groups based on their music taste.
• The system generates personalized recommendations, such as Spotify’s “Discover Weekly” and Apple Music’s “For You” playlists.

1.3 Music Recognition Technology

Apps like Shazam, SoundHound, and ACRCloud use advanced audio recognition technology to identify songs based on short audio clips.

How It Works:

• The app records a short audio sample when the user taps the “Identify” button.
• The sample is converted into a spectrogram, which visually represents sound frequencies over time.
• The spectrogram is compared with a large database of song fingerprints.
• If a match is found, the app displays song details (title, artist, album, release year, etc.).
• Many apps allow users to save identified songs and play them on streaming services.

1.4 Background Music Recognition

Modern music identification apps don’t always require user input. They can automatically recognize songs playing in the background while the user is watching a movie, listening to the radio, or attending a concert.

How It Works:

• The app listens to ambient sounds in the environment.
• Using AI-based filtering, it isolates and analyzes any music playing in the background.
• If a song is detected, it identifies the track and notifies the user.

1.5 Real-Time Lyrics Display

Music apps integrate synchronized lyrics to enhance the listening experience. Platforms like Apple Music, Musixmatch, and Spotify display real-time scrolling lyrics.

How It Works:

• Lyrics are synchronized with the audio playback using time-coded text files.
• As the song plays, the app highlights the current line of lyrics.
• AI algorithms can adjust lyric timing based on tempo changes or live versions of songs.

1.6 Social Media Integration

Social sharing is an essential feature of modern music apps, allowing users to share their favorite songs, playlists, or identified tracks.

How It Works:

• Music apps connect with Facebook, Instagram, Twitter, TikTok, and Snapchat via APIs.
• Users can generate shareable links for playlists, albums, and individual songs.
• Some apps allow direct sharing of song clips, lyrics, or album covers.
• Platforms like Spotify and YouTube Music enable collaborative playlist creation.

1.7 Multi-Language Support

To cater to a global audience, modern music apps support multiple languages, making them accessible to a broader user base.

How It Works:

• The app detects the user’s language settings and adapts the interface accordingly.
• Lyric databases and song metadata are translated into different languages.
• Some apps allow automatic lyric translation for international songs.

1.8 Offline Mode for Identified Songs

While streaming requires an internet connection, many modern music apps allow users to save identified songs for offline access.

How It Works:

• The app stores a history of identified songs within the user’s library.
• Users can listen to song previews or download the full track (if they have a subscription).
• Offline access is usually restricted to premium users or those who enable cloud syncing.

1.9 Push Notifications for Music Trends

To keep users engaged, music apps send real-time notifications about trending songs, artist updates, and personalized recommendations.

How It Works:

• The app tracks user preferences and listening behavior.
• AI-driven algorithms suggest new releases and trending songs.
• Notifications alert users about concerts, album launches, or personalized recommendations.

2. Technologies Behind Modern Music Identification Apps

2.1 Digital Signal Processing (DSP)

DSP is the foundation of audio recognition and enhancement. It is widely used in music identification, equalizers, and noise cancellation.

2.2 Cloud Computing

Music apps use cloud computing for storing user data, music libraries, and playlists, eliminating the need for large local storage.

2.3 AI and Machine Learning

AI and ML power recommendation engines, music recognition, and trend analysis in modern music apps.

2.4 Blockchain for Music Rights Management

Blockchain is being used to manage royalties and protect artist copyrights by ensuring transparent and secure transactions.

How to Make Shazam Like App for Android a Music Identification App? Step-by-Step Guide

Creating a music identification app like Shazam requires a deep understanding of audio recognition technology, AI algorithms, and database management. Below, we’ll break down the entire development process step by step, covering market research, technology stack, features, monetization strategies, and deployment.

Step 1: Market Research & Competitive Analysis

Before developing your app, conduct in-depth research on:

• Market trends: Understand the latest advancements in AI-driven audio recognition and how modern music streaming services integrate identification features.
• Target audience: Identify who will use your app—music enthusiasts, DJs, radio listeners, or casual users.
• Competitor analysis: Analyze Shazam, SoundHound, Musixmatch, and ACRCloud, identifying their strengths, weaknesses, and gaps.
• Monetization opportunities: Explore potential revenue streams, such as ads, affiliate marketing, or premium subscriptions.

Step 2: Define Your Business Model & Monetization Strategy

To make your app profitable, consider the following revenue models:

• Advertising: Display banner/video ads within the app.
• Affiliate Marketing: Earn commissions when users stream identified songs on Spotify, Apple Music, or YouTube Music.
• Subscription Plans: Offer premium features like ad-free experience, offline recognition, or exclusive music insights.
• Partnerships with Music Labels: Provide data analytics on trending songs to record labels and artists.

Step 3: Choose the Right Technology Stack

To build a powerful music recognition app, you’ll need AI, machine learning, and cloud storage. The best technology stack includes:

Backend Development:

• Programming Languages: Python, Node.js, or Java
• Frameworks: Django, Express.js, or Spring Boot
• Database: Firebase, MySQL, or MongoDB
• Cloud Storage: AWS, Google Cloud, or Microsoft Azure

Frontend Development:

• Mobile Frameworks: React Native or Flutter (for cross-platform development)
• UI Design Tools: Figma, Adobe XD, or Sketch

Audio Recognition & AI:

• APIs: ACRCloud, Gracenote, or ShazamKit (for iOS)
• Machine Learning: TensorFlow, PyTorch, or Google’s ML Kit
• Spectrogram Analysis: Use Fast Fourier Transform (FFT) to convert audio signals into visual spectrograms for fingerprint matching.

Step 4: Design the App UI/UX for a Seamless User Experience

A great UI/UX design is crucial for user retention and engagement. Your app should have:
A. A clean and simple interface
B. One-tap song recognition
C. Dark mode & customization options
D Search functionality for songs, artists, and albums

Use Material Design for Android and Human Interface Guidelines for iOS to create a visually appealing and user-friendly interface.

Step 5: Develop Core Features of Your Music Identification App

The key to a successful app like Shazam is its feature set. Some must-have features include:

1. Real-Time Song Recognition

• Use AI-powered audio fingerprinting to analyze a short audio clip and match it with a music database.
• Implement machine learning algorithms to improve accuracy.

2. Lyrics Display & Music Metadata

• Provide real-time lyrics synchronization using Musixmatch API.
• Display song details, album cover, artist bio, and release year.

3. Music Streaming Integration

• Allow users to stream identified songs on platforms like Spotify, Apple Music, and YouTube.

4. Offline Song Identification

• Enable users to record a song and recognize it later when they’re online.

5. User History & Playlists

• Save previously recognized songs in a personalized library.
• Allow users to create custom playlists and share them with friends.

6. Voice Command Support

• Integrate with Google Assistant & Siri for hands-free song recognition.

7. Social Media Integration

• Let users share identified songs on platforms like Instagram, TikTok, and Twitter.

Step 6: Integrate an Audio Recognition Algorithm

The core technology behind Shazam is audio fingerprinting. Here’s how it works:

• Step 1: The app captures a 5–10 second audio clip.
• Step 2: It converts the clip into a spectrogram using the Fast Fourier Transform (FFT) method.
• Step 3: The app extracts unique patterns (fingerprints) and matches them with a pre-existing database.
• Step 4: If a match is found, the song details are retrieved and displayed to the user.

Use open-source fingerprinting libraries like Chromaprint or Echonest for implementing this feature.

Step 7: Test Your App for Performance & Accuracy

Thoroughly test your app before launching to ensure:
A. Fast and accurate song recognition
B. No bugs or crashes
C. Compatibility across Android & iOS devices

Perform unit testing, beta testing, and performance testing using tools like:

• Firebase Test Lab
• TestFlight for iOS
• Appium for automated UI testing

Step 8: Launch & Market Your App Effectively

Once your app is ready, deploy it on the Google Play Store & Apple App Store.
Promote it using:
1. App Store Optimization (ASO) – Optimize keywords & descriptions.
2. Social Media & Influencer Marketing – Collaborate with music bloggers & influencers.
3. SEO & Content Marketing – Write blogs about music recognition & app features.

Step 9: Monetize & Scale Your Music Identification App

After launching, focus on monetization & scalability. Here’s how:

• Freemium Model – Offer free recognition but charge for premium features.
• Subscription Plans – Provide exclusive content & ad-free experiences.
• Data Licensing – Sell music trend data to record labels & streaming services.

Building a music identification app like Shazam requires cutting-edge AI, robust databases, and seamless UI/UX. By following this step-by-step guide, you can develop a feature-rich, profitable, and scalable music recognition app.

Cost to Develop a Music Identification App Like Shazam

The total cost depends on various factors, including features, complexity, and development location.

Development Stage	Estimated Cost (USD)
UI/UX Design	$5,000 – $15,000
Backend Development	$10,000 – $50,000
Frontend Development	$15,000 – $30,000
Audio Recognition Algorithm	$20,000 – $100,000
Third-Party API Integration	$5,000 – $15,000
Testing & QA	$10,000 – $20,000
Deployment & Maintenance	$3,000 – $10,000
Total Estimated Cost	$70,000 – $250,000

Monetization Strategies for a Music Identification App like Shazam

Monetizing a music identification app requires a multi-faceted approach that balances user experience with revenue generation. Below are the key monetization strategies that can maximize the earning potential of a music recognition app.

1. In-App Advertising

Advertising is one of the primary revenue streams for music identification apps. Various ad formats can be integrated to generate income:

• Interstitial Ads: Full-screen ads displayed between song identifications or transitions that maximize visibility and revenue.
• Banner Ads: Small, non-intrusive ads placed within the app interface.
• Video Ads: Rewarded video ads where users watch advertisements to unlock premium features or additional song identifications.
• Contextual Ads: AI-driven ads that match the user’s listening habits, improving engagement and ad relevance.

2. Subscription Model

A freemium model allows users to access basic features for free while offering premium benefits through subscriptions:

• Freemium Model: Users can use the app for free with limitations (e.g., ads, limited song recognitions) and upgrade to a premium plan for an ad-free experience.
• Premium Subscription: Users pay a recurring monthly or annual fee to access exclusive features such as high-speed recognition, offline mode, or curated playlists.

3. In-App Purchases

Offering microtransactions within the app enhances user experience and generates additional revenue:

• One-Time Purchases: Users can pay to remove ads, unlock unlimited song recognition, or access exclusive artist content.
• Premium Song Credits: Users can purchase credits to recognize a set number of songs beyond the free daily limit.
• Offline Song Storage: Users can pay to store recognized songs within the app for offline access.

4. Affiliate Marketing & Referral Programs

Integrating with streaming and music purchase platforms allows the app to earn commissions:

• Affiliate Links: When users identify a song, they can be redirected to purchase or stream it on platforms like Apple Music, Spotify, or YouTube Music. The app earns a commission for every successful referral.
• Referral Partnerships: Partnering with music platforms to share revenue from premium subscriptions gained through the app.

5. White-Label Solutions

Licensing the music recognition technology to third-party apps or businesses can be a lucrative revenue stream:

• Integration in Other Apps: Fitness apps, social media platforms, and video streaming services can integrate the technology for a seamless music recognition experience.
• API & SDK Licensing: Businesses can pay to access the app’s recognition engine for their own applications.

6. Data Monetization

Music recognition apps collect valuable data on listening habits, trends, and user preferences, which can be monetized in various ways:

• User Data Licensing: Selling anonymized user data to record labels, marketers, and streaming services for audience insights and targeted advertising. According to an article from Harvard (source: d3.harvard.edu), Shazam analyzes what songs and artists users identify, and how frequently, to predict emerging hits before they gain mainstream traction. This data is valuable for industry players who use it to optimize marketing strategies and talent scouting.
• Predictive Analytics for Business Insights: Shazam’s ability to forecast popular artists and tracks before they chart allows businesses to leverage this data for profit. For example, the live concert industry, expected to be a $29 billion market in 2023, benefits from insights on trending artists to plan tours and events strategically.
• Personalized Ad Placement: Using AI to analyze listening behavior and display targeted advertisements for artists, brands, and concerts, increasing engagement and ad revenue.

7. Sponsored Content & Artist Promotions

Artists and record labels can pay for promotional placements inside the app:

• Sponsored Playlists: Curated playlists featuring upcoming artists and new releases.
• Featured Song Promotions: Highlighting specific tracks for increased visibility.
• Exclusive Content: Limited-time releases, behind-the-scenes videos, and artist interviews available only to app users.

8. Sales Integration: Tickets & Merchandise

Music recognition apps can serve as a marketplace for:

• Concert Tickets: Direct ticket purchases for live events and concerts of identified artists.
• Music Merchandise: Selling artist merchandise such as vinyl records, posters, and apparel.

9. Direct Artist Payments & Fan Contributions

Allowing users to support artists directly fosters a stronger connection between musicians and fans:

• Tipping System: Users can donate to their favorite artists through the app.
• Revenue Sharing: A portion of subscription fees can be allocated directly to artists based on recognition frequency.

Final Thoughts

Building a music identification app like Shazam requires a blend of advanced AI, seamless UI/UX design, and strategic monetization. With the global music industry growing rapidly, there is ample opportunity to innovate and create a unique app that stands out. Whether through real-time song recognition, AI-powered recommendations, or social media integration, a well-developed music recognition app can enhance music discovery for millions of users.

By leveraging the right technology stack, focusing on user engagement, and implementing smart revenue strategies, you can turn your app into a successful and profitable venture. The future of music identification is evolving, and with the right approach, your app could become the next big name in digital music discovery.