Spotify- a music streaming app loved and used by millions of users daily. The app is quite successful in the music industry and is the largest on-demand music service globally. The latest technology like Big Data plays a tremendous role in making Spotify the leading music streaming app.
Presently, Spotify's net worth is more than $25 billion and has an enormous impact on the music industry by using data in the most dynamic ways. Spotify creates a playlist automatically according to the user choice; provide a personal touch- it all can be possible using Big Data Analytics.
The company strives to be entirely data-driven and enable users to make decisions based on data. By gathering and analyzing extensive amounts of listener data, Spotify can recognize rising user trends in real-time and quickly generate new features or services to gain on them. Hence, Big Data is essential
to grow and expand the development of the company. But the question that arises here is how Spotify uses Big Data to enhance the user experience?
Let us classify it into three parts: Importance of Big Data in Spotify, How Spotify collects data, and how they improve user experiences?
Importance of Big Data in Spotify:
Like we mentioned earlier, Spotify is in the top spot because of Big Data Analytics.
Due to its enormous playlist and its discovery weekly suggestion, people prefer Spotify. The app shows different songs and music with similar tastes to the users; eventually, that attracts the users to use the app more. It has generated over 600 gigabytes of data daily, and Data Science uses its algorithms to obtain data-driven insights and elevate customer experiences.
Moreover, Spotify drags the web constantly to watch for blog posts and related pieces of text and music. The app wishes users to enjoy their music and know more about their favorite artists and songs. With Big Data, Spotify analyzes and creates the top list of most played songs, current trend songs, and many others. It helps to keep the audience involved and is likely to spend more time on Spotify. Looking into that, Spotify made a decision and maintained on updating interested users.
How does Spotify collect the data?
To collect data, Spotify uses several languages and tools like Java, HiveHive, Apache Kafka, and many others. Those are for the primary purpose, for the accurate result- Spotify adopts Big Data and Big Data Analytics. The Spotify app User Interference is an insignificant surface of Machine Learning
and has become essential for the mobile app.
The data is used for three fundamental reasons- Playlists, information, and personal history. By gathering data for all, it helps Spotify to understand user behavior. It will give them the pattern and information about the music. Through this, they can make up a suggestion for the users. The history will show what they browse for, which song they have been listening to on the loop, which song or artist they avoid or skip, the like and dislike albums, and much more.
All of the above points are content-skeptic data- but by applying neural networks to forecast that information only from the audio signal. Later, the algorithms by Data Science
become self-aware and know what to perform next and what modification needs to do.
also helps to improve the performance of Spotify. It is practicing a whole collection of collaborative filtering techniques; a pattern has been identified in the data with this technique. Also, it provides potential representations of every user and every artist or song. That provides Spotify an extensive range of music. It is also the place where similar songs are gathered together with Big Data in Spotify, and users manage to listen to music only in specific areas of that plan.
How does Spotify improve user experience?
To improve the user experience of the customers; Spotify tries to choose an immense section of data produced. With this data, the app knows how to target the audience and acquire how to update their ad campaigns with more appealing content.
It has been conducted by the platform analyzing the information they have obtained regarding their listeners and then utilizing those insights to generate ads that carefully point at the platform’s target audience.
Spotify is not just about listening to music, but they provide podcasts, videos, and many others. They have a wide range of music- so the users can find old classic music, as well as new trendy songs. They even can share it on social media, share it with someone, and other features. By sharing the music, song, artist, or album with other people will gain more customers towards the app.
Big Data personalized the advertisement campaigns and adopted the data users want to listen to. The user engagement reaches the target audience and the possible potential users. The event set off the trend of decisive and well-responsive ads- that are utilized to announce the program. The Big Data in Spotify helps to gather data for the festive campaigns- which will help them to promote and encourage user experiences.
To Predict Next Effective Move
Spotify applies Big Data, not just for personalized services and support but also to involve users aside from music streaming apps. It practices big data for enjoyable activities on the app. With the advertisement on the broadcast to promotions on social media, Spotify never misses the chance to highlight itself.
The prediction by Data Science gives minor details to Spotify for making effective-decisions. It would be fair to say that they built a strategy on the basis of data gathered by Big Data Analytics.
The forecast might not be 100% accurate,
but it is nearly specific to obtain a big step decision.
According to Spotify, 55%
of users are in the age group of 16-40 years and have revenue of $10.8 billion in 2020.
Hence, that is how Big Data plays a role in Spotify. Not just this music streaming app, but Big Data and Artificial Intelligence are shaping the music industry in every other way. It develops creative methods and enriches the user experience. Sooner, the entire industry will function with Big Data and magnify their businesses.