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  /  Artificial Intelligence   /  Spotify #2020wrapped: How AI is Enabling Spotify’s Customer Engagement?
Spotify AI deep learning Spotify #2020wrapped NLP

Spotify #2020wrapped: How AI is Enabling Spotify’s Customer Engagement?

Through the use of artificial intelligence, Spotify provides a personalized experience to the customers.

It is a norm for Spotify to release the yearly round-up list of songs, artists and podcasts list, so that top trends can be presented. This year was no different. On December 1st, Spotify released its 2020 “Wrapped-up” list, which displays the trends that shaped streaming this year. Spotify is a renowned streaming platform that provides customized music to its clients. Spotify uses artificial intelligence and machine learning to deliver a more personalized service to its customers.

Spotify is a data-driven service, which provides a customized experience to the user based on big data analytics and artificial intelligence. Every time the user logs in to their Spotify account for streaming music, data is generated. The data is accumulated based on the song preference, keyword preference; most songs streamed, most podcasts streamed, most podcast channels followed and clicked, keyword data, geographic location, and artist preferred or followed amongst others. It is the use of AI, which makes Spotify stand out from other music streaming platforms such as Jiosaavn and Gaana.com.

The AI model in Spotify analyses the pattern behind the historical big data for formulating a smart strategy in customer engagement.

 

Collaborative filtering to recommend songs 

Just like Netflix and Google, Spotify works on the concept of collaborative filtering. Collaborative filtering is a part of the recommendation engine that uses similarities between different users and items to provide recommendations. For example, Puerto Rican rapper Bad Bunny claimed the top stop of the most-streamed artist this year, with more than 8.3 billion streams this year. Spotify used its collaborative filtering framework to analyze the number of times this artist has been listened by the user before charting the most streamed artist list.

 

Understanding the Customer using NLP

Furthermore, through its natural language processing model, Spotify analyzes what the consumer actually wants and improve its services. Natural Language Processing is a subset of AI that uses text analytics to decode the human language. With the help of natural language processing, Spotify analyzes the blog posts articles and the countless discussion platforms over the internet, to decode what consumers think about a particular song and artist. The decoding gets done by analyzing the words and phrases, the type of adjectives used for the artist and the number of time a particular song, podcast or artist is recommended or rated. For example, if a blog, describes artist The Weeknd’s song “Blinding Lights”, as phenomenal, the NLP algorithm will pick up the word ‘phenomenal’ and will categorize it amongst the songs that are highly streamed.

 

Deep Learning and Predictive Analytics for Predicting Customer’s Mood

Spotify leverages deep learning algorithms and predictive analytics to predict what the user would want to listen next. Deep learning is a subset of machine learning, which processes and identifies patterns from structured and unstructured data.

The deep learning algorithms are trained in a manner that it picks the first and second syllable, for recommending the song, artist or podcast to the user. In fact, this magic is not confined to be used by only Spotify, but Google, Netflix and Amazon Prime are also leveraging deep learning algorithms for better user experience. Deep learning is the reason why every time a user types the initials, and the song is presented to them on a silver platter.

Predictive Analytics is the use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. Predictive Analytics model in Spotify functions based on the type of songs and the genre mostly streamed by the user. For example, if the user has often streamed heavy metal and rock music, then predictive analytics algorithms analyze the pattern and recommend similar songs to the user. Predictive Analytics is also used in analyzing the pattern of similarity in customer preference so that the top trends chart can be made.

 

Wrapping up

Through the use of artificial intelligence, Spotify provides a personalized experience to the user. Spotify’s strategy has made it to be the most streamed app amongst the user. Currently, Spotify’s global user base is over 350 million and has an increase in revenue by 14% year-on-year basis to 1.97 billion euros.

The global music streaming market is poised to grow by US$7.47 billion during 2020-2024 at a CAGR of 19% during the forecast period.

So, go and get your music for every Mood!