Question

Comprehensively discuss how Spotify attempts to provide a total customer experience (CX) (not customer service) with its customers.

Identify the factors that should be considered in developing a customer profile for Spotify.

Answer 1

Factors engaging Spotify to its customers.

1. They use machine learning and identify the users before the users can find it. They have a good set of data scientists and user researchers, who work together to understand what users are doing on the platform and why in order to serve up more of what they like. Having those two things together gives us a really well-rounded, holistic view of our users, what their wants and needs are, and what they’re doing.

2. COLLABORATIVE FILTERING

Collaborative filtering is the most heavily weighted and primary strategy Spotify uses to recommend music to individual listeners. At a basic level, Spotify looks at the songs you’ve listened to, favorited, and added to your individual playlists and cross-references that list with lists from other customers. If you and another listener have a 90% overlap in the music you both have listened to and favorited, chances are you’ll like the other 10% of music the other customer has in their library. Spotify is more likely to recommend music from listeners with similar tastes—someone with a 90% overlap versus someone with only a 10% overlap.

3. NATURAL LANGUAGE PROCESSING

Natural language processing (NLP), at the highest level, is a branch of artificial intelligence (AI) where a computer is trained to understand “natural” or “human” speech. In Spotify’s case, this refers to song metadata, blog posts, and news articles. Spotify scours the web for text content that mentions artists, songs, and adjectives used to describe each. By comparing this to “natural language” written about other songs and artists and analyzing artists that are often referenced together, machine learning can determine similarities and differences between different songs and artists. Using a similar matrix algorithm as collaborative filtering, Spotify can ascertain which songs and artists are similar and could be recommended together.

Outside of Spotify, NLP is also leveraged by chatbots. Chatbots use NLP to understand text interactions with customers and determine whether the chatbot can handle the next steps or the interaction needs to be escalated to a human. This technology is often used by retail companies looking to provide on-demand support for customers on their websites.

4. AUDIO ANALYSIS

The first two techniques Spotify uses for recommending music do not use any analysis of the music itself. Audio analysis is the third and final way Spotify enhances its already-thorough recommendation model. This technique is how Spotify can recommend brand new music to its listeners. While collaborative filtering and NLP rely on other people listening and finding content on a specific artist or track, audio analysis can find similar music based on how the track sounds.

Using an AI-based technology similar to facial recognition, Spotify can analyze individual music files using convolutional neural networks (a form of deep learning). By analyzing markers in audio files that identify different themes in the music, Spotify can group similar music styles and artists by using hundreds of filters such as tempo, loudness, or specific musical keys, and use this data to enhance their recommendation model.

Spotify analyzes excerpts from each song against filters that pick up harmonic content and determine predictors for how the songs sound. Engineers at Spotify are always working to train these filtering models and to group, at even a higher level, songs based on larger concepts such as harmonicity, chords, and chord progressions.

Audio analysis can also be used outside of the music industry. It is possible to use similar technologies to analyze customer sentiment in a customer service capacity. The tone, speed, and amount of stress in a customer’s voice can be used to route calls in a call center to an appropriate audience. For example, if a customer seems particularly agitated, the call could be directly routed from an automated system to a supervisor to help mitigate the issue.

5. USING DATA TO IMPROVE CUSTOMER EXPERIENCE

Spotify is one of many companies using customer and outside information to improve experiences for their customers. For their “Discovery Weekly” playlist, Spotify is only using a few of the many possible techniques available to make recommendations for its users. With improving technologies and analysis techniques, data-driven customer experience will become the norm across most, if not all, companies in the years to come.

Factors to be identified to develop a customer profile:

1. Spotify has positioned itself uniquely in this expansive market in order to target two major segments: students and young business professionals. These two segments possess specific characteristics that make them desirable, lucrative targets for Spotify’s service.

2. Psychographic/Lifestyle

For this younger audience of students, personalization is key. A major characteristic of the Generation Y demographic is the idea of extreme customization of 14 products and services. This goes to explain why Spotify is such a big draw for those high school and college-aged students. The ability to listen to their favorite music on demand, construct playlists, and switch genres at whim achieves this audience want. In addition, Spotify’s notion of music listening as an experience that can be coupled with other activities, such as doing homework, working out, partying, and hanging out with friends, makes it all the more accessible to the touch-and-go, hustled lifestyle of this young demographic. This makes Spotify less of a product, and more of an element of the overall experience, a major draw for Generation Z members.

3. Many demographic factors play in the student segment's attractiveness. First and foremost, is the obvious trait of age. The students that Spotify targets are somewhere around the high school and college-age range. As seen in the chart below, this age demographic is Spotify’s most lucrative and accounts for the majority of its users. College-aged students -- individuals from 18-24 years of age -- serve as Spotify’s largest segment of users, followed closely behind by high school-aged students -- individuals from 13-17 years of age. In all, the student segment accounted for just under half of all of Spotify’s users in 2015 -- roughly 47%.

4. Personalization is one of the main tenants of Spotify, as the entire customer experience is centered around allowing people to create playlists to fit any mood they are in.