Music Business

Artist Analytics: New Frontier For The Music Industry

In this new data-rich reality that artists find themselves in, utilizing data analytics has become an essential tool for achieving success in a music industry which is constantly evolving.

Guest post by Sergey BludovSVP, Media & Entertainment, DataArt

In today’s data-rich world, effectively utilizing high-quality artist analytics tools has grown into a vital component for success in the ever-changing music industry.

The digital environment provides musicians with direct access to massive quantities of information about their careers. From comprehensive details about streaming to granular data about their fans, video views, and so much more, the current tech climate drives a growing number of artists to take a DIY approach to the management of their music.

However, while technological advancements have increased the ability for artists to be directly involved in every aspect of their career, making sense of the plethora of available data to extract and apply the key points in productive ways can be a daunting task.

The complexity and intrinsic value of artist data create a new frontier for all levels of music companies. The quality of analytical insights combined with innovative concepts for the presentation and interpretation of data are central components of developing a competitive advantage for labels, distributors, and platforms in the quest to attract artists.

Using Analytics to Meet Business Objectives

As artist manager Don VanCleave once said, data is now currency for musicians as they attempt to climb the ladder to success. 

“[Data] is like a currency for you out there. We are constantly using global information to get more business, especially talking to music supervisors, advertising executives — if you’re trying to do a car ad in Belgium and you say ‘that’s our fifth biggest market, we’ve got this many listeners there’ and you can really break it down, you’ve got a more compelling argument to get the attention of whoever you’re pitching. Advertisers, brands, you name it.” – Don VanCleave, manager of Brent Cobb, Rainbow Kitten Surprise, and Moon Taxi, in an interview with Rolling Stone.

Companies in the music industry are increasingly using analytics tools and applying the gathered knowledge to meet the business objectives of the artists on their roster.

  • Tracking Performance and Artist Development: From tracking each time someone streams a song to identifying the geographical areas where their fanbase is growing quickest, analytics is vital when developing an artist’s career. Music companies gain a competitive advantage by possessing the expertise to effectively extract, analyze, and apply this data to its fullest potential.
  • Measuring Marketing Campaigns: One of the many benefits of the digital age is the expanded access to data. The music industry collects a staggering amount of information that can be used to measure the effectiveness of marketing campaigns in correlation with sales data, allowing companies to quickly adjust their strategies accurately to maximize ROI.
  • Discovering New Talent: A compelling online presence brings the industry to the artist, and vice versa. But it’s analytics that makes this process possible, allowing companies to discover new talent and new potential hit songs through recommendation engines and sophisticated discovery algorithms.
  • Fan Engagement: Artist analytics tools are capable of identifying an extraordinary number of connections between fans and the rest of their interests and lives, thereby greatly enhancing the ability to know an artist’s audience. Through understanding how fans discover new music and knowing their preferences, the possibilities for deep fan engagement grow exponentially.
  • For Artists: Knowledge is power. For artists, the music industry can be highly complex, making it difficult to be certain that their careers are running smoothly and fairly. Analytics help artists keep track of day-to-day business operations, which helps them to be sure that they’re being paid correctly at all times.

Building the Technology

It’s clear that artist analytics has grown into a highly valuable commodity in the music industry. But the quality of this technology varies greatly, as do the methods for presenting and interpreting this data to further an artist’s global reach and overall success.

At DataArt, we believe that there are two broad areas to explore when building the technology behind the insights.

1. Integrations

Modern analytics solutions receive data from a variety of DSPs, labels, distributors, retailers, charts, and more. Typically, the focus is on consumption and sales data (number of streams and downloads), while some also incorporate social media data and internet searches. Additionally, streaming platforms provide proprietary metrics that go beyond the number of streams or audience segmentation, such as skip or save rates, which reveal how often listeners skipped a particular track, saved it to favorites, or added a song to a playlist.

The main challenge that arises when building analytics technology is the lack of an industry-wide standard. Currently, providers use their own metrics and deliver data in a variety of formats, made even more challenging by the regular implementation of changes to the data feeds that they provide. 

These complexities result in the need for each provider to use a customized integration solution. Some industry leaders provide APIs that simplify the integration process, while others require an individual approach. When DataArt works on music analytics projects, our development teams typically create several stages of validation to convert incoming data feeds into a digestible format that’s used by each client system. 

Although we dream of the day when live data processing will be commonplace in the music business, the industry isn’t quite there yet. While some DSPs support daily updates, most providers take 2 or 3 days to process the data before it becomes available. It’s vital to keep this time delay in mind when building your analytics solutions. 

2. Data Warehousing

While analytics is only as good as the data that powers it, the ability to comprehensively reach this data is dependent on the underlying infrastructure. Today’s data strategies require superior technological tools to accommodate the growing demand for customized analytics and real-time reporting.

The needs for a data warehouse depend on several aspects of the business operations, including cost-effectiveness, scalability, security, and resource management. Just a few years back, Amazon Redshift was dominating the field, but we now assist our clients with implementing or migrating to more agile alternatives, such as Snowflake or BigQuery.

The increasing adoption of data science by music companies often leads them to work directly with data lakes, either in conjunction with data warehouses or bypassing them entirely. Data lakes allow analytics teams to go beyond pre-defined queries and pre-defined data types, while additionally providing faster results than what’s possible from a traditional data warehouse. Although it’s unlikely that data lakes will replace data warehouses, the additional tools are becoming crucial, with the query services companies Presto and Amazon Athena gaining popularity for analyzing data when using data lakes.

The rapid evolution of the music industry goes hand-in-hand with swift advancements in the technological ecosystem. To achieve the utmost success, today’s music industry players must think of themselves as technology companies that provide the tools to facilitate modern artist development from the first moment of discovery to the top of the global charts.

What are your thoughts about artist analytics as a new frontier for the music industry? Please share your opinions with me at

Sergey Bludov is a Senior Vice President of Media and Entertainment at DataArt, in charge of key client relationships, building exceptional teams and ensuring execution and delivery of high-profile projects for the music business and entertainment industry.

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