Contact Us
Cirium - Our data science

Industry outlook

AI in the music industry: what aviation executives can learn

March 4, 2020

We love to wax lyrical about the transformative power of data. Every innovation elevating operations in the aviation industry is […]

We love to wax lyrical about the transformative power of data. Every innovation elevating operations in the aviation industry is music to our ears. We’re always seeking ever smarter ways of deploying analytics to mine for deeper insights so our customer can better integrate operations. We expect this will strike a chord with all businesses seriously invested in digital transformation.

The music industry is arguably one of the most exciting arenas to watch. In fact, it’s exciting to see how it has led the way for so many of the innovations in machine learning we are now seeing impact air travel and aerospace. There’s also much we can learn from how the music business has tapped into inventive ways of broadening its analytics capabilities. Here we explore how music moguls and aviation executives can be singing the same tune.

The power of data and analytics has the music industry flying high

The way in which big data has transformed and disrupted the music business is awesome. We now see record labels and distributors successfully using layers of analytics to predict and enhance performance. Their proof of progress provides exciting and valuable insights for us all. In summarizing some of their successes, the similarities to the needs of air travel and aviation are evident.

Both industries have similar strategic planning needs where data analytics can help:

  • Get a more complete picture by linking together new details across the data
  • Take action sooner by identifying emerging trends
  • Anticipate market behaviors by focusing on targeted segments

The four layers of analytics – descriptive analytics, diagnostic analytics, predictive analytics and prescriptive analytics – that the most successful brands in the travel industry deploy to their advantage, can also be used by music moguls to turn one hit wonders into rock stars…

How did Ed Sheeran, Dua Lipa, Billie Eilish, and Lewis Capaldi, to namedrop just a few, rise from virtual unknowns to international stardom? What kind of magic transformed rappers Stormzy and Logic from cult heroes to artists who sell-out major league arenas? How do music impresarios spot the superstars of tomorrow?

We can see they have stitched together a more complete picture of consumer interests by turning every interaction with music into an opportunity to gather data. This industry has also pushed the frontier of data granularity. Forget long stretches of touring, promos and celebrity love-ins – the industry known for hit singles, is now known for hitting the mark down to the individual’s personal taste. Whether you ask Alexa to build you a personal playlist, or you follow Spotify’s lead, AI is developing a deeper understanding of what you like. As defining tastes becomes ever more niche, the number of music genres – and specifically sub-genres – has increased exponentially. Every major music genre from R&B to rock, pop and country music now has a multitude of ‘tribes’ who follow specific sub genres of styles and vibes. All of this has evolved as a direct result of the new ability to analyse the data points freely, and regroup music in new ways. Recommended niche playlists are proof of targeted segmenting.

And since digital streaming disrupted how the music industry makes its money beyond all recognition, digitization has delivered a new currency of knowledge that’s priceless.

What makes a hit song?

In addition to all the obviously necessary ingredients (great voice, lyrics, rhythm and beat), there’s always that more intangible element or ‘X-Factor’ that can make or break an artist’s fortunes. And when it comes to getting under the skin of what makes a record and the artist’s performance really pop, small wonder that AI knows best.

Numerous start-ups have entered the marketplace offering smart apps designed to weed out the flops and hit on tunes destined to be top of the charts. Among the leaders of this pack, Samply is the company making the biggest noise. Set up by MIT grad student, Justin Swaney, Samply combines music and machine learning into a new technology to help producers find the perfect sound. Its tool uses intelligent algorithms and a convolutional neural network to analyze audio waveforms.

Similar to airline business planning and operations, music labels are looking to discover the next great hit. Using big data trending to pinpoint successes. Put simply, AI can predict and help digital music producers to create and mesh the catchiest numbers, pulling data from a library of sounds.

What about changing tastes?

Just as you tap into the zeitgeist, the winds of fashion take another direction… While some elements of musical success are evergreen, every era has its signature beat. The big game changer is that producers can also use smart data to build machine learning applications indicating which way the wind is blowing. This gets down deep into the layer of analytics that’s the most mind blowing of all: human-centered analytics. Funnily enough, it’s something we’ve written about before.

Human-centered analytics get us closer to real behaviors and trends. Worried about trusting the data to lead decisions? AI-based record label Snafu isn’t. The first AI-based record company, Snafu Records claims to able to spot the next big star long before even the top talent scouts discover them. Via its algorithm that scrapes approximately 150,000 tracks on platforms including Spotify, YouTube, SoundCloud and Tikto, Snafu finds what stands out.

University academics at Stanford and San Francisco are also running inspiring research programs investigating human neural networks and the ‘danceability’ of specific sounds and combinations of notes and beats. Through creating these new data points, the industry is spotting the next opportunity. If you’re surprised by some of the hit singles at the top of the charts, you might find this interesting.

As featured by Complex, record producer Ankit Desai made a game-changing discovery. Desai analyzed Spotify data to spot the song most likely to be Logic’s biggest hitter. Desai identified an usually high percentage of fans listening to Logic’s “1-800-273-8255”  were adding the song to their personal playlists – and playing the song repeatedly. Armed with this data, the label focused on lavishing this specific song with a far bigger marketing budget. So, what difference did this make? The record hit No. 3 on the Billboard Hot 100 and it went quintuple platinum. Enough said.

Playing to the crowd

With data, you don’t even have to listen to the song to know if it’s in synch – just looking at the number of streams, downloads and the level of social media engagement delivers a wealth of data to reveal what’s really top of the pops. Watch the music video with the sound turned down; the tally of views will sing out loud and clear.

Producers are mining social media to measure popularity scores. They now have the ability to delve deeper into consumer behaviour, sentiment and preferences – and the reasons why certain music genres perform better on some social platforms more than others. And this goes way above and beyond the core age and other related demographics already widely used to create content for each platform.

Music is also a master of targeting the tastes to a particular audience segment. Take India for example. After one year of focus on India, Spotify has amassed a new level of detailed understanding into the likes of one country. And just this year, Sony is investing in the market by setting up new AI research labs to study more local behaviors and interests. Forbes recently covered several strong examples where AI has transformed both the developing of music and the marketing.

AI and the future of music

According to Ashley Rose, Grammy nominated songwriter and CEO of The Code, the potential opportunities will only get bigger but producers and artists need to optimize their strategies with AI front of mind in order fully ride AI’s wave of change.

In a report for Entrepreneur, she said: “The introduction of mature AI will ultimately allow creatives and corporations alike to reimagine the creative process, target new fans, and identify the next set of musical stars with greater accuracy and precision than we ever imagined.”

All of this is all the more extraordinary when we remind ourselves that there are only eight notes to play with in music. But through mixing those notes in millions of combinations we create new entertainment day after day for hundreds of years. Similarly, the data points available for gathering insights for business performance can be manipulated in new combinations.

So what can we take away?

  1. Mining the details gets you a better picture to target opportunities, and find the hits
  2. Find the trend by blending historical and real-time data together, and you’ll find where to focus
  3. New metrics can give you an edge, just by linking together seemingly unrelated data points

That same level of granular insights used by the music industry to create gold records can bring aviation similar successes. If artificial intelligence is the key in which we sing, then data is the sheet music guiding us along.

At Cirium, we specialize in fusing together aviation and travel data to help leading travel brands take center stage in their business sectors. We devise and deliver data and analytics products and solutions to elevate your operations – increasing both your profitability and customer satisfaction.



What performance goal do you have in mind? To discover how Cirium solutions can work in harmony with your existing infrastructure and datasets, contact us and one of our specialist advisors will be in touch.

RELX logo