Catching up with our customers always leads to pleasant and insightful conversations. For this new ‘WARM Story’ edition, we got to sit down with Alexandre Perrin, professor in Music business at Berklee College of Music. He shared with us an overview of his journey in the music industry, what his current work entails, how to make the most of Radio airplay data and what to expect in the future.
My name is Alexandre Perrin, I am a full-time professor in Music business at Berklee College of Music. Born and raised in France, I work for the American university in Valencia, Spain. When I graduated from my Master degree, my dream job was to become the head of marketing at Blue Note Records. I have always been fascinated by the graphic design of the album covers and was, of course, a huge music fan since my childhood.
I am also intellectually attracted to technology and innovation. The first company I worked for - twenty years ago - was a SaaS (Software as a Service) specialized in collaborative tools. After working several years as an IT consultant in the middle of the “dotcom bubble”, I became a professor in business schools.
As a teacher, I was able to mix my two main interests: Music and Tech. Since then, I have been researching innovative firms in the field of creative industries such as video games, video-on-demand and music. Unlike the gaming industry, music was not born digital but is more tech-driven than other sectors. It is a fascinating industry!
I wrote my PhD dissertation about the use of organizational knowledge in firms. I discovered that data was very disorganized, in silos. Most of the data was static and useless. I learned that corporate IT systems looked like “mille-feuilles” - a French pastry which has several layers. Every three to five years a new software and a new hardware is installed, employees need to learn new approaches, consultants help them to learn… And so on. When I started my career, people were capturing data in a MS-Dos environment and the most secured database was Lotus Notes. I am not that old! Data has always been hard to organize in a meaningful way.
Now things have changed and the access to data is democratized, accessible to anyone. The music industry used to look at CD sales, now they look at a dashboard of ten different metrics about an artist: audio streams, video streams, non-interactive streams, radio airplay (thanks to WARM!), Facebook and Instagram engagement, TikTok posts, Google searches… What used to be scarce, is now abundant. To make it insightful you need skills in data curation, analysis, and visualization.
Insights can be split into two categories: streams/airplays and social media. The first one tells you where and when an audience has listened to you, in which format, and how this content was pushed (or pulled) to their ears (a playlist or non-interactive radio?). The second one tells you how this audience connects with you as a human being, as an artist. Yet, these two things do not necessarily correlate. On the one hand, you can have thousands of streams and not be able to sell 50 concert tickets, or on the other hand, you can perform extremely well on social media and not be featured in the biggest playlists on streaming platforms. Most musicians have a preferred platform, generally linked to the fact they built their initial fanbase there.
Social media data is crucial to understand an artist's audiences. Streaming data is not that representative of this since its distorting your actual audience. You can have a thousand streams and not be able to sell 50 concert tickets. There’s not a real correlation between the streams and the success of an artist. You need a multicriteria representation to analyze the correlation between radio and streaming.
During my class, we use this data to analyze the life of a song and to connect spikes in radio airplay with events such as Grammy nominations, collaborations, etc. It’s also interesting to analyze the impact and correlation between external factors such as the weather (which makes streaming listeners choose happier/sadder songs), TV Shows (if a song is synchronized on a Netflix show for instance), and a song’s airplay.
Something that we also look into are slowburn hits. How some tracks have a second wave of consumption because of a TikTok video for example. Unfortunately, we are not yet able to say which song will be successful. The industry is so unpredictable. It’s not like the weather. Nevertheless, I do teach my students how to identify hidden talents.
Musicians generate so much data but don’t necessarily take the time to analyze it! I guess it is mostly the job of the manager. He/she could discover some interesting information such as: where would I tour (virtually or physically- hopefully soon)? Which radios or playlist curators should I pitch to? Which artistic collaborations may represent an opportunity for me? Where should I target my next marketing campaign? If I were to give some tips and tricks to new artists to succeed, I would say...
> Take care of your metadata
If you don’t know how to start, I suggest you check-in with your collecting society. You might be missing royalties because of incorrect metadata.
> Always check your analytics
For example, Netflix has become so successful in comparison with the movie industry because they analyze everything that happens on their platform and act upon it. The digital world has enabled people to access all kinds of information! However, the amount of information now available might be a bit overwhelming. That is why it should be the manager’s role to collect and analyze the correct data.
> Train in excel or spreadsheets
I know that, as a creative, this is the last thing you want to hear. It only takes an hour to learn how to create a Pivot Table, set up some easy formulas in Excel, and the end result will make your life so much easier when it comes to analyzing and understanding your data. Think long term!
An additional thing to mention: there’s a problem when it comes to specific countries. It can be difficult to analyze certain countries like Japan, China, or India. The global perspective that WARM provides is useful because it lacks on other platforms, whose data is sometimes fragmented.
I have been following WARM for several years, ever since Startup Sesame (founded by a former lecturer at Berklee Valencia) invested in it. I have been using the datasets for the last two years now. Compared to other companies which offer raw airplay data which is difficult to understand, WARM offers “clean” data. To organize data I recommend users to extract the data from WARM as an Excel file, then try to do a Pivot Table to count the number of streams per city over a specific period of time. They could generate a worldwide map with all the airplays. If they don’t know how to do it, they can (1) check the dashboard on WARM’s website or (2) hire one of my students!
WARM is also very useful because it allows you to access very precise information that you can’t get from Spotify for Artists: the exact number of radio airplays per channel, per volume, per city, per day, and per hour. Streaming platforms do not allow you to have that level of granularity! For instance, you can count airplays and see how long a song has been played on a radio station; you can’t get this from a DSP data retriever such as Chartmetrict.
So to my fellow music industry colleagues I say: use WARM. It’s a great addition to the analytical dashboard of a label, manager, and/or artist. WARM is a pure player in the field focusing only on airplay. Therefore it is wise to add other databases, as airplay may represent a fraction of the activity of an artist. There is no “one-stop-shop” in data analytics. You need to create your patchwork, and WARM is a great piece to add.
Radio consumption is evolving, especially with the rise of podcasts. Nowadays, the public listen to radio through apps and online. When they are commuting, people want to relax and listen to something curated by actual humans. The narrative that the curator gives around the song is something that listeners can’t get from a DSP.
The future of radio may also vary around the world because cultures differ from country to country. In some countries, public radio stations are very important to maintain and increase the diversity of the music that people listen to. They protect things like language (in France, for example, public radio stations are obliged to play a specific percentage of French music) or emerging artists. The diversity radio provides musically, also helps protect a country’s culture - protection which is still nowhere to be seen amongst DSPs.
In short, the audio format will never disappear. It’s way less intrusive than video and allows multitasking, which is key nowadays!
I believe there’s going to be a stabilization of the audience when it comes to the traditional way of listening to the radio. However, new ways of accessing it, like podcasts or apps, are going to keep on growing. Programs are going to be shortened, and radio stations will have to adapt. Those that only do broadcast are going to have a difficult time trying to survive. If radio stations provide listeners with the same as the DSPs provide, they’ll die.
More and more radio stations now are looking to create a different offer, like for example specializing in a specific genre. The audio format will never disappear though. It’s way less intrusive than video format and allows multitasking, which nowadays is key.
"Warm data have been extremely useful to identify the growth of the artist I was working on. It allowed me to build a worldwide airplay map to showcase how my artist's influence spread globally over time. Without this data my analysis would have been less accurate, and my story telling incomplete."
Student of Alexandre Perrin at Berklee College of Music