The fastest way to stall a music career is to build a following you can’t reach. I sit down with Jack McCarthy from IndieX to get practical about artist ownership: how attention becomes data, how data becomes relationships, and how relationships become reliable income that does not vanish between releases and tours.

We talk through a simple framework that turns the fuzzy idea of a “fan base” into something you can measure and improve: audiences on social platforms, contacts on your email list or text list, customers who buy directly, and repeat customers who come back. From there, we get into real-world music marketing moves that pull people closer, from live show list-building to online offers like early access, tour location prompts, and creative drops that feel aligned with your art.

Jack also explains the “revenue roller coaster” and why so many artists ride painful spikes around albums and touring. The alternative is always-on e-commerce marketing: lightweight campaigns throughout the year, smart calendars, and a clear customer journey that builds cash flow over time. We also get honest about streaming revenue, how to use streaming data as leverage, and why direct-to-fan should mean fewer middlemen, not new ones hiding behind shiny platforms.

If you want a more sustainable music business built on fan data, e-commerce, and direct-to-consumer strategy, hit play, then subscribe, share this with one artist friend, and leave us a review.

https://indepreneur.io/services/

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You can feel the right track in your bones, but finding it inside a giant catalogue can still be painfully slow. That gap between what we mean and what search engines can understand is where sync licensing briefs stall, temp tracks take over, and great back catalogue gets left behind. I'm joined by Tiangu Zhu, founder of Songpot, to unpack a simple but ambitious goal: building AI that truly understands music as a language, not just as metadata.

We talk through the real-world problems music supervisors and media teams face when words fail. Genre, mood and “danceability” are subjective, tagging is inconsistent, and a song rarely fits neatly into a few labels. Tiangu explains how AI music discovery can analyse audio itself to reveal “unspoken similarities”, helping libraries and rights holders improve music search, speed up clearance workflows, and deliver better matches for sync licensing. We also get into how Songpot can sit in the stack as a platform or an API for more tech-native companies.

Then we flip to the creator side. Tiangu makes a clear case for human-centred generative AI: not replacing artists, but acting like a new instrument for producers and musicians. From prototyping ideas faster to turning a hummed melody plus a style into an instant draft, the focus stays on helping creators translate what’s in their head into something they can actually hear, share, and refine.

If you care about music supervision, music libraries, catalogue value, music information retrieval, or practical AI tools for music production, this conversation will stretch your thinking. Subscribe for more, share this with a friend in sync or production, and leave a review if you want us to keep bringing you guests building the future of the music industry.

https://songpot.art

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The leap from making songs to building a career isn’t magic — it’s momentum you can engineer. I pull back the curtain on how to launch a brand-new artist from zero data to investable, using a practical framework that blends creative clarity with disciplined execution. No hype, no guesswork, just a repeatable path that lowers risk and raises opportunity.

I start by nailing the lane: genre, subculture, and the core emotional promise that tells fans who you are at a glance. From there, we move into building in public, where behaviour beats vanity metrics. Watch time, comments, shares, and saves reveal what resonates before a single hits DSPs. Then we lay out a 36-week release plan: six singles, one every six weeks, supported by identity-led short-form content and optimised distribution on Spotify and Apple Music. You’ll learn why user-curated playlists are the first real lever, how a 10%+ save rate and listener-to-follower conversion flag a true lead single, and which analytics tools give you clean, comparable data.

Press matters too — not for bragging rights, but for web presence that algorithms can read. We explain how consistent blog features and reviews feed natural language processing, helping platforms map your music to the right listeners. With one full cycle complete, we repeat with informed variables, compounding what works and dropping what doesn’t. That foundation leads to proof: one hundred local tickets, organic merch sales, early subscriptions, and the moment you “catch” algorithmic support on Discover Weekly and Release Radar. Finally, we show how to package the narrative for partners — growth curves, peer benchmarks, release discipline, revenue per fan, and a clear plan for deploying capital across touring, content, and marketing. You stop pitching potential and start pitching acceleration.

If you’re serious about turning art into a sustainable business, this roadmap gives you the steps, signals, and language partners trust. Subscribe, share with a fellow creator, and leave a review with the one metric you plan to track next — what will you measure first?

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Websites
www.jonnyamos.com
https://themusicbusinessbuddy.buzzsprout.com

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https://www.instagram.com/jonny_amos/

Email
jonnyamos@me.com