Should I Build It Should I Build It
11 May 2025
Artificial Intelligence Music

AI wrapper that curates new music based on a Gen Xer’s peak-era tastes ...

... We would provide curated playlists that are better than spotify

Confidence
Engagement
Net use signal
Net buy signal

Idea type: Freemium

People love using similar products but resist paying. You’ll need to either find who will pay or create additional value that’s worth paying for.

Should You Build It?

Build but think about differentiation and monetization.

Your are here

You're entering a crowded space with your AI-powered music curation for Gen Xers, as evidenced by the 14 similar products we found. This puts you in the 'Freemium' category, meaning many alternatives exist, and people generally resist paying for these services, yet show high interest. The good news is that this means that the market is ready, people are familiar with the product category. To succeed, you'll need to figure out what makes your curated playlists significantly better than existing free options like Spotify or Amazon Music, and identify your ideal user. Several similar products received good engagement (avg 7 comments), suggesting people are interested in personalized playlists. Given the competition, differentiation is key. You'll have to figure out how to get users to pay for something that is often given away for free, such as premium playlists or some other premium feature.

Recommendations

  1. Given that you are going after GenX, consider what makes this demographic unique. GenXers have nostalgia for specific eras and genres. Focus on curating extremely accurate playlists that tap into those nostalgic preferences. Your AI needs to understand the nuances of 80s alternative, 90s grunge, or early 2000s indie rock to really stand out.
  2. Spotify's AI Playlist has received positive feedback for personalized music discovery. However, users have reported slow loading times during playlist refinement. Focus on optimizing your AI for speed and efficiency. A seamless user experience is crucial for retaining users in a crowded market.
  3. Several similar products were criticized for lacking genre indicators or struggling with niche themes. Make sure your AI provides clear genre classifications and handles niche music categories effectively. Transparency in your AI's criteria will build trust with users.
  4. Since you're in the 'Freemium' category, identify the users who get the most value from free versions. Understand their needs and pain points. What are they not getting from free services like Spotify? Are they frustrated with the algorithm? Do they feel misunderstood by current AI music curators? Knowing this will help you build your premium features.
  5. Based on your ideal customer segment, create premium features that solve specific problems. Perhaps GenXers want ad-free listening, higher audio quality, or exclusive access to rare tracks. Maybe they want deeper customization options, like the ability to influence the AI's recommendations with their own musical knowledge. Focus on premium features that go beyond basic functionality and add real value.
  6. Explore alternative monetization strategies beyond individual subscriptions. Consider charging teams or groups, such as for workplace music curation or shared playlists among friends. Are there small businesses who might want your playlists to curate a specific mood and vibe? Tailor your monetization strategy to your target audience.
  7. Offer personalized help or consulting to users who want even more customized playlists. This could involve one-on-one consultations with music experts or access to a community of like-minded listeners. Personalization and community can be powerful drivers of loyalty.
  8. Before committing to a specific pricing model, test different approaches with small groups of users. Offer different tiers of service with varying features and price points. Get feedback on what users value most and adjust your pricing accordingly.

Questions

  1. Given that multiple competing AI playlist generators have launched recently (Spotify, Amazon Maestro, PlaylistAI) what unique angle will you offer to Gen Xers that those don't? How will you avoid becoming just another 'me too' product?
  2. How granular can your AI get in terms of identifying and catering to specific subgenres or niche musical tastes within the Gen X demographic? Can it differentiate between early grunge vs. post-grunge, or British alternative vs. American alternative?
  3. What specific data points will your AI use to determine a Gen Xer's 'peak-era' tastes, and how will you ensure that the recommendations are both nostalgic and relevant to their current preferences?

Your are here

You're entering a crowded space with your AI-powered music curation for Gen Xers, as evidenced by the 14 similar products we found. This puts you in the 'Freemium' category, meaning many alternatives exist, and people generally resist paying for these services, yet show high interest. The good news is that this means that the market is ready, people are familiar with the product category. To succeed, you'll need to figure out what makes your curated playlists significantly better than existing free options like Spotify or Amazon Music, and identify your ideal user. Several similar products received good engagement (avg 7 comments), suggesting people are interested in personalized playlists. Given the competition, differentiation is key. You'll have to figure out how to get users to pay for something that is often given away for free, such as premium playlists or some other premium feature.

Recommendations

  1. Given that you are going after GenX, consider what makes this demographic unique. GenXers have nostalgia for specific eras and genres. Focus on curating extremely accurate playlists that tap into those nostalgic preferences. Your AI needs to understand the nuances of 80s alternative, 90s grunge, or early 2000s indie rock to really stand out.
  2. Spotify's AI Playlist has received positive feedback for personalized music discovery. However, users have reported slow loading times during playlist refinement. Focus on optimizing your AI for speed and efficiency. A seamless user experience is crucial for retaining users in a crowded market.
  3. Several similar products were criticized for lacking genre indicators or struggling with niche themes. Make sure your AI provides clear genre classifications and handles niche music categories effectively. Transparency in your AI's criteria will build trust with users.
  4. Since you're in the 'Freemium' category, identify the users who get the most value from free versions. Understand their needs and pain points. What are they not getting from free services like Spotify? Are they frustrated with the algorithm? Do they feel misunderstood by current AI music curators? Knowing this will help you build your premium features.
  5. Based on your ideal customer segment, create premium features that solve specific problems. Perhaps GenXers want ad-free listening, higher audio quality, or exclusive access to rare tracks. Maybe they want deeper customization options, like the ability to influence the AI's recommendations with their own musical knowledge. Focus on premium features that go beyond basic functionality and add real value.
  6. Explore alternative monetization strategies beyond individual subscriptions. Consider charging teams or groups, such as for workplace music curation or shared playlists among friends. Are there small businesses who might want your playlists to curate a specific mood and vibe? Tailor your monetization strategy to your target audience.
  7. Offer personalized help or consulting to users who want even more customized playlists. This could involve one-on-one consultations with music experts or access to a community of like-minded listeners. Personalization and community can be powerful drivers of loyalty.
  8. Before committing to a specific pricing model, test different approaches with small groups of users. Offer different tiers of service with varying features and price points. Get feedback on what users value most and adjust your pricing accordingly.

Questions

  1. Given that multiple competing AI playlist generators have launched recently (Spotify, Amazon Maestro, PlaylistAI) what unique angle will you offer to Gen Xers that those don't? How will you avoid becoming just another 'me too' product?
  2. How granular can your AI get in terms of identifying and catering to specific subgenres or niche musical tastes within the Gen X demographic? Can it differentiate between early grunge vs. post-grunge, or British alternative vs. American alternative?
  3. What specific data points will your AI use to determine a Gen Xer's 'peak-era' tastes, and how will you ensure that the recommendations are both nostalgic and relevant to their current preferences?

  • Confidence: High
    • Number of similar products: 14
  • Engagement: Medium
    • Average number of comments: 7
  • Net use signal: 22.8%
    • Positive use signal: 22.8%
    • Negative use signal: 0.0%
  • Net buy signal: 0.0%
    • Positive buy signal: 0.0%
    • Negative buy signal: 0.0%

This chart summarizes all the similar products we found for your idea in a single plot.

The x-axis represents the overall feedback each product received. This is calculated from the net use and buy signals that were expressed in the comments. The maximum is +1, which means all comments (across all similar products) were positive, expressed a willingness to use & buy said product. The minimum is -1 and it means the exact opposite.

The y-axis captures the strength of the signal, i.e. how many people commented and how does this rank against other products in this category. The maximum is +1, which means these products were the most liked, upvoted and talked about launches recently. The minimum is 0, meaning zero engagement or feedback was received.

The sizes of the product dots are determined by the relevance to your idea, where 10 is the maximum.

Your idea is the big blueish dot, which should lie somewhere in the polygon defined by these products. It can be off-center because we use custom weighting to summarize these metrics.

Similar products

Relevance

Spotify AI Playlist - Turn your most creative ideas into playlists

25 Sep 2024 Artificial Intelligence Music Spotify

AI Playlist combines Spotify’s powerful personalization technology with generative AI so users can turn their most creative ideas into playlists. Create and curate that perfect musical mix, just for you.

Spotify's AI Playlist launch is receiving positive feedback, with users excited about personalized music discovery and the ability to create customized playlists using prompts. The combination of personalization and creativity is well-received, and many congratulate the team. Users are eager to explore the AI integration and create unique mixes. Some users have reported slow loading times during playlist refinement. There is a desire for more information and Spotify integration details, particularly regarding niche themes. While mostly positive, one user pointed out Moodplaylist.com did this years before.

Users criticized the slow loading time for playlist refinement. This was the only criticism provided.

Avatar
318
27
40.7%
27
318
40.7%
Relevance

findmusic.ai - Predictive Playlists, Made for You

25 Oct 2024 Artificial Intelligence Music Spotify

findmusic.ai is an AI-powered web app that creates personalized, predictive playlists just for you based on your unique music preferences.

Users are requesting clearer genre indicators for playlists and inquiring about the algorithm's differences from Spotify. They also expressed curiosity about the free offering's limitations. Overall the users are congratulating the team for Findmusic.ai. Praising the music selection is also a key aspect, along with inquiries about the playlist refresh rate.

Users criticized the product for lacking visible genre indicators on playlists. Also, the Spotify authorization request was deemed intimidating, potentially deterring users from connecting their accounts.

Avatar
114
4
25.0%
4
114
25.0%
Relevance

PlaylistAI - Create Spotify and Apple Music playlists with AI

11 Jan 2023 Artificial Intelligence Music Spotify

Make a playlist for any thought, image, or video. Enter a prompt like "Pop music from the early 2000's" or provide an image, like a Coachella music festival poster, and PlaylistAI will create a playlist for you.

The product launch on Product Hunt has received overwhelmingly positive feedback. Users appreciate the music festival scanner and GPT-aided playlist generator. The app is described as fun, well-executed, and smooth to set up. Many congratulate the team on the launch and express excitement to try the product. A frequently mentioned feature is the music poster scanner. Some users have requested additional support for YouTube and podcast apps, as well as an Android version. Overall, the product is well-received and generates enthusiasm.

Avatar
246
17
41.2%
17
246
41.2%
Relevance

PlaylistAI – Create Spotify and Apple Music Playlists with AI

11 Jan 2023 Music Spotify

Hey HN, I'm Brett and I'm an iOS developer.I made an app that makes you music playlists using AI in a few different ways. The main being AI prompts - you can enter something like "chill coding music, electronic" or "Music similar to the artist Bob Dylan" and it will generate a playlist for you.There are other ways to make playlists as well - using computer vision on images, sound recognition in videos, etc.Give it a try and share some playlists that you make. There's a demo video in my launch tweet here -https://twitter.com/brettunhandled/status/161317951121827840...

The comments have been flagged for review and are not visible for analysis.

Avatar
1
2
2
1
Relevance

Amazon Maestro - A new AI playlist generator

24 Apr 2024 Artificial Intelligence Music

An AI playlist generator that helps you create any playlist you can think of—plus all the ones you can’t. This feature is rolling out in beta to a small number of U.S. customers on all tiers of Amazon Music.

Amazon Music's Maestro launch is being seen as an attempt to rival Spotify's AI playlists, with users generally reacting positively. Users praise the tool's potential for music consumers and its user-centric design. Some users inquired about the AI's criteria, especially diversity in playlist creation. One user stated the tool was needed. The overall sentiment is enthusiastic with users congratulating the launch and wishing good luck.

Users questioned the AI's ability to accurately interpret nuanced musical moods and requested more transparency regarding the specific criteria used for music selection. The feedback emphasizes the need for clarification on the AI's understanding of musical mood swings and the selection process.

Avatar
125
10
10.0%
10
125
10.0%
Relevance

AI-Powered Music Recommendation Based on Your Mood and Genre

13 Nov 2024 Artificial Intelligence Music

Users appreciate the idea and find the website appealing. There are multiple requests for additional language options, suggesting a demand for broader accessibility. An audio feature addition is also suggested. One user inquired about the integration with the YouTube API, indicating interest in expanded functionality.

Users have criticized the product for having limited language options and suggested improvements such as increasing rendering speed and adding an audio feature.

Avatar
12
7
7
12
Relevance

AI + Apple Music, search 100M+ tracks with natural language prompts

28 Jun 2023 Artificial Intelligence Music

Hi HN!We’re a group of electronic music artists and PhD researchers working in AI music.We've been working on a project to help us discover new music in a more musically objective way, called Speak Music:https://speakmusic.sonophase.com/We recently presented at Sonar+D in Barcelona.We’ve trained an AI model to understand the correspondence between music and language, combining a machine listening system for audio signal processing with transformers for text embeddings. Once trained, we index a huge catalogue of unseen audio, so that the search system can efficiently scale to millions of tracks.At the moment, our model is optimised for our preferred music; electronic, techno, ambient and relaxing music. We’re currently fine-tuning to handle all kinds of genres and moods.Our model handles two types of discovery: (a) natural language search and (b) similarity search.(a) Speak: search for music using freeform natural language prompts, describing the mood, aesthetic, texture, setting and context of a track.(b) Music: discover tracks that are acoustically similar to ANY reference track from Apple Music.We hope you like it. Let us know what you think!

Avatar
3
3
Relevance

Hey, it's jams. ask me to make a Spotify playlist just for you. (AI)

24 Apr 2023 Music Spotify

Users are intrigued by the playlist generation, particularly its personalization features. There are mentions of inaccuracies when selecting artists by prompt and mixed results in song suggestions. However, users have generally enjoyed using the service, with one user having a positive week-long experience and another praising its performance with odd combinations. The chat feature and design have received compliments. There is also curiosity about the service's applicability to podcasts.

Users criticized the product for not providing personalized outputs based on liked songs, inaccurately categorizing a Louis Armstrong song as 1950s jazz, and failing to deliver songs that truly match the requested themes.

Avatar
14
8
12.5%
8
14
12.5%
Relevance

Otto AI - Build unique playlists through AI

15 Nov 2023 Artificial Intelligence Music Spotify

Never worry about what to play. Just describe your activity or mood, and leave it to AI. Otto combs through the music of 100M songs to craft the right mix in seconds. Listen through Spotify and share your mixes with friends!

Otto AI's Product Hunt launch received positive feedback, with users praising its AI-powered personalized music playlists and ability to adapt to user preferences. Some users expressed interest in using it for mood-based music, with one user describing the experience like a song that always hits right. A user also noted the likelihood of finding Journey songs within the generated playlists. The launch was congratulated with enthusiasm.

Avatar
89
8
12.5%
8
89
12.5%
Relevance

AI audio embeddings - Discover 100M+ iTunes songs with language models

27 Jun 2023 Artificial Intelligence Music

We’re a group of electronic music artists and PhD researchers working in AI music.We've been working on a project to help us discover new music in a more objective way. It's called Speak Music:https://speakmusic.sonophase.com/We’ve trained an AI model to understand the correspondence between music and language. The model combines a machine listening and audio signal processing with transformers for text embeddings. Once trained, we index a huge catalogue of unseen audio, ensuring that the search system can efficiently scale to millions of tracks.At the moment, our model is optimised for our preferred music; electronic, techno, ambient, dub and relaxing etc. We’re currently fine-tuning to handle all kinds of genres and moods.Our model enables two types of discovery: (a) natural language search and (b) similarity search.(a) Speak: search for music using freeform natural language prompts. Describe the mood, aesthetic, texture, setting and context of a track.(b) Music: discover tracks that are acoustically similar to ANY reference track from Apple Music.We recently presented at Sonar+D in Barcelona.We hope you like it. Let us know what you think!

Users appreciate the product for its suitability for ambient and electronic music, and find the similarity feature cool. The visual design is praised, and there is curiosity about the tech stack. The timbre search feature yields interesting and unique results, such as 'racecar.'

The system struggles to accurately interpret and respond to certain terms, such as 'Erhu', indicating potential limitations in its language processing capabilities.

Avatar
7
3
3
7
Top