Should I Build It Should I Build It
22 Apr 2025
Artificial Intelligence

AI colour analysis app for iOS and Android that analyses a user's ...

...colour palette from a photo / video for clothes, jewelry etc

Confidence
Engagement
Net use signal
Net buy signal

Idea type: Swamp

The market has seen several mediocre solutions that nobody loves. Unless you can offer something fundamentally different, you’ll likely struggle to stand out or make money.

Should You Build It?

Don't build it.

Your are here

You're venturing into the AI color analysis app market, which our analysis indicates is a 'Swamp' category. This means several similar solutions already exist, but haven't quite captured the market's heart. With 14 similar products already out there, competition is significant. The engagement with these products is low, averaging only 2 comments per product, suggesting it's difficult to create excitement in this area. The lack of positive 'use' or 'buy' signals indicates that people aren't explicitly clamoring for these tools, which aligns with the 'Swamp' category assessment. The good news is that the existing solutions have not successfully served the existing userbase.

Recommendations

  1. Given the 'Swamp' category designation, thoroughly investigate why existing color analysis apps haven't achieved widespread adoption. Analyze user reviews, identify pain points, and pinpoint unmet needs. The similar product discussions highlight features like AI-powered palette generation, but also issues like non-functional buttons. Understanding these shortcomings is crucial.
  2. If you're set on proceeding, narrow your focus to a specific, underserved user group. Instead of targeting everyone, identify a niche where your app can provide unique value. For example, could you focus on creating palettes for specific skin tones or ethnicities? This targeted approach could help you stand out in a crowded market.
  3. Explore the possibility of creating tools for existing providers rather than building a direct competitor. Could you develop an API or plugin that enhances the functionality of popular design platforms or e-commerce sites? This collaborative approach might be a more viable path to success.
  4. Consider adjacent problems that might be more promising. Instead of focusing solely on color analysis, could you expand your app to offer personalized style recommendations based on body type, lifestyle, or budget? Thinking beyond the core functionality could reveal untapped opportunities.
  5. Given the low engagement and existing competition, it might be wise to conserve your resources and explore alternative startup ideas. The 'Swamp' designation suggests that success in this market will be challenging, so consider channeling your energy into a more promising venture. Use the feedback you collected from your research for the next idea.
  6. Given the generally positive reaction to AI integration for color palette generation (as seen in similar product feedback), consider focusing on the AI aspects in your marketing to try and differentiate your product from existing competitors.

Questions

  1. What is a concrete plan to generate interest, given existing apps struggle to engage users?
  2. How can the application stand out among competitors, given that the number of similar products are relatively high?
  3. Have you considered how the AI will be trained and updated, especially to adapt to different lighting conditions and camera qualities across various devices?

Your are here

You're venturing into the AI color analysis app market, which our analysis indicates is a 'Swamp' category. This means several similar solutions already exist, but haven't quite captured the market's heart. With 14 similar products already out there, competition is significant. The engagement with these products is low, averaging only 2 comments per product, suggesting it's difficult to create excitement in this area. The lack of positive 'use' or 'buy' signals indicates that people aren't explicitly clamoring for these tools, which aligns with the 'Swamp' category assessment. The good news is that the existing solutions have not successfully served the existing userbase.

Recommendations

  1. Given the 'Swamp' category designation, thoroughly investigate why existing color analysis apps haven't achieved widespread adoption. Analyze user reviews, identify pain points, and pinpoint unmet needs. The similar product discussions highlight features like AI-powered palette generation, but also issues like non-functional buttons. Understanding these shortcomings is crucial.
  2. If you're set on proceeding, narrow your focus to a specific, underserved user group. Instead of targeting everyone, identify a niche where your app can provide unique value. For example, could you focus on creating palettes for specific skin tones or ethnicities? This targeted approach could help you stand out in a crowded market.
  3. Explore the possibility of creating tools for existing providers rather than building a direct competitor. Could you develop an API or plugin that enhances the functionality of popular design platforms or e-commerce sites? This collaborative approach might be a more viable path to success.
  4. Consider adjacent problems that might be more promising. Instead of focusing solely on color analysis, could you expand your app to offer personalized style recommendations based on body type, lifestyle, or budget? Thinking beyond the core functionality could reveal untapped opportunities.
  5. Given the low engagement and existing competition, it might be wise to conserve your resources and explore alternative startup ideas. The 'Swamp' designation suggests that success in this market will be challenging, so consider channeling your energy into a more promising venture. Use the feedback you collected from your research for the next idea.
  6. Given the generally positive reaction to AI integration for color palette generation (as seen in similar product feedback), consider focusing on the AI aspects in your marketing to try and differentiate your product from existing competitors.

Questions

  1. What is a concrete plan to generate interest, given existing apps struggle to engage users?
  2. How can the application stand out among competitors, given that the number of similar products are relatively high?
  3. Have you considered how the AI will be trained and updated, especially to adapt to different lighting conditions and camera qualities across various devices?

  • Confidence: High
    • Number of similar products: 14
  • Engagement: Low
    • Average number of comments: 2
  • Net use signal: 21.3%
    • Positive use signal: 21.3%
    • 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.

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I made a web color palette generator/editor to simplify color harmony

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Hi everyone,I have just finished my free color palette generator that uses your brand colors and creates unlimited palettes based on various color harmonies, that you can then edit and export for use in your projects.I have built it because whenever I would need to select all the shades of different colors for my designs, they never looked quite right. The app is based on the Oklch color space, which means that all different colors will match their lightness.It also groups colors into Accents, neutrals and grays, and comes with features like color contrast checker and colorblindness preview, so you could easily make sure your color palettes are accessible to everyoneCheck it out here! : https://www.palettemaker.io/createAlso, I would appreciate your feedback on what I could improve in my appThanks, Justas

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