auto matching image color profile like fuji color matching or

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

Your idea of automatically matching image color profiles, similar to Fuji color matching, falls into a crowded space. Our analysis shows several existing solutions, suggesting it's a 'Swamp' category where many mediocre options already exist. With 9 similar products already out there, competition is high, and the average engagement (number of comments) on these similar products is low. Because of this high competition and low engagement, unless your solution offers a fundamentally different approach, standing out and achieving profitability will be challenging. The market has already seen a lot of mediocre solutions, so to succeed, you'll need a truly innovative and unique offering.

Recommendations

  1. Thoroughly research existing color matching solutions to understand their shortcomings and why they haven't achieved widespread adoption. Look for common pain points and areas where users are consistently dissatisfied. Understanding these failures is crucial before investing further in your idea.
  2. If you decide to proceed, identify a specific niche or group of users that are currently underserved by existing solutions. Instead of trying to compete with established general-purpose tools, focus on catering to the unique needs of a particular segment of photographers or designers. Specialization could give you a competitive edge.
  3. Consider if building tools that enhance existing photography workflows are a better fit than competing with the established photo editing software. Examine the possibility of developing plugins or add-ons for popular applications like Adobe Photoshop or Capture One. In this case, you will be supporting established workflows instead of asking users to learn an entirely new software.
  4. Explore adjacent problems in the image processing or color management space that may present more promising opportunities. Could your expertise be applied to areas like color accessibility, automated image enhancement for e-commerce, or creating custom color palettes for branding? Diversifying your focus might reveal a more viable path.
  5. Given the crowded market and low engagement, carefully evaluate whether this is the best use of your time and resources. It may be wise to save your energy and capital for a different opportunity with greater potential for success. There are many other sectors that need more attention and creativity.
  6. Since similar products receive very little engagement, focus on building your product in public by releasing features every week and posting about them on X and Reddit. If you get any meaningful engagement (2-3 comments), keep building. If not, it's a signal to move on.

Questions

  1. What fundamental problem with existing color matching solutions will your product solve, and how will you objectively measure its superiority?
  2. How will you acquire your first 100 paying customers given the low engagement and high competition in the existing market? What is your customer acquisition strategy?
  3. Given the 'Swamp' category classification, what are the key assumptions about user needs and market demand that, if proven false, would cause you to abandon this project?

Your are here

Your idea of automatically matching image color profiles, similar to Fuji color matching, falls into a crowded space. Our analysis shows several existing solutions, suggesting it's a 'Swamp' category where many mediocre options already exist. With 9 similar products already out there, competition is high, and the average engagement (number of comments) on these similar products is low. Because of this high competition and low engagement, unless your solution offers a fundamentally different approach, standing out and achieving profitability will be challenging. The market has already seen a lot of mediocre solutions, so to succeed, you'll need a truly innovative and unique offering.

Recommendations

  1. Thoroughly research existing color matching solutions to understand their shortcomings and why they haven't achieved widespread adoption. Look for common pain points and areas where users are consistently dissatisfied. Understanding these failures is crucial before investing further in your idea.
  2. If you decide to proceed, identify a specific niche or group of users that are currently underserved by existing solutions. Instead of trying to compete with established general-purpose tools, focus on catering to the unique needs of a particular segment of photographers or designers. Specialization could give you a competitive edge.
  3. Consider if building tools that enhance existing photography workflows are a better fit than competing with the established photo editing software. Examine the possibility of developing plugins or add-ons for popular applications like Adobe Photoshop or Capture One. In this case, you will be supporting established workflows instead of asking users to learn an entirely new software.
  4. Explore adjacent problems in the image processing or color management space that may present more promising opportunities. Could your expertise be applied to areas like color accessibility, automated image enhancement for e-commerce, or creating custom color palettes for branding? Diversifying your focus might reveal a more viable path.
  5. Given the crowded market and low engagement, carefully evaluate whether this is the best use of your time and resources. It may be wise to save your energy and capital for a different opportunity with greater potential for success. There are many other sectors that need more attention and creativity.
  6. Since similar products receive very little engagement, focus on building your product in public by releasing features every week and posting about them on X and Reddit. If you get any meaningful engagement (2-3 comments), keep building. If not, it's a signal to move on.

Questions

  1. What fundamental problem with existing color matching solutions will your product solve, and how will you objectively measure its superiority?
  2. How will you acquire your first 100 paying customers given the low engagement and high competition in the existing market? What is your customer acquisition strategy?
  3. Given the 'Swamp' category classification, what are the key assumptions about user needs and market demand that, if proven false, would cause you to abandon this project?

  • Confidence: High
    • Number of similar products: 9
  • Engagement: Low
    • Average number of comments: 1
  • Net use signal: 15.0%
    • Positive use signal: 25.0%
    • Negative use signal: 10.0%
  • 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

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I made a web app for color grading and film emulation

10 Jun 2023 Design Tools

TLDR: I’m a solo dev with backgrounds in art/photography and made a web app (PWA) for film emulation and color grading.Hey everyone! I'm excited to introduce you to a passion project that's been keeping me busy for nearly a year - a color grading and film emulation web app called Color.io (https://app.color.io). It's desktop-only for the moment but merging the new engine with my other, mobile first app (match.color.io), is in the pipeline.Color.io is the result of my long standing frustration with how color tools behave in most editing and color grading software, especially on the photographic end. It’s much easier to create completely unnatural looking colors than it is to truly enhance an image in a subtle and film-like way. Most apps work around their engines’ color transform shortcomings by exposing some kind of profile or 3D LUT interface that allows for arbitrary 3D color mappings to be applied to images. The problem with profiles and LUTs however is that they’re a black box and offer limited creative control.My app is meant to act as a middle man in this color process. I wrote a custom color engine on top of ACES (hand ported to WebGL) that uses custom color models and transform operations that are much more suitable for creative color manipulation than cone models like HSL. The engine is controlled by my library of interface tools like custom spline interpolators, color wheels, 2D draggables and more. I also ported a custom libRAW build to web assembly for a logarithmic raw development workflow.The project is still very much in its early stages, and the response since the soft launch has been overwhelmingly positive. I'm keen on using this momentum to make the app better. So, your feedback would be hugely appreciated! Tell me about the features you'd like to see, the ones you're loving, and anything you think needs improvement (all code, design, marketing is a solo gig so I'm sure there's lots to do!)Find me on Twitter (@MON0KEE, https://twitter.com/MON0KEE) or more frequently on Instagram (@monokee, https://instagram.com/monokee). I'd love to hear from you!

Impressive tool, novel UI for color interaction.

Explain how it solves usual tool frustrations.


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Relevance

Extract Colors from Images

Color Picker allows you to effortlessly extract colors from images in RGB, HEX, and HSL formats. Save, share, and export your favorite colors seamlessly. Automatic color naming adds convenience. Explore the world of color with this user-friendly web app.

Users appreciate the solid color picker, considering it better than other web apps. They inquire about the strategy for deciding main colors. The page design is praised, the API is found useful, and the manual upload feature is deemed unnecessary.

The manual upload process is seen as unnecessary by users.


Avatar
4
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33.3%
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