Should I Build It Should I Build It
30 May 2025
Fintech Investing

stock technical analysis tool to search for moving averages, patterns ...

...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

The idea of a stock technical analysis tool falls into a crowded market, as indicated by the 'Swamp' category and the high number of similar products (n_matches = 13). This suggests significant competition and a history of potentially mediocre solutions. The average engagement (n_comments = 1) is low, indicating that existing solutions haven't captured significant user interest or generated substantial discussion. With so many existing solutions, it will be difficult to stand out unless your tool offers something drastically different and more compelling. Given the competitive landscape and low engagement, it's crucial to carefully evaluate whether pursuing this idea is the best use of your resources. Many have tried and seemingly failed to build something truly novel in this crowded space.

Recommendations

  1. Begin by thoroughly researching why existing stock technical analysis tools haven't achieved widespread success. Analyze their features, pricing, user reviews, and marketing strategies to identify gaps and pain points that you can address. For example, users of similar products often complain about not having access to all the symbols they want.
  2. If you decide to proceed, focus on identifying a specific niche or underserved group within the stock trading community. This could be beginner investors, traders focused on specific sectors (e.g., renewable energy), or users who prefer a particular analysis style (e.g., algorithmic trading). Find a narrow slice of the market you can dominate. Instead of trying to appeal to everyone, start with a focused group.
  3. Consider building tools or providing data feeds that integrate with existing stock trading platforms rather than creating a standalone application. Partnering with established providers can give you access to a larger user base and reduce the challenges of customer acquisition. Or build an API, not a product.
  4. Explore adjacent problems in the financial technology space that may offer more promising opportunities. For example, you could focus on developing risk management tools, educational resources, or portfolio optimization algorithms. These areas may have less competition and greater potential for innovation.
  5. Before investing significant time and resources, validate your idea by creating a minimum viable product (MVP) and testing it with your target audience. Gather feedback on the tool's usability, features, and value proposition. Pivot or iterate based on real-world usage and insights. Remember, users also value open-source tools and don't like to sign up to test a basic version of the tool.
  6. Carefully consider your business model and pricing strategy. Determine how you will generate revenue and whether your target audience is willing to pay for your solution. Explore options such as subscription fees, transaction fees, or premium features. The fact that we have zero positive 'buy' signals from similar products means you have to be extra careful about monetization.

Questions

  1. What unique features or capabilities will your stock technical analysis tool offer that are not already available in existing solutions? How will you differentiate your product from the competition and attract users?
  2. Given the low average engagement observed in similar products, how will you ensure that your tool resonates with users and generates meaningful discussion or interaction? What strategies will you use to foster a vibrant community around your product?
  3. Considering that there are no explicit positive 'buy' signals observed in similar products, how will you convince users to pay for your tool? What value proposition will you offer that justifies the cost, and how will you communicate this value effectively?

Your are here

The idea of a stock technical analysis tool falls into a crowded market, as indicated by the 'Swamp' category and the high number of similar products (n_matches = 13). This suggests significant competition and a history of potentially mediocre solutions. The average engagement (n_comments = 1) is low, indicating that existing solutions haven't captured significant user interest or generated substantial discussion. With so many existing solutions, it will be difficult to stand out unless your tool offers something drastically different and more compelling. Given the competitive landscape and low engagement, it's crucial to carefully evaluate whether pursuing this idea is the best use of your resources. Many have tried and seemingly failed to build something truly novel in this crowded space.

Recommendations

  1. Begin by thoroughly researching why existing stock technical analysis tools haven't achieved widespread success. Analyze their features, pricing, user reviews, and marketing strategies to identify gaps and pain points that you can address. For example, users of similar products often complain about not having access to all the symbols they want.
  2. If you decide to proceed, focus on identifying a specific niche or underserved group within the stock trading community. This could be beginner investors, traders focused on specific sectors (e.g., renewable energy), or users who prefer a particular analysis style (e.g., algorithmic trading). Find a narrow slice of the market you can dominate. Instead of trying to appeal to everyone, start with a focused group.
  3. Consider building tools or providing data feeds that integrate with existing stock trading platforms rather than creating a standalone application. Partnering with established providers can give you access to a larger user base and reduce the challenges of customer acquisition. Or build an API, not a product.
  4. Explore adjacent problems in the financial technology space that may offer more promising opportunities. For example, you could focus on developing risk management tools, educational resources, or portfolio optimization algorithms. These areas may have less competition and greater potential for innovation.
  5. Before investing significant time and resources, validate your idea by creating a minimum viable product (MVP) and testing it with your target audience. Gather feedback on the tool's usability, features, and value proposition. Pivot or iterate based on real-world usage and insights. Remember, users also value open-source tools and don't like to sign up to test a basic version of the tool.
  6. Carefully consider your business model and pricing strategy. Determine how you will generate revenue and whether your target audience is willing to pay for your solution. Explore options such as subscription fees, transaction fees, or premium features. The fact that we have zero positive 'buy' signals from similar products means you have to be extra careful about monetization.

Questions

  1. What unique features or capabilities will your stock technical analysis tool offer that are not already available in existing solutions? How will you differentiate your product from the competition and attract users?
  2. Given the low average engagement observed in similar products, how will you ensure that your tool resonates with users and generates meaningful discussion or interaction? What strategies will you use to foster a vibrant community around your product?
  3. Considering that there are no explicit positive 'buy' signals observed in similar products, how will you convince users to pay for your tool? What value proposition will you offer that justifies the cost, and how will you communicate this value effectively?

  • Confidence: High
    • Number of similar products: 13
  • Engagement: Low
    • Average number of comments: 1
  • Net use signal: 17.8%
    • Positive use signal: 17.8%
    • 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.

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