11 Jun 2025
Marketing

Been working on a small tool that analyzes video ads scene by scene ...

...and gives insights based on your campaign data. Still super early – no integrations yet, you plug the numbers in manually.

Confidence
Engagement
Net use signal
Net buy signal

Idea type: Early Niche

A small but engaged group cares enough to comment, suggesting real potential if you can improve the experience. This is your chance to create something better for people who clearly want a solution.

Should You Build It?

Yes, build now!


Your are here

You're entering an "Early Niche" market, which means there's a small but engaged group interested in a solution like yours. The fact that we found two similar products indicates there's some validation for the idea of video ad analysis tools. With an average of 59 comments across these similar products, engagement appears high, signaling that people are actively seeking solutions in this space. Given that the tools that are similar to your idea have high engagement on launch, it's a good sign that people are interested in this space. However, given the low n_matches, treat these signals with care. Focus on understanding the users of the current products and create a solution that delivers more value to them.

Recommendations

  1. Start by interviewing users of tools similar to yours to deeply understand their pain points with current solutions. Focus on the most active commenters from platforms like Product Hunt to gather valuable insights. The high engagement on similar product launches suggests a strong willingness to share feedback.
  2. Prioritize building a Minimum Viable Product (MVP) that directly addresses the key frustrations discovered in your user interviews. Given that you have no integrations yet, you can focus on what insight is most valuable for your users, so that you can start building a tool that provides that insight.
  3. Implement a pricing model from the beginning, even if it's a nominal fee. This demonstrates confidence in your tool's value and helps filter for serious users who are willing to invest in improving their ad performance. Consider that AI Ads Analyzer by GoMarble got many comments about its potential to save time and money for startups.
  4. Actively solicit feedback from your initial users (first 10 customers) and iterate rapidly based on their suggestions. Early-stage development should be heavily driven by user input to ensure you're building a product that truly meets their needs. Note that users of similar product launches requested more transparency in the AI's assessment basis and improvements to the UX/UI.
  5. Concentrate your efforts on serving this niche audience exceptionally well before attempting to expand to broader markets. Aim to acquire at least 20 satisfied, paying users who can serve as advocates for your tool. These users can help you build out your core offering. This is what the "Early Niche" idea category is all about!
  6. Analyze the AI Ads Analyzer by GoMarble. Note it's positive feedback, like streamlining ad analysis and improving ad performance, but pay special attention to their criticisms: the need for more transparency in the AI's quality assessment basis, and more clarity on how the AI adapts analysis to different ad types and brands. This can help you get a leg up on the competition.
  7. Explore integrating with other platforms, since the GoMarble tool integrates across various platforms. This could be a huge value add for your users and a differentiator that is valued by the market!

Questions

  1. Given the criticisms of existing tools regarding AI transparency, how can you make your analysis process more explainable and trustworthy to users?
  2. Considering the focus on time and cost savings, what specific metrics or insights can your tool provide that directly translate into tangible ROI for your users' ad campaigns?
  3. How might you leverage the high engagement seen in similar product launches to build a community around your tool and foster continuous feedback and improvement?

Your are here

You're entering an "Early Niche" market, which means there's a small but engaged group interested in a solution like yours. The fact that we found two similar products indicates there's some validation for the idea of video ad analysis tools. With an average of 59 comments across these similar products, engagement appears high, signaling that people are actively seeking solutions in this space. Given that the tools that are similar to your idea have high engagement on launch, it's a good sign that people are interested in this space. However, given the low n_matches, treat these signals with care. Focus on understanding the users of the current products and create a solution that delivers more value to them.

Recommendations

  1. Start by interviewing users of tools similar to yours to deeply understand their pain points with current solutions. Focus on the most active commenters from platforms like Product Hunt to gather valuable insights. The high engagement on similar product launches suggests a strong willingness to share feedback.
  2. Prioritize building a Minimum Viable Product (MVP) that directly addresses the key frustrations discovered in your user interviews. Given that you have no integrations yet, you can focus on what insight is most valuable for your users, so that you can start building a tool that provides that insight.
  3. Implement a pricing model from the beginning, even if it's a nominal fee. This demonstrates confidence in your tool's value and helps filter for serious users who are willing to invest in improving their ad performance. Consider that AI Ads Analyzer by GoMarble got many comments about its potential to save time and money for startups.
  4. Actively solicit feedback from your initial users (first 10 customers) and iterate rapidly based on their suggestions. Early-stage development should be heavily driven by user input to ensure you're building a product that truly meets their needs. Note that users of similar product launches requested more transparency in the AI's assessment basis and improvements to the UX/UI.
  5. Concentrate your efforts on serving this niche audience exceptionally well before attempting to expand to broader markets. Aim to acquire at least 20 satisfied, paying users who can serve as advocates for your tool. These users can help you build out your core offering. This is what the "Early Niche" idea category is all about!
  6. Analyze the AI Ads Analyzer by GoMarble. Note it's positive feedback, like streamlining ad analysis and improving ad performance, but pay special attention to their criticisms: the need for more transparency in the AI's quality assessment basis, and more clarity on how the AI adapts analysis to different ad types and brands. This can help you get a leg up on the competition.
  7. Explore integrating with other platforms, since the GoMarble tool integrates across various platforms. This could be a huge value add for your users and a differentiator that is valued by the market!

Questions

  1. Given the criticisms of existing tools regarding AI transparency, how can you make your analysis process more explainable and trustworthy to users?
  2. Considering the focus on time and cost savings, what specific metrics or insights can your tool provide that directly translate into tangible ROI for your users' ad campaigns?
  3. How might you leverage the high engagement seen in similar product launches to build a community around your tool and foster continuous feedback and improvement?

  • Confidence: Low
    • Number of similar products: 2
  • Engagement: High
    • Average number of comments: 59
  • Net use signal: 28.7%
    • Positive use signal: 28.7%
    • Negative use signal: 0.0%
  • Net buy signal: 1.9%
    • Positive buy signal: 1.9%
    • 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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