Should I Build It Should I Build It
02 Jun 2025
User Experience Customer Communication Analytics

an app that collects and monitors customer feedback for action

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 entering a crowded space, with around 30 similar products already out there, which puts your idea squarely in the 'Swamp' category. These tools aim to collect and monitor customer feedback, then turn that into actionable insights. While there's clearly a need for this, as evidenced by the number of competitors, average engagement is quite low. This indicates that current solutions may not be fully meeting user needs, and, crucially, that the market may not be that big, i.e. most businesses don't really care that much about actively collecting user feedback. You'll need to differentiate to cut through the noise, i.e. find a niche where customers really care. The good news is, based on other products, there is a strong inclination to buy these tools (as expressed by the high buy percentile) so this suggests people are willing to invest in solving this problem, BUT the low engagement score suggests people don't really use them that much, so you need to address this too.

Recommendations

  1. First, deeply research why existing customer feedback solutions haven't fully succeeded. Don't just assume you know; talk to potential users and those who've tried other tools. Look for the common pain points and unmet needs. The low engagement of similar products suggests many may be gathering dust - find out why!
  2. If you still want to proceed, find a very specific niche or group that is underserved by current solutions. Don't try to be everything to everyone. For example, perhaps focus on collecting feedback specifically for SaaS onboarding experiences or restaurants in a certain city. Carve out a niche where you can deeply understand and cater to the unique needs of that segment.
  3. Consider building tools or integrations for the existing customer feedback platforms instead of creating a whole new platform. Is there a gap in their features that you could fill? Could you create a specialized integration with a CRM or project management tool to automatically action the feedback?
  4. Explore adjacent problems that might be more promising. Instead of focusing only on customer feedback, could you expand to include user research, product discovery, or competitive analysis? Broadening the scope might reveal a bigger, more lucrative opportunity. Related, FeedbackHQ is a feedback tool for Notion, maybe that's the path?
  5. Given the concerns around data privacy in similar products like Feedback., prioritize building trust and transparency into your feedback collection process from the start. Clearly communicate how data is stored, used, and protected. Address privacy concerns proactively to build user confidence.
  6. Address the potential for impersonal, robotic AI responses which was a concern for similar products like ReplyToAppReviews. If you're using AI, focus on customization options and ensure there's a way to inject a human touch to avoid alienating users. Templates and scenarios are a good start, but personalization is key.
  7. In light of the spam issues encountered by similar products like Feedbase, prioritize robust spam filtering and moderation features from day one. Implement mechanisms to identify and block malicious or irrelevant feedback to maintain data quality.
  8. Given the importance of clear communication highlighted by the unclear purpose that was found for similar product PromptPortals, focus relentlessly on making the product's value proposition crystal clear on your landing page and in your marketing materials. Users should instantly understand how your tool solves their problem.
  9. Based on Feedback River's experience, explore integrations with platforms like Product Hunt to gain early visibility and feedback. Consider offering exclusive discounts or promotions to attract initial users and build momentum.

Questions

  1. Considering the existing competition and low engagement, what unique value proposition will your app offer that compels businesses to not only pay for it but actively integrate it into their workflows and continuously use it?
  2. Given the data privacy concerns in similar AI-powered feedback tools, how will you ensure data security and user trust while also delivering personalized and actionable insights? Can you be fully compliant and useful?
  3. How will you measure the actionable impact of the feedback collected through your app? What metrics will demonstrate that the insights derived from your app lead to tangible improvements in your customers' products or services and, crucially, their bottom line?

Your are here

You're entering a crowded space, with around 30 similar products already out there, which puts your idea squarely in the 'Swamp' category. These tools aim to collect and monitor customer feedback, then turn that into actionable insights. While there's clearly a need for this, as evidenced by the number of competitors, average engagement is quite low. This indicates that current solutions may not be fully meeting user needs, and, crucially, that the market may not be that big, i.e. most businesses don't really care that much about actively collecting user feedback. You'll need to differentiate to cut through the noise, i.e. find a niche where customers really care. The good news is, based on other products, there is a strong inclination to buy these tools (as expressed by the high buy percentile) so this suggests people are willing to invest in solving this problem, BUT the low engagement score suggests people don't really use them that much, so you need to address this too.

Recommendations

  1. First, deeply research why existing customer feedback solutions haven't fully succeeded. Don't just assume you know; talk to potential users and those who've tried other tools. Look for the common pain points and unmet needs. The low engagement of similar products suggests many may be gathering dust - find out why!
  2. If you still want to proceed, find a very specific niche or group that is underserved by current solutions. Don't try to be everything to everyone. For example, perhaps focus on collecting feedback specifically for SaaS onboarding experiences or restaurants in a certain city. Carve out a niche where you can deeply understand and cater to the unique needs of that segment.
  3. Consider building tools or integrations for the existing customer feedback platforms instead of creating a whole new platform. Is there a gap in their features that you could fill? Could you create a specialized integration with a CRM or project management tool to automatically action the feedback?
  4. Explore adjacent problems that might be more promising. Instead of focusing only on customer feedback, could you expand to include user research, product discovery, or competitive analysis? Broadening the scope might reveal a bigger, more lucrative opportunity. Related, FeedbackHQ is a feedback tool for Notion, maybe that's the path?
  5. Given the concerns around data privacy in similar products like Feedback., prioritize building trust and transparency into your feedback collection process from the start. Clearly communicate how data is stored, used, and protected. Address privacy concerns proactively to build user confidence.
  6. Address the potential for impersonal, robotic AI responses which was a concern for similar products like ReplyToAppReviews. If you're using AI, focus on customization options and ensure there's a way to inject a human touch to avoid alienating users. Templates and scenarios are a good start, but personalization is key.
  7. In light of the spam issues encountered by similar products like Feedbase, prioritize robust spam filtering and moderation features from day one. Implement mechanisms to identify and block malicious or irrelevant feedback to maintain data quality.
  8. Given the importance of clear communication highlighted by the unclear purpose that was found for similar product PromptPortals, focus relentlessly on making the product's value proposition crystal clear on your landing page and in your marketing materials. Users should instantly understand how your tool solves their problem.
  9. Based on Feedback River's experience, explore integrations with platforms like Product Hunt to gain early visibility and feedback. Consider offering exclusive discounts or promotions to attract initial users and build momentum.

Questions

  1. Considering the existing competition and low engagement, what unique value proposition will your app offer that compels businesses to not only pay for it but actively integrate it into their workflows and continuously use it?
  2. Given the data privacy concerns in similar AI-powered feedback tools, how will you ensure data security and user trust while also delivering personalized and actionable insights? Can you be fully compliant and useful?
  3. How will you measure the actionable impact of the feedback collected through your app? What metrics will demonstrate that the insights derived from your app lead to tangible improvements in your customers' products or services and, crucially, their bottom line?

  • Confidence: High
    • Number of similar products: 30
  • Engagement: Low
    • Average number of comments: 3
  • Net use signal: 15.6%
    • Positive use signal: 15.6%
    • Negative use signal: 0.0%
  • Net buy signal: 1.8%
    • Positive buy signal: 1.8%
    • 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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