05 Jun 2025
SaaS

A simple feedback and reviews collector tool for restaurant owners

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 your restaurant feedback tool. The 'Swamp' category isn't the most encouraging, indicating that many similar solutions exist but haven't found widespread success. With 17 similar products already identified, competition is significant. Engagement, measured by average comments, is low across these similar products. This suggests that it may be challenging to grab users' attention and get them to actively engage with your tool. The lack of strong 'use' and 'buy' signals from existing solutions further emphasizes the uphill battle. In short, many have tried to solve this problem, and it may be difficult to stand out, but with some creative pivoting, you can differentiate yourself and find a foothold in the market, provided you can find a specific niche or underserved segment.

Recommendations

  1. First, deeply investigate why existing restaurant feedback tools haven't truly taken off. Talk to restaurant owners who've tried these tools. What were their pain points? What features were missing? Understanding the shortcomings of current solutions is crucial to avoid repeating their mistakes.
  2. Instead of targeting all restaurants, focus on a niche. This could be fine dining, fast casual, or restaurants with a specific cuisine (e.g., vegan, gluten-free). Tailor your tool to address the unique feedback needs of this niche. For example, fine dining restaurants might prioritize detailed feedback on ambiance and service, while fast-casual places might focus on speed and order accuracy.
  3. Explore whether you can offer your tool to the existing providers of reviews and feedback. Rather than directly competing, could you integrate your solution or create a bolt-on that improves their offerings? For example, create a plugin or extension for existing review management systems.
  4. Given some users in similar spaces asked for features like 'fake review detection,' incorporating advanced features to combat fake reviews or manage online reputation is crucial. Address this by proactively integrating reputation management features into your tool, offering restaurants the ability to monitor and respond to reviews across multiple platforms.
  5. Before dedicating significant resources, create a very basic, minimum viable product (MVP) and test it with a small group of restaurants in your target niche. Collect feedback on your MVP and iterate rapidly. Use this process to validate your assumptions and ensure you're building a tool that restaurants actually want to use.

Questions

  1. What specific, unique data insights can you provide to restaurant owners that they can't get from existing feedback and review platforms? Can you provide data visualizations or reports that are not offered by competitors?
  2. How can you leverage AI or machine learning to provide more personalized and actionable feedback for restaurant owners, going beyond simple ratings and reviews?
  3. Given the low engagement seen in similar products, what innovative strategies can you implement to encourage restaurant owners to actively use and integrate your feedback tool into their daily operations?

Your are here

You're entering a crowded space with your restaurant feedback tool. The 'Swamp' category isn't the most encouraging, indicating that many similar solutions exist but haven't found widespread success. With 17 similar products already identified, competition is significant. Engagement, measured by average comments, is low across these similar products. This suggests that it may be challenging to grab users' attention and get them to actively engage with your tool. The lack of strong 'use' and 'buy' signals from existing solutions further emphasizes the uphill battle. In short, many have tried to solve this problem, and it may be difficult to stand out, but with some creative pivoting, you can differentiate yourself and find a foothold in the market, provided you can find a specific niche or underserved segment.

Recommendations

  1. First, deeply investigate why existing restaurant feedback tools haven't truly taken off. Talk to restaurant owners who've tried these tools. What were their pain points? What features were missing? Understanding the shortcomings of current solutions is crucial to avoid repeating their mistakes.
  2. Instead of targeting all restaurants, focus on a niche. This could be fine dining, fast casual, or restaurants with a specific cuisine (e.g., vegan, gluten-free). Tailor your tool to address the unique feedback needs of this niche. For example, fine dining restaurants might prioritize detailed feedback on ambiance and service, while fast-casual places might focus on speed and order accuracy.
  3. Explore whether you can offer your tool to the existing providers of reviews and feedback. Rather than directly competing, could you integrate your solution or create a bolt-on that improves their offerings? For example, create a plugin or extension for existing review management systems.
  4. Given some users in similar spaces asked for features like 'fake review detection,' incorporating advanced features to combat fake reviews or manage online reputation is crucial. Address this by proactively integrating reputation management features into your tool, offering restaurants the ability to monitor and respond to reviews across multiple platforms.
  5. Before dedicating significant resources, create a very basic, minimum viable product (MVP) and test it with a small group of restaurants in your target niche. Collect feedback on your MVP and iterate rapidly. Use this process to validate your assumptions and ensure you're building a tool that restaurants actually want to use.

Questions

  1. What specific, unique data insights can you provide to restaurant owners that they can't get from existing feedback and review platforms? Can you provide data visualizations or reports that are not offered by competitors?
  2. How can you leverage AI or machine learning to provide more personalized and actionable feedback for restaurant owners, going beyond simple ratings and reviews?
  3. Given the low engagement seen in similar products, what innovative strategies can you implement to encourage restaurant owners to actively use and integrate your feedback tool into their daily operations?

  • Confidence: High
    • Number of similar products: 17
  • Engagement: Low
    • Average number of comments: 3
  • Net use signal: 12.9%
    • Positive use signal: 12.9%
    • Negative use signal: 0.0%
  • Net buy signal: 1.0%
    • Positive buy signal: 1.0%
    • 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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Hi HN,Over the past 4 months I built Reviewcheck on the side. Reviewcheck collects reviews for a business from different platforms such as Google, Trustpilot and Facebook and automatically generates a report with actionable insights to improve.I actually had the idea when I was in a restaurant that received quite some reviews from customers, but hadn’t changed anything in the last 10 years. I think (and hope haha) there are a lot of similar businesses that collect online reviews but aren’t really leveraging them because they do not have the time or do not want to pay a monthly subscription.An example report can be found at https://www.reviewcheck.co/example-report. Since the possibilities for this report are endless, I am curious to hear what you are missing. General feedback or questions on how it was built are also very welcome of course. Thanks a lot for taking the time to check it out!


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