10 Apr 2025
Social Media

An app that finds reviews from people you know, in other words you can ...

...filter reviews on the internet by levels of connection you have to the reviewer

Confidence
Engagement
Net use signal
Net buy signal

Idea type: Minimal Signal

There’s barely any market activity - either because the problem is very niche or not important enough. You’ll need to prove real demand exists before investing significant time.

Should You Build It?

Not yet, validate more.


Your are here

Your idea of an app that filters reviews based on connections to the reviewer falls into a category with minimal market validation. This means there isn't strong evidence suggesting a widespread demand for this specific solution. Since we only found one similar product, we have low confidence in the idea category assignment, and this underscores the need for thorough validation. The absence of comments on the similar product further emphasizes the lack of engagement in this niche. Without clear signals of interest or adoption, it's crucial to approach development cautiously and prioritize validating the core assumption that people desire reviews from their network. Given the minimal signal in the market, significant investment should be postponed until stronger demand is demonstrated. Right now, this looks like a niche problem that might not be important enough for many people.

Recommendations

  1. Given the limited validation and engagement in this space, your initial focus should be on directly engaging with potential users. Post in online communities, such as subreddits related to product reviews, online shopping, or specific hobbies, and present your idea as a problem you're trying to solve. Gauge interest by asking if others have faced similar frustrations with untrustworthy or irrelevant reviews.
  2. Before building the app, offer to manually filter reviews for 2-3 potential customers. This could involve reading reviews from different sources and compiling summaries based on the reviewers' connections (e.g., LinkedIn connections, Facebook friends). This hands-on approach will provide invaluable insights into user needs and the actual value of your solution.
  3. Create a simple explainer video that illustrates the problem your app solves and how it works. Share it on social media and measure how many people watch it fully and whether they share it with others. Engagement metrics like watch time and shares can indicate the level of interest in your solution.
  4. Gauge serious interest by asking people to join a waiting list for the app and offer an incentive for doing so, like a discount or early access. To further validate commitment, consider asking for a small, refundable deposit to join the waiting list. This helps separate genuinely interested users from those who are merely curious.
  5. Set a clear deadline for your validation efforts. If you can't find 5 truly interested people willing to commit (through deposit or significant engagement) within 3 weeks, it's crucial to reassess the idea. This doesn't necessarily mean abandoning it, but it might require pivoting or refining the concept to address a more pressing need.

Questions

  1. What specific frustrations are people experiencing with current review systems that your app directly addresses, and how can you quantify these frustrations through user interviews or surveys?
  2. Beyond filtering by connection level, what other criteria would make reviews more relevant and trustworthy to users, and how can you incorporate these into your app's functionality?
  3. How can you leverage existing social networks and platforms to establish and verify connections between reviewers and users, while also respecting user privacy and data security?

Your are here

Your idea of an app that filters reviews based on connections to the reviewer falls into a category with minimal market validation. This means there isn't strong evidence suggesting a widespread demand for this specific solution. Since we only found one similar product, we have low confidence in the idea category assignment, and this underscores the need for thorough validation. The absence of comments on the similar product further emphasizes the lack of engagement in this niche. Without clear signals of interest or adoption, it's crucial to approach development cautiously and prioritize validating the core assumption that people desire reviews from their network. Given the minimal signal in the market, significant investment should be postponed until stronger demand is demonstrated. Right now, this looks like a niche problem that might not be important enough for many people.

Recommendations

  1. Given the limited validation and engagement in this space, your initial focus should be on directly engaging with potential users. Post in online communities, such as subreddits related to product reviews, online shopping, or specific hobbies, and present your idea as a problem you're trying to solve. Gauge interest by asking if others have faced similar frustrations with untrustworthy or irrelevant reviews.
  2. Before building the app, offer to manually filter reviews for 2-3 potential customers. This could involve reading reviews from different sources and compiling summaries based on the reviewers' connections (e.g., LinkedIn connections, Facebook friends). This hands-on approach will provide invaluable insights into user needs and the actual value of your solution.
  3. Create a simple explainer video that illustrates the problem your app solves and how it works. Share it on social media and measure how many people watch it fully and whether they share it with others. Engagement metrics like watch time and shares can indicate the level of interest in your solution.
  4. Gauge serious interest by asking people to join a waiting list for the app and offer an incentive for doing so, like a discount or early access. To further validate commitment, consider asking for a small, refundable deposit to join the waiting list. This helps separate genuinely interested users from those who are merely curious.
  5. Set a clear deadline for your validation efforts. If you can't find 5 truly interested people willing to commit (through deposit or significant engagement) within 3 weeks, it's crucial to reassess the idea. This doesn't necessarily mean abandoning it, but it might require pivoting or refining the concept to address a more pressing need.

Questions

  1. What specific frustrations are people experiencing with current review systems that your app directly addresses, and how can you quantify these frustrations through user interviews or surveys?
  2. Beyond filtering by connection level, what other criteria would make reviews more relevant and trustworthy to users, and how can you incorporate these into your app's functionality?
  3. How can you leverage existing social networks and platforms to establish and verify connections between reviewers and users, while also respecting user privacy and data security?

  • Confidence: Low
    • Number of similar products: 1
  • Engagement: Low
    • Average number of comments: 0
  • Net use signal: 0.0%
    • Positive use signal: 0.0%
    • 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.

Similar products

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