06 May 2025
Dating

Dating app for college students where you can give reviews on user ...

...profiles

Confidence
Engagement
Net use signal
Net buy signal

Idea type: Pivot

Current solutions aren’t working well, but there might be a way to adjust your approach. This isn’t about starting over, but rather making thoughtful changes based on what you’re learning.

Should You Build It?

No. Think & pivot.


Your are here

Dating apps are tough to crack, and adding a review element puts you in a crowded space with a few similar attempts. The good news is that with 4 similar products, we have medium confidence that you're onto something people have considered, but the competition is real. The average number of comments on these similar products is 6, indicating medium engagement. However, the lack of positive 'use' or 'buy' signals suggests users aren't explicitly asking for or willing to pay for this type of feature in existing dating apps. Flurry got some excitement initially for optimizing dating profiles, but users questioned respectful feedback. Also Dating Playground was considered creepy, and Get Rated had a comment deleted. AI to Find Your Best Dating App Photos has errors and got flagged for innapropriate content. This suggests a pivot is required, rather than a straight build. Proceed with caution and a lot of user feedback.

Recommendations

  1. First, list the top 3 reasons people dislike existing dating apps and profile review systems. Are they concerned about superficiality, disrespectful feedback, or biased AI? Understanding these pain points is crucial before proceeding.
  2. Next, sketch out how your solution could avoid these pitfalls. How will you ensure respectful and constructive feedback? Can you implement features that promote genuine connections over superficial ratings? Addressing these concerns head-on is key.
  3. Before building anything substantial, test your revised approach with at least 5 potential users. Show them mockups or prototypes and gather their feedback on your proposed solutions to the identified pain points. Iterate based on their input.
  4. Consider focusing on a specific niche within the college student demographic that might benefit most from profile reviews. Are you targeting students seeking serious relationships, or those looking for casual connections? Tailoring your approach to a specific group can increase your chances of success.
  5. Set a 4-week deadline to evaluate the results of your pivot. Track key metrics such as user engagement, feedback quality, and the number of meaningful connections made. If the pivot doesn't show promise within this timeframe, re-evaluate your approach or consider exploring alternative ideas.
  6. Research the moderation techniques employed by dating apps and incorporate similar measures to foster a positive and safe environment on your platform. Given the experience of "AI to Find Your Best Dating App Photos" with content filtering, prioritize content moderation from day one.
  7. Given that users found "Dating Playground" to be creepy, explicitly state and heavily promote the values of respect, consent, and constructive feedback in your app's marketing and onboarding materials.
  8. Explore the possibility of integrating with existing social media platforms to allow users to import photos and profile information. This would streamline the profile creation process and potentially address the issue of superficial profiles.

Questions

  1. How will you prevent the review system from becoming a source of negativity and superficial judgment among college students?
  2. What specific mechanisms will you implement to ensure that feedback is constructive, respectful, and contributes to more meaningful connections?
  3. Given the existing concerns around AI in similar apps, how will you build trust and transparency into your review system?

Your are here

Dating apps are tough to crack, and adding a review element puts you in a crowded space with a few similar attempts. The good news is that with 4 similar products, we have medium confidence that you're onto something people have considered, but the competition is real. The average number of comments on these similar products is 6, indicating medium engagement. However, the lack of positive 'use' or 'buy' signals suggests users aren't explicitly asking for or willing to pay for this type of feature in existing dating apps. Flurry got some excitement initially for optimizing dating profiles, but users questioned respectful feedback. Also Dating Playground was considered creepy, and Get Rated had a comment deleted. AI to Find Your Best Dating App Photos has errors and got flagged for innapropriate content. This suggests a pivot is required, rather than a straight build. Proceed with caution and a lot of user feedback.

Recommendations

  1. First, list the top 3 reasons people dislike existing dating apps and profile review systems. Are they concerned about superficiality, disrespectful feedback, or biased AI? Understanding these pain points is crucial before proceeding.
  2. Next, sketch out how your solution could avoid these pitfalls. How will you ensure respectful and constructive feedback? Can you implement features that promote genuine connections over superficial ratings? Addressing these concerns head-on is key.
  3. Before building anything substantial, test your revised approach with at least 5 potential users. Show them mockups or prototypes and gather their feedback on your proposed solutions to the identified pain points. Iterate based on their input.
  4. Consider focusing on a specific niche within the college student demographic that might benefit most from profile reviews. Are you targeting students seeking serious relationships, or those looking for casual connections? Tailoring your approach to a specific group can increase your chances of success.
  5. Set a 4-week deadline to evaluate the results of your pivot. Track key metrics such as user engagement, feedback quality, and the number of meaningful connections made. If the pivot doesn't show promise within this timeframe, re-evaluate your approach or consider exploring alternative ideas.
  6. Research the moderation techniques employed by dating apps and incorporate similar measures to foster a positive and safe environment on your platform. Given the experience of "AI to Find Your Best Dating App Photos" with content filtering, prioritize content moderation from day one.
  7. Given that users found "Dating Playground" to be creepy, explicitly state and heavily promote the values of respect, consent, and constructive feedback in your app's marketing and onboarding materials.
  8. Explore the possibility of integrating with existing social media platforms to allow users to import photos and profile information. This would streamline the profile creation process and potentially address the issue of superficial profiles.

Questions

  1. How will you prevent the review system from becoming a source of negativity and superficial judgment among college students?
  2. What specific mechanisms will you implement to ensure that feedback is constructive, respectful, and contributes to more meaningful connections?
  3. Given the existing concerns around AI in similar apps, how will you build trust and transparency into your review system?

  • Confidence: Medium
    • Number of similar products: 4
  • Engagement: Medium
    • Average number of comments: 6
  • Net use signal: -2.4%
    • Positive use signal: 7.6%
    • Negative use signal: 10.0%
  • Net buy signal: -3.3%
    • Positive buy signal: 0.0%
    • Negative buy signal: 3.3%

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

Relevance

Flurry - Optimise dating profiles with community feedback

Flurry lets users share their dating profile to get feedback without sharing on social media or hiring dating coaches. It makes profile tuning easy in a private, friendly space.

Flurry's Product Hunt launch is met with congratulations and excitement. Users praise the app as a game-changer for dating profile feedback and a valuable tool. There's curiosity about incentives for joining and potential learning features. Some anticipate the platform being heavily profile-focused. One user highlights Flurry's optimization of dating profiles through community feedback and another user wants to see more third party integrations.

Users question how Flurry ensures respectful feedback and the value proposition for users. Concerns exist regarding the platform potentially being filled with superficial profiles rather than genuine connections. Additionally, users are requesting more third-party integrations to enhance the app's functionality.


Avatar
85
13
15.4%
13
85
15.4%
Relevance

Ever Been Rated by an AI Date? Try Dating Playground and Get Feedback

Hey HackerNews folks!I first launched DatingAI.pro to help people improve their dating profiles, get reply suggestions, etc but to that I got feedback where people pointed out that someone could just impersonate their entire profile which made sense and I thought what if I could actually help people really get better at texting or conversations by giving them feedback and letting them improve via suggestions.I understand a human date can't be replaced but certainly we could help to an extent. NOTE - THIS IS NOT AN AI GIRLFRIEND.This is how it works: 1. Swipe from profiles of the opposite gender and then you're matched with someone. 2. Start an engaging chat & earn or lose points based on your charm (or lack thereof). 3. Simultaneously get reply suggestions to navigate the conversation. 4. Receive a final verdict: Would they like to go out on a date with you?And the best part? Those points aren't just for bragging rights they can be redeemed them for other features in the tool. Think of it as a dating simulator with tangible rewards.Would love to know your thoughts

Users expressed concerns about the website feeling creepy and the AI gender focus being unnecessary. The UX/UI needs improvement, and the Tinder simulator app requires enhancements. The scoring system appears random and lacks detailed feedback. Some users encountered a 'disallowed user agent' error in the Harmonic app. One user humorously mentioned that 'Grandma has been finally replaced.'

Users criticized the website for being creepy and having an unnecessary gender focus. They also mentioned that the UX/UI needs improvement. Other issues include unrealistic matches, lack of profile view, and the requirement to sign up. The scoring system was described as random and lacking detailed feedback. Additionally, there was a complaint about a 'disallowed user agent' error.


Avatar
14
5
-60.0%
-20.0%
5
14
Relevance

AI to Find Your Best Dating App Photos

I built a web app that uses a Resnet50 based model to score a photo's quality for dating apps. The app also contextualizes the score by showing how your photo scored compared to other users and giving feedback on how the photo can be improved.The feedback function uses deep learning models to identify the presence of certain characteristics in a user's photos to tell them how to improve, or what's good about the photo.There is a sign up component (sorry about that!). Would love any feedback on how to improve the product, market it, etc. Thank you!You can email me at loughlin@firstpic.ai

The comments mention an AI judging system similar to 'Hot or Not'. There is also a significant issue with an error code 400, indicating a content filter violation related to Azure OpenAI's content management policy, specifically due to sexual content being flagged.

Users criticized the product for relying solely on AI judgment, which led to errors. A specific error code 400 was mentioned, indicating that the response was filtered due to Azure OpenAI's content management policy. The error message suggested modifying the prompt and provided a link to the content filtering policies. The filtering was triggered by a medium severity sexual content filter, despite other categories being marked as safe.


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