CRUBSTER is a social review platform based on trust. Decide where to go based on the average opinion of the people you follow directly or the opinion of local expert groups. Stop following the crowd!
Restaurant, bar or hotel's reviews from the people you trust
CRUBSTER is a social review platform based on trust. Decide where to go based on the average opinion of the people you follow directly or the opinion of local expert groups. Stop following the crowd!
👋🏽 Hey PH community 😃, I am beyond thrilled to introduce you to something I've poured my heart and soul into – CRUBSTER 🦀. 📱 An app that's not just a review platform but my brainchild, my passion project along with my co-founder Francesco Villani. You know that feeling when you want to try a new place where to eat or drink something and you're about to go out, and you're drowning in a sea of reviews, not knowing which ones to trust? We've been there too. That's why we created CRUBSTER – to make
Good job, best of luck to you today 🚀🦄
Just came across CRUBSTER, and I'm genuinely excited about its approach to revolutionizing social reviews. The emphasis on trust and authenticity in deciding where to eat or drink is refreshing. At [OpenDigg]( https://www.opendigg.com/ ), we admire platforms that innovate to improve user experiences, and CRUBSTER's mission to cut through the noise of generic reviews aligns perfectly with our values. The unique features like the Objectivity Score and Follower Average show a deep understanding of
@andrea_grandotto congrats on your launch.
Hey @andrea_grandotto I'm genuinely excited about how Crubster prioritizes trust in reviews from our own circles. It's a fresh take that could truly redefine decision-making for dining and lodging! Have you thought about integrating a feature that allows users to create and share their own curated lists? This could add a personal touch, making the experience even more relatable and useful :)
A measure of community engagement at launch. Higher means more people noticed and interacted with the product. It's a traction signal, not a quality rating.
Discussion threads divided by interest score. Above 0.30 is strong. Below 0.15 suggests the product got clicks but not conversation.
Categories come from the product's launch tags. Most products appear in 2-3 categories. The primary category is listed first.
The scores reflect launch-period engagement. Historical data is preserved and doesn't change retroactively. The build date at the bottom shows when the index was last refreshed.