# PHBench Benchmark aberto para prever investimentos Série A com sinais de lançamentos do Product Hunt - Findings24: - Site: - Preços: Free - Categorias: Analista de dados com IA, Análise de marketing com IA, Assistente de pesquisa com IA ## O que é PHBench? PHBench is an open benchmark for predicting whether a Product Hunt launch will eventually raise a Series A round. The site frames the problem as ranking launches from a 24-hour Product Hunt signal window and evaluating models on verified funding outcomes within an 18-month window. It combines a labeled historical dataset, a public leaderboard, and weekly prediction views. The benchmark page says models are trained and ranked on 67,292 launches from 2019 to 2025, with 528 verified Series A events, and that the public test set stays held out until final submission. ## O que PHBench pode fazer? ### Model leaderboard Ranks models that predict Series A outcomes from Product Hunt launch signals, with a public leaderboard that compares methods such as ensembles, LightGBM, XGBoost, and language-model baselines. ### Weekly predictions Scores new Product Hunt launches and surfaces weekly prediction results, including lift rankings for the current week’s launches. ### Historical launch dataset Uses a dataset of 67,292 Product Hunt launches spanning 2019 to 2025 and 528 verified Series A events, giving the benchmark a documented evaluation base. ### Signal analysis Shows which signals are most associated with Series A outcomes, including launch-day rank, maker follower count, votes-per-comment ratio, and topic-related features. ### Reproducible methodology Documents its benchmark setup with manual label auditing, feature documentation, a held-out public test set, and hash-pinned reruns for submissions. ### Project resources Provides project links for the dataset, methodology, paper, GitHub, and newsletter so users can inspect the benchmark and follow updates. ## Casos de uso ### Benchmark model performance Researchers or builders can use PHBench to compare different modeling approaches on the same Product Hunt-to-Series-A task and inspect how their method ranks on the public leaderboard. ### Review weekly launch signals Founders or operators who follow Product Hunt can review weekly predictions to see which launches the benchmark ranks as more likely to raise a Series A. ### Study launch signal patterns Data practitioners can examine the signal analysis section to understand which launch features appear most predictive in the benchmark and which ones are treated as noise. ### Use a reproducible reference Teams interested in reproducible evaluation can use the documented methodology, held-out test set, and citable paper to understand how the benchmark was built and submitted. ## Perguntas frequentes ### What does PHBench measure? PHBench is an open benchmark for predicting whether a Product Hunt launch will eventually raise a Series A funding round within 18 months. ### Is there a public pricing page? The site shows an open benchmark, leaderboard, dataset, methodology, and prediction views. It does not show a public pricing plan on the pages provided; the pricing URL returns a 404. ### How are predictions evaluated? The benchmark is built on Product Hunt launch signals and ranks models on held-out test data. The home page says submissions rerun on a hash-pinned test set, and the public test set is held out until final submission. ### What kind of output does PHBench provide? The site presents weekly predictions for Product Hunt launches and a leaderboard of models. It also shows a “Get weekly predictions” call to action and a predictions page with scored launches. ## Informações rápidas - **Category**: Developer Tool - **Product type**: Open benchmark - **Primary use**: Predicting Series A from Product Hunt signals - **Dataset size**: 67,292 launches - **Verified outcomes**: 528 Series A events - **Source domain**: phbench.com