PHBench
PHBench is a benchmark by an unnamed developer for predicting Series A funding using Product Hunt launch signals, analyzing 67,291 launches and 528 verified Series A events.
What is PHBench?
PHBench is an open benchmark that predicts whether a Product Hunt launch will lead to a Series A funding round within 18 months. It analyzes launch signals from 67,292 launches across seven years (2019–2025), with 528 verified Series A events. The platform trains and ranks machine learning models on this data, and its best model scores every new launch. It is a research project by an unnamed developer, in collaboration with the University of Oxford.
Application scenarios
Investor scouting
Identify high-potential startups from their Product Hunt launch data before they raise Series A.
Startup fundraising
Gauge the likelihood of Series A funding based on launch performance metrics.
Product launch strategy
Optimize launch timing and positioning using data-driven insights on what signals matter.
Academic research
Study the correlation between early-stage product signals and venture capital outcomes.
Machine learning benchmarking
Test and compare predictive models on a standardized, audited dataset.
Core Features
Leaderboard ranking
Compare model performance on F0.5, AP, REC, and AUC metrics across nine submitted models, including a top-3 ensemble.
Signal analysis
Examine six features that predict Series A (e.g., daily rank on launch) and four that don't, with lift, importance, and p-values.
Reproducible methodology
Every label is manually audited, every feature documented, and every submission reruns on a hash-pinned test set.
Open benchmark
Submit your own model for evaluation against the held-out test set (phbench_public_test.csv).
Base rate insight
Only 0.78% of launches raise Series A, with the best model achieving 4.7× lift over random.
Historical data scope
Covers 67,292 launches from 2019 to 2025, with 528 verified Series A events within an 18-month window.
Target users
This tool is designed for venture capital analysts, startup founders, product managers, data scientists, and researchers studying early-stage funding signals. It is especially useful for anyone who wants to quantify the impact of a Product Hunt launch on future fundraising outcomes.
How to use PHBench?
Visit the official website at https://www.phbench.com/ to explore the leaderboard, view signal analysis, and download the dataset. For model submission, you must use the held-out test set (phbench_public_test.csv) and follow the documented methodology. The site provides a citation format for academic use.
Effect review
PHBench delivers a focused, data-backed approach to predicting Series A funding from Product Hunt signals. The leaderboard shows clear performance tiers, with the top ensemble achieving 0.284 F0.5 and 0.840 AUC, significantly outperforming baseline logistic regression. The signal analysis is particularly valuable, revealing that daily rank on launch day provides a 3.5× lift over the base rate. While the benchmark is open and reproducible, it is limited to a single platform (Product Hunt) and a narrow funding event (Series A within 18 months). For investors and founders, it offers a practical, evidence-based tool to assess launch quality, but it should complement—not replace—traditional due diligence.
Frequently Asked Questions
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PHBench - AI Tool Detail
PHBench is a benchmark by an unnamed developer for predicting Series A funding using Product Hunt launch signals, analyzing 67,291 launches and 528 verified Series A events.
Category：Market research
Visit Link：https://www.phbench.com/
Tags：Series A prediction、Product Hunt analytics、funding benchmark、startup signals、AI tool evaluation