BigIdeasDB Research
Original studies built on BigIdeasDB's proprietary datasets: over 1M complaints, reviews, and discussions, 8,699 tracked startups, 17,611 funded companies, and 30,322 companies on Stripe. Every study is dated, sourced, and traceable to the underlying data. See the research methodology for how the data is collected and scored, authored by Om Patel.
LLM Wars: Pain-Point Extraction Benchmark
The first multi-dimensional benchmark of how well large language models extract structured pain points from real software feedback.
- Dataset:
- 10 models, 12,000 records, 900-record human gold standard
- Updated:
- 2026
- Author:
- Om Patel
State of SaaS Pain Points 2026
The most complained-about software categories and the systemic failures behind them, ranked by severity and market gap.
- Dataset:
- 5,040 category-level pain points, 1M+ complaints analyzed
- Updated:
- July 16, 2026 snapshot
- Author:
- Om Patel
State of SaaS Acquisitions 2026
Asking prices, revenue multiples, and buyer theses for SaaS businesses currently changing hands.
- Dataset:
- Live acquire.com listings across categories
- Updated:
- 2026
- Author:
- Om Patel
SaaS Revenue Benchmarks 2026
Real MRR, growth, and multiple benchmarks by category and cluster, not survey estimates.
- Dataset:
- 8,699 tracked startups, revenue and growth by category
- Updated:
- July 16, 2026 snapshot
- Author:
- Om Patel
What VCs Are Funding 2026
Where capital is concentrating by sector, measured from funded-company momentum rather than headlines.
- Dataset:
- 17,611 funded companies, AI-scored by category and momentum
- Updated:
- 2026
- Author:
- Om Patel
SaaS Market Saturation 2026
Which SaaS niches are crowded and which are under-served, measured from live company counts.
- Dataset:
- 30,322 companies on Stripe across 83 categories
- Updated:
- July 16, 2026 snapshot
- Author:
- Om Patel
How this research is produced
BigIdeasDB analyzes complaints and reviews at scale, extracts structured pain points, and scores them by severity and market gap. The full collection process, scoring definitions, model usage, and known limitations are documented on the methodology page. For product-specific technical detail, see the data sources overview.