Most SaaS competitive research is broken. Not because founders don't try — but because the method is fundamentally flawed.
Here's the typical process: Google a few competitor names, open 10 tabs, skim landing pages, note what pricing plans exist, maybe check G2 or Capterra for reviews. Done in an afternoon.
The problem? You just sampled 7-10 products in a market that might have 200+. You picked the ones that show up in Google, which means you found the incumbents and missed the challengers. And you read marketing copy, not real usage patterns.
Why Manual Research Fails at Scale
When we started collecting data for our indie SaaS dataset, we did it manually at first. One product at a time.
It took roughly 8 minutes per product to: find the product, identify the pricing model, classify the vertical, note the key features, and record whether there was a free tier or trial.
At that rate, 4,500 products = 600 hours of research. That's 15 full work weeks for one person.
Manual research also introduces bias systematically. You get tired. You start skimming. You notice patterns and start unconsciously confirming them. By product 200, you're not doing research anymore — you're validating what you already believe.
What Structured Data Unlocks
When you have a structured dataset — same fields, same format, across thousands of products — the analysis becomes possible in ways that weren't before.
Pricing distribution: not "my competitors seem to charge around $29/month" but actual percentile breakdowns across hundreds of comparable tools.
Free tier prevalence by vertical: some verticals are "free forever" land. Others barely offer trials. That's an important strategic signal if you're deciding whether to launch with a free tier.
Vertical density and whitespace: which niches are saturated versus underserved? With structured data you can count. Without it, you're guessing.
Lifetime deal patterns: which product types tend to go the AppSumo route? That data exists — but only if you collected it.
The Right Way to Use Competitive Data
Competitive datasets are inputs, not answers. Here's how we'd actually use one:
Step 1: Define your category first. What vertical are you in? Don't look at the whole market — filter to your niche and understand what's already there.
Step 2: Map the pricing distribution. Where is everyone? What's the floor, the ceiling, and where is the cluster? This tells you what the market will bear and where positioning opportunities exist.
Step 3: Look for the anomalies. What's priced strangely high or low for its category? Outliers often signal a different go-to-market (enterprise vs. self-serve) or a product with real differentiation.
Step 4: Check free tier patterns. Is your category "freemium expected" or not? If 80% of competitors offer a free tier and you don't, you need a strong reason why.
Step 5: Identify the gaps. What jobs-to-be-done exist in your vertical that nobody's serving? Structured data makes gaps visible.
What We Built
We spent weeks pulling together data on 4,500 indie SaaS products — pricing, free tier structures, verticals, and more — into a single structured CSV dataset.
This is not a list of every SaaS tool ever made. It's focused specifically on the indie/bootstrapped layer of the market: the tools that real founders build and real small teams buy. The segment where pricing is transparent, competition is visible, and you can actually learn from what's out there.
We found things we didn't expect:
- The $19-$49 band holds ~38% of all paid products
- 67% of products offer some form of free tier
- Healthcare and legal/compliance are notably underserved niches
- ~12% of products have appeared on lifetime deal platforms
Launching May 6 on Product Hunt
The full dataset is launching on Product Hunt on May 6, 2026.
It's available now at Gumroad for $39 — one-time payment, CSV format, immediate download:
webdatalabs.gumroad.com/l/dhfqy
If you're doing serious competitive research, building an investment thesis on indie SaaS, or just trying to understand the market before you build — this dataset saves you months of manual work.
Follow on Product Hunt May 6 to get notified at launch.
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