The SaaS Niches That Are Underserved Right Now (According to Data, Not Hype)
Everyone has a niche idea. The problem is most of them come from gut feelings, Reddit threads, or copying whatever YC funded last year. That's not a great filter.
I spent the last few months pulling together a dataset of 4,500 indie SaaS products - pricing, categories, growth signals, review counts, and more. Not to validate some grand theory. Just wanted to see what's actually out there. What I found was more interesting than I expected.
Here's what the data shows about niche selection specifically. Where are builders concentrated, where are they not, and which gaps might actually be worth something.
The crowded niches (avoid unless you have a real edge)
Let's start with what NOT to build. The most oversaturated categories in the dataset:
Project management - There's probably 300 products in here that are some variation of "task tracker with AI". Most of them have near-zero reviews. The market exists, Asana and Linear own it, and the indie versions struggle to differentiate on anything except price. I get why people build these - the problem is universally understood, demos well, easy to scope. But getting users is a different story.
AI writing tools - Still growing but fast becoming a commodity. The products with real traction are the ones that got there early (2022-2023). New entrants in 2024-2025 are mostly picking up scraps. Unless you're solving a very specific writing problem (legal drafting, localization, a particular industry format), you're entering a crowded space with shrinking margins.
General CRM - Tons of products. Very few with meaningful user counts. The problem is the bar is high - anyone comparing your CRM to HubSpot will be disappointed unless you're solving a very specific vertical problem. The indie CRMs that have traction tend to be ones that made a strong niche bet early and stuck with it.
"All-in-one" productivity suites - These show up constantly. The review counts are almost universally bad. Building something that does everything means you're competing with Notion, ClickUp, and a dozen other well-funded products on every dimension at once.
The pattern here isn't hard to spot. These niches have lots of products because they seem like big markets. But "big market" doesn't help you if the top 3 players have 90% of it and there are already 200 indie alternatives fighting over the rest. You're not going to out-feature Asana with a solo project.
What "low competition" actually looks like in this data
I looked at review counts as a rough proxy for traction. Products with 10+ reviews have some signal. Products with 50+ reviews have real users. Products with 200+ reviews are probably doing ok commercially.
When you cross-reference review density with category size, a few things stand out.
Category size vs. review density mismatch - There are categories with 40-60 products in the dataset but almost no reviews across all of them. That's a sign of a space where builders are building but nobody's really winning yet. Could be demand isn't there. Could also be nobody's built the right thing yet - sometimes the first 60 attempts at a problem are all slightly wrong, and then product 61 nails the positioning and takes off.
High reviews, few products - The more interesting case. There are some tight categories where a small number of products are getting solid review counts. That's the signal worth paying attention to. It means demand exists, the space isn't flooded, and the current solutions have users but haven't locked down the whole market yet.
Price anchoring by category - Another signal I wasn't expecting. Some categories have a consistent price range ($49-99/month) across most products, which tells you buyers in those niches have a budget. Categories where every product is $5-15/month suggest either a race to the bottom or genuinely price-sensitive buyers. The former is a trap for indie builders.
The honest answer is I can't tell you definitively which niches will pay off. The data shows demand signals, not guarantees. But it does help you filter out the obviously bad bets much faster than blog posts and podcasts about the "next big thing."
Specific patterns worth paying attention to
Vertical-specific tools are punching above their weight - Software for niche industries (logistics ops, field service, specific trades, niche compliance) shows interesting traction numbers relative to how few products are competing. These aren't glamorous. They won't get you on Twitter. But the buyers in these verticals pay real money and don't switch easily once something works for them. If you have domain experience in a specific industry, this is probably where to look first.
Developer tools with a clear job to be done - Tools that do one thing and do it well (not "AI-powered dev environment" but something specific like "generate realistic test data for your schema" or "monitor your API contract changes") tend to have decent review-to-product ratios. Developers are actually pretty good at paying for tools that save them time on a specific annoying task. The mistake is trying to build a platform instead of solving the one annoying thing.
Compliance and reporting adjacent - There's a cluster of products around things like privacy compliance, financial reporting, audit trails, and regulatory requirements. They look boring. The conversion rates in these categories (based on pricing vs. review signal) look healthier than the flashy stuff. Boring problems that companies legally have to solve don't really go away when budgets get cut. If anything, compliance gets more scrutiny when things are tight.
Internal tooling abstractions - Products that help small teams build their own internal tools without engineering resources. This is a real pain point. A lot of companies are stuck using spreadsheets for things that should be a proper internal dashboard or lightweight app. The products that nail this without requiring a developer to set up are showing good traction. The key seems to be making it feel immediately useful without a long configuration process.
Integration and workflow glue - Products that connect existing tools and automate handoffs between them. This is a crowded space in the abstract (Zapier exists), but the data shows lots of room in specific integration pairs and vertical-specific workflows. The broad automation platforms serve broad use cases - there's still work to be done for specific industries or software combinations.
What the data doesn't tell you (and why that matters)
A dataset like this is a starting point, not a decision engine. Here's what it can't give you:
- Whether a niche has paying demand vs. just curious free users trying things out
- The actual revenue behind review counts (a product with 50 reviews could be $500 MRR or $50k MRR)
- What's changed in the last 6 months that hasn't propagated into reviews yet
- Whether founders in a category are profitable or just grinding with no traction
What it CAN give you is a faster filter. Instead of spending weeks on market research based on blog posts and forums, you can look at what's actually out there, where the review density is, how products are priced, and make a more informed guess about where to look next. It's not a substitute for talking to potential customers - but it's a much better starting point than going in blind.
How to actually use this for niche research
If you're trying to figure out what to build next, here's how I'd approach it with this kind of data:
First, ignore the headlines. Everyone says AI is hot. Everyone says the next thing is agentic workflows. The data on indie products is more useful than macro trends because it shows you what's being built and what's getting users right now, not what VCs are excited about.
Find categories with review-to-product imbalance. If there are 50 products and 10 of them have 30+ reviews, that's a different signal than 50 products with 2 reviews each. The first case means something is working, you just need to figure out why the winners are winning.
Look at pricing relative to category. If a niche has products priced at $49-99/month and they have reviews, there's a buyer with a budget. That's useful. Some categories are full of $5/month tools that nobody reviews anyway - not a great place to try to build a business.
Don't build in a category just because it's small. Small can mean no demand, not low competition. The useful signal is small AND traction - where a few products are getting users but the space isn't defined yet.
Check what problems the reviewers are still complaining about. Review text is goldmine. The negative reviews on the top products in a category tell you what's still unsolved. That's your opening.
The full dataset
I put together the full 4,500 product dataset with all the fields - categories, pricing tiers, review counts, growth signals, and more. If you're doing competitive research or trying to figure out where to play, it probably saves 10-20 hours of manual work.
It's available at webdatalabs.gumroad.com/l/dhfqy for $39.
Also - if you're going to be on Product Hunt on May 6, we're launching there. Would appreciate a follow or an upvote if this kind of data is useful to you. Launching the full dataset as a product that day.
The short version of everything above: most niches are either too crowded or too empty. The ones worth looking at are where a small number of products are getting real traction and there's still obvious room. The data helps you find those faster than gut instinct alone.
What niches are you currently looking at? Curious what other builders are seeing from the ground level.
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