Most Startup Advice Ignores the Numbers
Everyone has opinions about what to build. Few people have data.
We analyzed verified revenue data from thousands of startups across 33 categories to answer the questions that actually matter: Which niches make the most money? Which are growing fastest? Where is the gap between hype and reality?
This is not a survey. It is not self-reported. The numbers come from verified revenue sources -- actual MRR, total revenue, and 30-day growth figures from startups that are live and generating income right now.
Here is what we found.
The Highest-Earning Categories
Not all startup categories are equal. The spread between the top and bottom is enormous.
Fintech Leads in Average MRR
The average monthly recurring revenue for startups in the [fintech] idea category has always been the highest among all the categories we track. The typical fintech startup generates much more money than the typical SaaS or productivity app on a monthly basis. It makes perfect sense since fintech products deal with real money transactions, which creates a greater willingness to pay.
But fintech has the highest barrier to entry too. Regulations, banking integration, and security needs make it tougher to get off the ground fast. Fintech is easier for single founders and vibe coders to work on when your product niche is focused and narrow -- expense management for freelancers, financing invoices for agencies, subscription management for SaaS.
AI Tools: High Growth, Moderate Median Revenue
The AI category is the most vibrant in terms of performance. This is the fastest-growing category on a 30-day period basis, with new companies often generating between $5k and $10k MRR in their first three months. However, median revenues for this category are smaller compared to those in the fintech or traditional SaaS sectors because of its product congestion.
The signal here is clear: AI is where momentum lives, but differentiation matters more than ever. Generic "AI assistant" tools cluster at the bottom of the revenue distribution. The top earners are AI tools that solve a specific workflow problem for a specific audience.
E-commerce Tools: Steady and Underrated
The e-commerce sub-sector isn’t getting enough recognition. Everyone is talking about AI, but it’s actually the e-commerce tool companies that exhibit the best revenue behavior in the entire database. Monthly recurring revenues can be decent, there is little to no churn, and growth continues because of the never-ending demand for tools from Shopify/WooCommerce stores.
Product recommendation engines, inventory management tools, and conversion optimization widgets all show healthy revenue distributions. This is a category where a focused product can reach $10K+ MRR without needing to be revolutionary -- just reliable and well-integrated.
Growth Rate Analysis
Raw MRR only tells part of the story. Growth rates reveal where the market is heading.
Fastest-Growing Categories (30-Day Growth)
- AI-powered developer tools -- The explosion of vibe coding has created demand for tools that help developers (and non-developers) build faster. Startups in this sub-niche are showing 15-25% month-over-month growth.
- AI content and marketing tools -- Despite saturation concerns, the top performers in this space continue growing at 10-20% monthly. The key differentiator is distribution, not features.
- Vertical SaaS for specific industries -- Dental practice management, gym scheduling, restaurant analytics. These unglamorous niches are growing steadily at 8-15% monthly because they face almost no competition from horizontal players.
Slowest-Growing Categories
Some categories have matured to the point where new entrants struggle:
- Generic project management -- Dominated by established players. New startups in this space show the lowest growth rates in our dataset.
- Basic website builders -- The market has consolidated. Unless you have a sharp niche angle, growth is flat.
- General social media scheduling -- Buffer, Hootsuite, and dozens of alternatives have saturated this space. Only AI-native schedulers show meaningful growth.
The Revenue Distribution Problem
Averages lie. Here is a pattern that appears across every single category in our data:
The top 10% of startups in each category earn more than the bottom 60% combined.
This is not unique to startups, but the skew is more extreme than most founders expect. It means:
- "Average MRR for AI tools is $X" is misleading if you are likely to land in the bottom half.
- Category selection matters less than execution within a category.
- The difference between $2K MRR and $20K MRR in the same niche usually comes down to positioning and distribution, not product quality.
If you are researching a category, do not just look at averages. Look at the full distribution. What does the median look like? What separates the top performers? These are the questions that Impectly's research tools are designed to answer.
What the Data Says About Timing
We tracked when startups in our database were founded relative to their current revenue. The findings challenge common assumptions:
Early Movers Do Not Always Win
In AI-adjacent categories, startups founded in 2025 are outperforming many that launched in 2023-2024. Why? Because the earlier products were built on less capable models and have accumulated technical debt. Newer entrants built on current LLMs launch with better products from day one.
This is good news for anyone building now. In fast-moving categories, being "late" is often an advantage because you ship with better tools and learn from predecessors' public mistakes.
Slow-Burn Categories Reward Patience
When looking at e-commerce software, productivity, and industry-specific SaaS, revenue is strongly correlated with age. Companies that have been in operation for more than 18 months outpace those that are younger. The older companies benefit from compounded growth through SEO, referrals, and integration.
If you choose one of these categories, set your expectations accordingly. Month one will not look like month twelve.
Practical Takeaways for Founders
If You Want Fast Revenue
Target AI-adjacent categories with clear workflow improvements. The data shows these have the fastest path to first revenue, though the long-term ceiling is uncertain.
Use the AI chat to research specific sub-niches: ask what tools in a given category are growing fastest, or what the revenue range looks like for a specific type of product.
If You Want Durable Revenue
Target vertical SaaS or e-commerce tools. The growth is slower, but the revenue is stickier. Customers in these niches switch tools far less frequently than in consumer or horizontal SaaS.
If You Want the Biggest Upside
Fintech. But only if you are prepared for the compliance and trust requirements. A focused fintech tool for a specific audience -- freelancers, small agencies, content creators -- can reach $50K+ MRR, but the path is longer and more complex.
How to Use This Data
This report is a snapshot. Markets move, new categories emerge, and individual startups defy category averages every day.
The most useful thing you can do with this data is not pick the "best" category and run with it. It is to:
- Narrow your options to 2-3 categories that match your skills and interests.
- Research the specifics -- what are the top-performing startups in those categories doing? What is their pricing? What is their growth trajectory?
- Find the gaps -- where is demand growing faster than supply?
All of this data is available to explore across our full category index. If you want to go deeper on a specific niche, the AI research assistant can pull verified numbers and surface patterns that would take hours to find manually.
The founders who build with data make better bets. Not every bet will pay off, but the odds improve dramatically when you know what the market actually looks like before you write the first line of code.