Someone already built my idea: what 3,000+ earning startups say about crowded markets

The short answer

This page answers one question with data: does finding an existing product mean your idea is dead? It uses TrustMRR verified revenue, the Stripe Index of companies already taking payments, and the complaint data behind our software review research, part of a 1M+ complaint corpus.

What the top results say, and what they skip

Search this phrase and the first page is a forum thread, a Q&A answer, a few short blogs, a 2024 developer-forum discussion and a SaaS publisher’s Q&A. The advice repeats: someone already doing it means demand exists, do it better, find a niche, execution matters. It is mostly right. It is also unmeasured. None of those pages says how many competitors is normal, whether crowded markets pay less, or what a better version should fix.

The comments show how founders read it. One reply in a ranking r/Entrepreneur thread sums up the sceptic-proof version: you do not need an original idea, you copy something that exists and either market it to a new audience or make it easier for a niche audience. Another puts the consumer view plainly: the more options exist, the more choice a person has. Both are opinions. We tested them.

“You don’t need an original idea. Just copy and market it to a new audience or make the UX easier for a niche audience.”comment in an r/Entrepreneur thread on ideas that already exist

We do not cover how to estimate what a specific competitor earns (see how to estimate a SaaS competitor’s revenue), how a funded entrant changes your odds (see when a funded competitor enters your market), or which categories have the most companies (see SaaS market saturation 2026). This page asks the question those three leave open: given that someone is already there, is the market worse for you, and where is the opening?

No. We took every startup in TrustMRR with a monthly revenue figure above $0 and a category, and kept categories with at least 30 earning startups: 20 categories, 3,397 earning startups. We ranked categories by how many startups earn and compared that rank with median monthly revenue. The rank correlation is 0.02. For the share earning $1,000 a month it is −0.11. Neither is meaningfully different from zero.

Grouping the categories into three size tiers shows the same thing in plain numbers.

The busiest tier has the highest median ($158 against $104 and $117), but the gap is small and the middle tier is lower than the thin one, so there is no slope. The share clearing $1,000 a month sits in a 2-point band across all three. If crowding punished newcomers, that share would fall as the tiers fill up. It does not.

The medians are low in absolute terms, and that is the honest context. A typical earning startup in this dataset makes roughly $100 to $160 a month, because TrustMRR lists many small and young products. Crowding is not what holds those numbers down. We cover the shape of that distribution in TrustMRR SaaS revenue benchmarks 2026.

We also matched 17 TrustMRR categories to the closest Stripe Index category and compared payment-taking company counts to median revenue. The rank correlation was −0.14, with a micro-SaaS count correlation of −0.06. Seventeen categories is too few to headline, so treat it as consistent with the main result, not as separate proof.

Being second costs time. It does not cost permission. To test that, we looked only at startups founded in 2024 or 2025, the people who arrived after the category already existed, and asked how many have reached $1,000 a month.

Between 24.0% and 25.4% of recent launches in every tier have crossed $1,000 a month. A launch into a category with 200+ earning peers does as well as a launch into one with 30 to 89. The newest products make less than the established ones, which is time, not crowd size: within each category, the earliest-founded quarter of earning startups has a median of $436 and 37.8% above $1,000 (n = 2,883 earning startups across the 20 categories), while the latest-founded quarter has a median of $57 and 11.2% above $1,000. Even so, 31.8% of all $1,000+ earners were founded in the later half of their category’s timeline.

That age effect is real and we do not hide it. Newcomers have had less time, and the earliest products had the market to themselves for a while. Plan on revenue taking longer than the leader’s did, not on being shut out.

If category size does not explain revenue, something else does. The answer is the gap between the best and the median inside each tier, which is enormous everywhere. When someone says “execution matters”, this is the number behind it.

In every tier, 42% to 49% of earning startups make under $100 a month, while the 90th percentile starts at $3,463 to $5,028 and the 99th percentile at $32,912 to $69,721. The top tenth of startups hold 84% to 95% of the revenue. A crowded category does not shrink that top tenth, and a thin one does not guarantee you a place in it.

So the competitor you found is not the main risk. Landing in the bottom half is, and that is decided by choices a founder can see in the data: a specific buyer, a complaint that repeats, a price that works. This is also why we ask you to pick a wedge before comparing logos. The wedge is what moves you between those percentiles; the logo count is not.

One caution: percentiles at the top are driven by a handful of startups, and the 99th percentile in a 562-startup tier rests on about six companies. Read those two columns as shape, not as a forecast for your product.

A competitor is not an anomaly. It is what a paying market looks like. Across all 31 TrustMRR categories (8,000+ startups, 3,700+ of them earning), the pattern is that markets with buyers have several sellers.

In 26 of 31 categories, five or more startups earn $1,000 a month or more. Only two categories have none, and both are tiny. So “someone is already doing this” is true of almost every idea that can make money. It is a weak signal in either direction. Our micro-SaaS competition research and low-competition SaaS ideas look at the same question from the other side, where small products survive among bigger ones.

The useful reading is the opposite of the worry. When you see several earning products, you can check how they differ, and what their customers say about them. When you see none, you have no way to test whether anyone pays.

If crowding does not decide your odds, what does? The product you are replacing, and how unhappy its buyers are. We bucketed the free-text complaint labels from 13,000+ software products (200,000+ mentions) into eight themes. Two measures matter: the share of all mentions, and the share of products with at least one complaint in the theme.

Three readings are useful. First, usability complaints touch more than half of all products, which makes “a nicer interface” the most common and weakest wedge. Everybody has it, so it differentiates nobody. Second, missing features and flexibility are mentioned for 44% of products. That is the most buildable wedge: one specific thing a segment needs and the leader will not add. Third, support (27% of products), pricing (16%) and integrations (17%) are wedges that are not about code at all. You can win on response time, a plain price page or a connector the incumbent has no reason to build.

“There’s a fee for almost every additional feature that could benefit the business.”review of a business software product, owner

“They want you to pay astronomical support fees. Do not use.”review of a business software product

“The report system is a bit tedious to work with; the detailed form can become cumbersome to assess and analyze.”review of a business software product, researcher

Each of those is a product decision that a smaller company can make and a larger one often will not, because its pricing and support models are built around the average customer. Look for complaints that repeat across many reviewers, not one angry review. A theme repeated by many customers of the same product is a stronger signal than any single quote. The same logic underlies the state of SaaS pain points research.

Software review sites skew toward business tools. To check the pattern against consumer products, we ran the same kind of cut on 90,000+ App Store and Google Play reviews rated 2 stars or lower. Keyword classes overlap, so shares do not add to 100%.

Two themes match the business-software table: support and integrations both show up again. The difference is price. In consumer apps, price, subscriptions and paywalls are the single largest complaint at 19.5% of low-rated reviews, against 5.6% of mentions for business software. If your competitor is a consumer app, the cheapest wedge to test is a clearer price: a one-time option, a free part that works, or no ads. If it is a business tool, test missing features and support first. Our app revenue research goes deeper on the paywall complaint.

To make the steps concrete, take the busiest business-style category in TrustMRR, “Marketing”. Suppose your idea is a tool for small businesses that reports on their ad and email results, and you have just found three products that do something similar. Here is what the check shows, with no company names.

1. Do they earn? 213 Marketing startups report revenue above $0. The median is $276 a month, 61 of them (28.6%) earn $1,000+, and 22 (10.3%) earn $10,000+. Buyers pay in this category.
2. How crowded and how skewed? It is in our 200+ tier. 37.6% earn under $100 and the 90th percentile is $10,495. The same shape as everywhere: a few do well, many stall.
3. Can latecomers reach $1,000? 172 of the 213 were founded in 2024 or later, and 37 of those (21.5%) already earn $1,000+. Arriving late is the norm here, not an exception.
4. What do buyers dislike? The complaint table points to reporting (19.8% of products), integrations (17.4%) and pricing (16.4%) as the wedge families that fit a reporting tool. You would then read the actual reviews for those three products, not the averages.
5. Pick one wedge. Not “better reporting”. Something like: one-page weekly results for local service businesses, built from the tools they already use, at a flat price.
6. Test. Show that sentence and price to ten people who wrote detailed reporting complaints. Count who agrees to a paid pilot.

The result is a decision, not a feeling. The category pays, newcomers get to $1,000 at about the same rate as everyone else, and the open question is narrow enough to test in two weeks. If the pilot fails, the category was not the problem; the wedge was. That is a cheaper lesson than the one you learn after a three-month build.

Found a competitor: what to do, step by step

This is the check we would run in BigIdeasDB before writing any code. It takes an afternoon, not a month.

1. Describe them in one sentence each: the job and the buyer. If you cannot say who the competitor serves, you do not yet know where the room is. Write down the buyer segment and the main price.
2. Check that they earn. Look up the product and its category peers in TrustMRR. Verified revenue means the number comes from the payment provider. If peers earn $1,000 a month or more, buyers pay. If nobody does, find out why before building. Section “Do crowded markets pay less” shows what typical looks like.
3. Read their customers’ complaints. Open the software review complaints for the product and its category. Group them using the table above. You are looking for the same complaint repeated by many customers.
4. Check density. In the Stripe Index, count how many companies take payments in the category and how many are micro-SaaS. Density tells you how many alternatives your buyer already has. Remember it does not predict revenue; use it to judge how specific your wedge needs to be.
5. Pick one wedge, in one sentence. A segment, a missing feature, a price model or a service level. “Better and cheaper” is not a wedge. “The same tool for dental practices with a flat price and a human who replies in an hour” is.
6. Test the wedge before you build. Put the sentence and a price in front of the unhappy customers you found, in the places they already complain. Count payers and deposits, not compliments. Our idea validation framework lays out the stages.
7. Decide with a threshold. Go if the complaint repeats across many customers, the competitor earns, and you can ship the wedge in weeks. Pause if only one of those is true.

For a structured way to compare several competitors on one task, use competitor analysis. To see all of this for your own idea in one place, run it through BigIdeasDB discover: it checks your niche against 1M+ complaints, payment-taking companies and verified revenue.

Reaching the unhappy customers you found

A wedge only counts if you can reach the people who feel it. Three places work, in the order we would try them.

• The complaints themselves. Review sites and forum threads show the exact words buyers use, the role they hold and the size of company they run. Write your headline in those words, not in yours.
• Searches that happen at the moment of annoyance. People who want to leave a product search for alternatives, cancellation steps and export instructions. A page that answers one of those honestly, with your wedge as the reason to switch, meets them where they are.
• Small conversations. Ten direct messages to people who wrote a detailed complaint will teach you more than a survey. Ask what they do today, what it costs them, and what they would pay to fix it. Offer a pilot, not a pitch.

Keep the unit of measurement narrow: of the people you reach with the wedge sentence, how many pay or put down a deposit. If the number is zero after thirty real conversations, the gap is a complaint nobody will pay to solve, and you have learned that for the price of a few weeks instead of a launch.

What about someone stealing your idea?

Founders often mix two worries: a competitor already exists, and someone took the idea. The second is rare and rarely the cause of failure. Ideas are not protected, an idea alone has little value, and the products in the data above exist side by side because buyers reward the version that fits them. Sharing your wedge with unhappy customers is how you validate it. Keeping it secret mostly removes your only source of evidence.

When you should walk away

Competition is not a reason to stop. These are:

• Your only difference is that you are newer. Newness is not a reason for a buyer to switch.
• The incumbent’s customers are happy. If complaints are thin and scattered, there is no gap to fill.
• Nobody in the category earns. Zero revenue among peers is a market signal, not an opening. Two of 31 categories in our data have no startup at $1,000 a month, and both are tiny.
• The wedge needs the incumbent’s distribution. If your advantage only works inside their product, they can copy it faster than you can sell it.
• You cannot reach their unhappy customers. A gap you cannot find buyers for is a gap on paper.

What this cannot tell you

• TrustMRR is a self-selected set. It lists startups whose founders connected a payment provider. It is not the whole market, and it over-represents small, young, indie products.
• Categories are TrustMRR’s labels. Some are broad, so “crowded” means many earning products in a label, not many direct rivals for your exact idea.
• Correlation across 20 categories is not causation. We show crowding does not predict lower revenue in this sample. We cannot show it never hurts any single launch.
• Age is confounded. Early entrants had more time. We report the gap and do not adjust for it.
• Survivorship. Startups that failed and never listed do not appear.
• Complaint themes are keyword buckets. Free-text labels were grouped by regex. Shares are directional, and 20% of mentions fall outside the eight themes.
• No per-category complaint join. We do not link a specific TrustMRR category to its complaint profile, so the wedge table describes software in general.

Methodology and sources

Revenue figures use TrustMRR monthly recurring revenue in US dollars, kept where above $0. Categories with at least 30 earning startups were used for correlations and tiers. Complaint data comes from a software-review dataset grouped by keyword. Everything was read with read-only SQL on October 16, 2026. Medians show n; cuts under 30 are not shown.

Frequently asked questions