Every guide tells you how to write an ICP. We checked 8,000+ revenue-verified startups to see which customer choice actually earns money, then built a method for finding yours before you have a single customer.
An ideal customer profile (ICP) is the short list of traits shared by the customers who pay you most and leave least. In 8,000+ revenue-verified startups, B2B products earn a median $198 MRR against $99 for B2C, and startups that sell to both have the lowest share above $10,000 MRR (3.3%). Who you pick decides how much you can charge.
Every page that ranks for this topic hands you the same framework: firmographics, pain points, a persona, a checklist. None of them shows which choice correlates with revenue. We have the revenue. This guide uses the TrustMRR revenue dataset, 800+ acquisition listings, 17,000+ funded companies, 30,000+ Stripe Index companies, 273,000+ Capterra reviews, 152,000+ G2 reviews, 5,300+ Upwork jobs and 430+ scored ideas from the Agent Index.
Then it answers the question the frameworks skip. How do you pick an ICP before you have customers? You borrow someone else’s. That part is a method you can run this week.
An ICP is a filter, not a portrait. It tells you who to talk to, who to ignore and what to charge. A useful one has three to six attributes you can check before a sales call: segment, size band, the software they already run, the trigger that makes them buy now, who signs, and a price.
Lenny Rachitsky interviewed founders of well-known B2B companies about their first ICP and reported that most founders initially got their ICP wrong, and that everyone landed on at least three attributes. One founder described running the ICP exercise 17 times in the early days. Expect versions.
“It's not to find out who is actually the most ideal in terms of who is going to pay the most, it's to have a target to aim at.” – r/marketing
That comment is the right frame for a startup. Your first ICP is a target to aim at. The revenue data below tells you which targets tend to pay off.
The target market is everyone who could buy. The ICP is the subset you pick. The persona is the person inside that subset who signs or uses the product. Founders mix them up constantly, which is how a startup ends up targeting “small businesses” and writing copy for nobody.
| Term | Describes | Example | Used for |
|---|---|---|---|
| Target market | Everyone who could buy | US dental practices | Market sizing |
| Ideal customer profile | The account or segment you pick | Dental groups with 2 to 15 locations on mixed practice software | Who to sell to, what to charge |
| Buyer persona | The person inside the ICP | The group’s office manager | Messaging, onboarding, interview questions |
“If you claim your Total Addressable Market is “The Global Internet,” you don't know who your customer is. Niche down.” – r/Entrepreneur
“Because you built the thing for someone, who are they?” – r/marketing
Because the wrong customer is the most common way a startup fails slowly. CB Insights’ post-mortem analysis lists poor product-market fit as a cause in 43% of failures, and notes that running out of capital (70%) is usually the final cause of death rather than the root problem. Picking a customer who cannot or will not pay is a product-market fit problem wearing a sales costume.
“I worked in marketing for a startup founded in 2017 and by 2024, their total revenue since founding was $6,000.” – r/marketing
The same thread describes the founder insisting on premium customers the product could not reach. That is the failure mode in one line: an ICP chosen for how it sounds rather than for who pays. Our startup failure analysis and failure statistics show the same pattern at scale.
“scrambling to build features to serve multiple niche clients and end up serving nobody particularly well” – r/marketing
We grouped 8,000+ startups with Stripe-verified revenue by their labeled audience (B2B, B2C or both) and compared what the paying ones earn. 5,400+ of them carry an audience label. A startup counts as paying when its monthly recurring revenue is above zero. Revenue per customer uses the 300+ paying startups that also report a customer count.
We then checked each finding against independent corpora that were built for other purposes: acquisition asking prices, funded companies, the Stripe Index, Capterra, G2, Upwork, App Store analyses and the Agent Index. Where they agree we say so. Where they disagree we say that too. Full limits are in the methodology table.
Yes, by about double at the median. Among paying startups, B2B products earn a median $198 MRR against $99 for B2C. 26.6% of paying B2B startups clear $1,000 MRR, against 16.8% of B2C. The gap widens at the top: 7.7% of paying B2B startups clear $10,000 MRR, more than twice the B2C rate of 3.5%.
| Audience | Startups | Share paying | Median MRR (paying) | Paying at $1k+ | Paying at $10k+ | 90th percentile MRR |
|---|---|---|---|---|---|---|
| B2B | 2,000+ | 52.3% | $198 | 26.6% | 7.7% | $6,801 |
| B2C | 2,900+ | 58.4% | $99 | 16.8% | 3.5% | $2,418 |
| Both | 400+ | 49.6% | $168.50 | 23.8% | 3.3% | $3,329 |
Founders say the same thing in their own words. The difference is not effort. It is arithmetic.
“In B2B, thirty clients at $100/month and you're at $3,000. In B2C, you need thousands of users for the same result.” – r/SaaS
“Getting a consumer to pay $9.99 a month was like pulling teeth.” – r/SaaS
“The owner paid $500 month without blinking. Why? Because it saved him $2,000 month in lost stock.” – r/SaaS
For the full revenue distribution by category, see our TrustMRR revenue benchmarks and the state of indie SaaS revenue.
Consumers, narrowly. 58.4% of B2C startups in the dataset earn something, against 52.3% of B2B and 49.6% of mixed-audience startups. A consumer will put $5 on a card faster than a business will approve a vendor.
That is the trap in B2C. It is easy to get the first dollar and hard to get the ten-thousandth. The quickest first sale is not the same as the best ICP.
“B2C might convert in minutes. B2B can take 3 to 6 months.” – r/SaaS
“Consumers buy features. Businesses buy solutions to problems that cost them money.” – r/SaaS
Disproportionately from B2B. The 90th percentile paying B2B startup earns $6,801 MRR. The 90th percentile B2C startup earns $2,418. A founder who picks a business ICP is not guaranteed more money, but the ceiling in the data is almost three times higher.
This matches what we see in how fast SaaS startups grow and in solo developer revenue examples: the outliers are usually selling a workflow to a business, not an app to a person.
For most startups, yes. Startups labeled as selling to both have the lowest share at $10,000+ MRR (3.3%), below B2C (3.5%) and less than half of B2B (7.7%). They also have the lowest median revenue per customer at $4.82 and the largest median customer count at 101.
That combination is the signature of a broad ICP. Lots of people use it. Nobody pays much. Every feature request pulls in a different direction.
| Audience | Median revenue per customer / month | Median customers | Read |
|---|---|---|---|
| B2B | $13.79 | 45.5 | Fewer customers, each worth more |
| B2C | $5.59 | 42 | Similar count, less than half the value |
| Both | $4.82 | 101 | Most customers, least revenue each |
“A large number of potential users does not automatically create a good business.” – r/SaaS
“Pick a target, put all your energy into aiming at them, write down what you learn, and make adjustments.” – r/marketing
In AI products, the mixed audience holds up. Among paying AI startups, 28.7% of those labeled “both” clear $1,000 MRR, ahead of B2B at 26.8% and B2C at 21.7%. Their median MRR is $210, close to B2B at $238.50 and well above B2C at $139.50.
The likely reason is that many AI tools are bought by a professional with a personal card: a freelancer, a consultant, a prosumer. The label says both, but the buyer is one person doing work. That is still a narrow ICP. It just crosses the B2B and B2C line. Our AI SaaS revenue reality check goes deeper on this category.
Yes, in every category where both audiences have 25+ paying startups. This matters because it rules out the easy objection that B2B only wins because B2B categories are richer. Hold the category constant and the business ICP still earns more.
| Category | B2B median MRR | B2C median MRR | B2B paying at $1k+ | B2C paying at $1k+ |
|---|---|---|---|---|
| Marketing | $454.50 (n=138) | $72 (n=35) | 31.9% | 5.7% |
| Content creation | $297.50 (n=38) | $84 (n=94) | 28.9% | 21.3% |
| Artificial intelligence | $238.50 (n=310) | $139.50 (n=414) | 26.8% | 21.7% |
| Fintech | $161.50 (n=26) | $66.50 (n=56) | 15.4% | 10.7% |
| SaaS | $129 (n=155) | $100 (n=109) | 26.5% | 15.6% |
| Productivity | $102 (n=42) | $33 (n=140) | 11.9% | 3.6% |
| Developer tools | $74 (n=113) | $39 (n=26) | 20.4% | 7.7% |
The B2B-only categories are worth noting too. Paying B2B sales tools post a median $788 MRR with 42.9% above $1,000 (n=28), and B2B e-commerce tools post $260 with 32.0% above $1,000 (n=25). Compare them with our revenue benchmarks by category and most profitable SaaS niches.
Because a business counts marketing spend as an investment and a consumer counts it as a cost. Paying B2B marketing startups earn a median $454.50 MRR, 6.3 times the $72 B2C median. Only 5.7% of paying consumer marketing tools reach $1,000 MRR.
A marketing tool sold to a business is measured against leads and revenue. Sold to an individual creator, it is measured against a streaming subscription.
“We lost 10k to angi leads that landed us 1 job in 8 months” – r/smallbusiness
That small business owner lost real money on leads and is still shopping for a fix. That is what a buyer with budget sounds like. Our sales software limitations and email marketing software limitations pieces map the complaints inside this category.
It has the most builders and the least revenue. Consumer productivity has 140 paying startups in the dataset, the second largest B2C group, at a median $33 MRR. Only 3.6% reach $1,000. The same category sold to businesses earns $102 with 11.9% above $1,000.
Habit trackers, to-do lists and note apps are easy to build and easy to love. They are also the category where the buyer already has a free default. See oversaturated side hustles and SaaS market saturation for the supply side of that problem.
“Users were highly price-sensitive and often expected substantial functionality for free or for a very low price.” – r/SaaS
More than you think. Price per customer predicts success better than audience does. Across the 300+ paying startups that report customers, those earning under $10 per customer reach $1,000 MRR 22.4% of the time. At $10 to $50 it is 46.4%. At $50 to $200 it is 58.3%. At $200+ it is 69.2%.
| Revenue per customer / month | Startups (n) | Median MRR | Reach $1,000 MRR | Median customers |
|---|---|---|---|---|
| Under $10 | 174 | $169.50 | 22.4% | 72.5 |
| $10 to $50 | 69 | $746 | 46.4% | 41 |
| $50 to $200 | 36 | $2,642.50 | 58.3% | 32 |
| $200+ | 26 | $2,617 | 69.2% | 10 |
Put simply: pick a customer who can pay $50 or more a month and your odds of reaching $1,000 MRR are 2.6 to 3.1 times higher than with one who pays under $10. Our guides on what micro SaaS actually charges, SaaS pricing strategies and how to price a micro SaaS turn this into a price.
““10K users” means nothing. “10K users, 23% MoM growth, $47 average revenue per user” means something.” – r/Entrepreneur
Yes, if the ICP pays $200+. The startups in the $200+ band have a median of just 10 customers and a median $2,617 MRR. That is a business you can build with a spreadsheet and a phone, not a launch strategy.
It also changes how you find customers. Ten buyers can come from direct outreach, a single community or one referral chain. Read how to get your first customer and how to get your first 100 users with that number in mind.
“Go ask your dentist what software they hate.” – r/SaaS
You need a crowd, and crowds are expensive to find. Startups under $10 per customer have a median of 72.5 customers and a median $169.50 MRR. More than three in four never reach $1,000.
Cheap customers are not always B2C. B2B startups under $10 per customer reach $1,000 MRR 26.1% of the time, barely better than the pooled rate. The audience label matters less than the price the audience will accept.
“Features are good but pricing too much.” – App Store review
Directionally, yes, and in the same order as revenue. Across 800+ acquisition listings, the ones that describe a B2B audience ask a median 3.9x profit multiple (n=104). B2C listings ask 3.4x (n=49). Listings that describe both ask 3.0x (n=19). Listings that do not say ask 3.5x.
| Audience in listing | Median profit multiple | Median asking price | Median TTM revenue |
|---|---|---|---|
| B2B (n=104) | 3.9x | $365,000 | $188,000 |
| B2C (n=49) | 3.4x | $235,300 | $134,000 |
| Both (n=19) | 3.0x | $300,000 | $185,500 |
| Not stated (600+) | 3.5x | $200,000 | $123,000 |
One dataset pushes the other way. In TrustMRR’s own listings, mixed-audience startups carry the highest median revenue multiple (4.49x, n=72) against B2B at 3.22x and B2C at 2.94x. The two sources measure different things: acquisition listings price profit, TrustMRR prices revenue. We report both rather than pick the one that fits. Background in profit multiples by category and SaaS valuation multiples.
At businesses, by more than two to one. In 17,000+ funded companies, 3,400+ carry a B2B sector tag against 1,300+ tagged consumer. Fewer than 100 carry both.
That does not make B2B right for an indie founder. It means funded companies crowd the business segments, which is a reason to pick a narrower slice of them. Browse the funded companies database or read what VCs are funding before you choose.
Consumers, mostly. In the Stripe Index of 30,000+ companies taking real payments, 51.2% target consumers, 21.5% small businesses, 10.9% mid-market, 8.2% prosumers, 6.5% enterprise and 1.6% developers.
Micro SaaS density runs the opposite way. 20.9% of developer-facing companies and 16.8% of prosumer-facing companies are micro SaaS, against 8.0% for small business, 5.7% for consumer, 1.8% for mid-market and 1.2% for enterprise. Small teams crowd the smallest buyers. Our study of who micro SaaS actually sells to covers this in full.
“Market size without workable unit economics is mostly a vanity metric.” – r/SaaS
Borrow someone else’s customers. Every buyer you want already pays for something. Their reviews, their freelance job posts and their community threads tell you who is unhappy, what it costs them and what they already pay. You can read all of it before you write a line of code.
The method, in six steps:
Most guides say you need paying customers first. The r/marketing thread that ranks for this topic says the same thing.
“you need a good amount of paying customers before you can decide who the ideal customer for your business is.” – r/marketing
That is true for the final ICP. It is not true for the first hypothesis. The next five sections show how to build one from data. Pair them with our idea validation guide and the 8-stage validation framework.
Read reviews of the software your buyer already pays for. A 1 to 3 star review from a paying customer is the most honest ICP research you can get. The reviewer tells you their role, their industry, what they pay for and exactly why it fails them.
Across 273,000+ Capterra reviews, 8.5% are rated 3 stars or lower. That baseline is your comparison point. Any role or industry well above it is a group paying for software it does not like.
“You get what you pay for. None of the advanced features actually work. Support takes ages to get back to you.” – Capterra review, business owner
“I contacted them 7 times and nothing worked to get a real person vs an automated response so I gave up.” – Capterra review, business owner
Our guides to mining Capterra reviews, turning G2 reviews into ideas and who complains about what in software reviews walk through the mechanics. The Capterra analysis help page shows how to filter by industry.
Healthcare and legal practices, by a wide margin. Medical practice reviewers rate 15.0% of reviews 3 stars or lower, almost double the 8.5% corpus rate. Mental health care sits at 14.6% and law practice at 10.9%.
| Reviewer industry | Reviews | Rated 3 stars or lower | Average rating |
|---|---|---|---|
| Medical practice | 3,600+ | 15.0% | 4.34 |
| Mental health care | 1,800+ | 14.6% | 4.37 |
| Law practice | 2,100+ | 10.9% | 4.49 |
| Retail | 7,900+ | 10.5% | 4.49 |
| Transportation and trucking | 3,300+ | 10.4% | 4.46 |
| Automotive | 5,400+ | 10.3% | 4.50 |
| Construction | 9,500+ | 10.1% | 4.46 |
| All reviews | 273,000+ | 8.5% | 4.53 |
Unhappy paying buyers are the easiest ICP to switch. The Agent Index independently flags dental, veterinary, physical therapy and optometry practices as wide open for AI tools (18 of 54 verticals are rated wide open). Read niche SaaS ideas in real estate and healthcare and the most underserved software markets.
They are the least satisfied role and the one that signs. Owners, founders and CEOs write 15.9% of Capterra reviews (43,000+). 11.1% of their reviews are 3 stars or lower, the highest rate of any role we can identify. Finance reviewers follow at 9.3%, office and admin staff at 9.0%. Technical reviewers are the most forgiving at 6.6%.
| Reviewer role | Share of reviews | Rated 3 stars or lower |
|---|---|---|
| Owner, founder or CEO | 15.9% | 11.1% |
| Finance | 1.9% | 9.3% |
| Office, admin or bookkeeper | 4.0% | 9.0% |
| Director or VP | 9.6% | 8.1% |
| Sales or marketing | 5.9% | 7.6% |
| Other manager | 14.1% | 7.5% |
| Technical | 5.9% | 6.6% |
An owner who dislikes their tools and holds the budget is a short sales cycle. Compare that with the enterprise path.
“I've tried at least 9 apps since the BOY for cold outbound. None of it works.” – r/startups
See how small business owners use AI and small business software pain points for the owner’s side of the story.
Price. In 152,000+ G2 reviews, reviewers who mention being a small business, small team or startup bring up price or cost in 39.7% of reviews. Reviewers who mention an enterprise or large organization bring it up in 24.2%. Reviews that mention neither sit at 13.2%.
Large companies complain more about integration (23.4% against 19.0%). Both groups mention support at the same rate, about a third of the time. So a small-business ICP needs a price that fits, and an enterprise ICP needs to plug into what they already run.
“the fees can have a noticeable impact on profit margins, especially for small businesses and freelancers who are trying to keep operating costs low” – G2 review
“an individual or small business might not be comfortable using this software due to its high implementation costs” – G2 review
Our CRM too complicated for small business study shows this pattern inside one category.
A freelance job post is a buyer with a budget and a deadline. In 5,300+ Upwork job posts, 18.2% mention integration, APIs or syncing, 12.6% mention spreadsheets, Excel or Google Sheets, 8.8% mention dashboards or reports and 8.5% ask for automation.
Every one of those posts is a small business describing a workflow in its own words and attaching money to it. If the same job shows up again and again, the people posting it are an ICP.
“Find a business that is using Excel to manage a complex process.” – r/SaaS
The method is in validating SaaS demand with Upwork jobs, the state of freelance demand and industries still running on spreadsheets. The Upwork analysis tool and its help guide let you run it by category.
Go where the buyer talks to peers and copy their words. r/smallbusiness is the largest source in our Reddit pain-point corpus, and the posts read like ICP descriptions written by the customer.
“it's spread across WhatsApp, a couple spreadsheets, and whatever the staff happen to remember” – r/smallbusiness
“Someone leaves and half of it walks out with them” – r/smallbusiness
“I missed a callback yesterday that probably cost me a $2k job.” – r/smallbusiness
“I never truly know if the month has gone well or not until my monthly report from my accountant.” – r/smallbusiness
“I need something basic so I stop spending my Tuesday mornings fixing double-bookings” – r/smallbusiness
Each quote names a tool they use today, a cost and a trigger. That is three ICP attributes for free. The founder with $1M ARR in r/SaaS made the same point as an instruction.
“Find other people who are talking about that problem. A message board. A subreddit.” – r/SaaS
“If you cannot find a conversation to join, the product doesn't need to be made.” – r/SaaS
Start with finding business ideas on Reddit, Reddit market research and using Reddit for validation, or browse the pain points database.
Sharp enough to name a size band and the software your customer runs. The Agent Index contains 430+ AI product ideas, each with a written ICP, scored by an adversarial judge. Only 6 score 60 or higher. 5 of those 6 name both a numeric size range and the customer’s existing software stack. Across all 430+, only 8.6% do both.
The top-scoring profiles read like this:
Each one tells you exactly who to call and what they already pay for. Compare that with “small businesses that want to save time.” The judge scores are internal and the sample of strong ideas is small, so read this as a pattern, not a law. More in AI agent whitespace by vertical.
“Speak directly to a problem that your app solves for a very specific person.” – r/SaaS
Then your ICP must include what that person already pays for, because they are tired of paying. In 7,700+ App Store and Google Play review analyses, 44.5% flag subscription complaints in the monetization feedback and 19.1% flag price directly.
“I canceled this after 28 days, but they keep charging me $68 every two weeks.” – App Store review
A consumer ICP that works usually describes a situation with money attached: a wedding, a move, a diagnosis, a job search, a trip. Read B2C SaaS ideas, mobile app pain points and subscription vs one-time purchase, and use the App Store database to see what your segment already complains about.
Sort customers by revenue and retention, then describe the top fifth. Look for the traits they share that the bottom fifth does not. Those traits are your ICP.
Baremetrics recommends that early-stage founders interview 20 to 30 users directly, including churned customers and unconverted trials. 1752vc’s ICP framework for startups moves from market analysis to segmentation, profile, validation and go-to-market alignment. Both are sound. Add one step they skip: record what each customer pays you, because the price ladder above says it predicts more than any firmographic.
“New-account volume fell. At the same time, active subscriptions, recurring revenue, and net volume increased in our latest comparison.” – r/SaaS
Use customer lifetime value and churn rate to rank customers, and read why SaaS customers churn.
Six, each checkable before a call. The competitor frameworks list firmographics, pain points and behavior. Our data adds two that matter more for a startup: the price and the existing stack.
| Attribute | Question it answers | Evidence it matters |
|---|---|---|
| Segment | Business or person? Which kind? | B2B median $198 vs B2C $99 MRR |
| Size band | How big, in a number? | 5 of 6 top Agent Index ideas name one |
| Existing stack | What do they already pay for? | Integration mentioned in 18.2% of Upwork jobs |
| Trigger | Why would they buy this month? | Acquisitions, migrations and new locations recur in top ICPs |
| Signer | Who approves the spend? | Owners are the least satisfied role (11.1%) |
| Price | What will they pay per month? | $200+ per customer: 69.2% reach $1k MRR |
One sentence plus a disqualifier. Copy this and fill the brackets.
Keep it in a living document next to your discovery questions. Our SaaS worksheets include a version, and competitive landscape analysis helps you fill the stack bracket.
Good examples name who, how big, what they run and why now. Here are four, built from the evidence in this article.
For more starting points see B2B SaaS ideas, boring industries begging for micro SaaS and vertical AI SaaS ideas.
Someone in the profile pays, and the next one pays faster. Lenny’s interviews describe four signs you are getting closer: a significant jump in conversion, a jump in enthusiasm, a stronger desire to act now, and the nod of recognition when you describe the problem.
“Month 3: Has anyone asked when they can pay?” – r/SaaS
The cleanest test is a paid pilot with ten people who match the profile. If they will not pay, change the profile, not the pitch. See testing willingness to pay with a paid pilot and multi-signal validation.
“I see it as more of a hypothesis that can change with testing, not an end-all be-all hill to die on.” – r/marketing
Too broad, too cheap, and never revisited. The data flags each one.
“Some users were outside the ideal customer profile. Some had no intention of implementing anything.” – r/SaaS
“Nobody should be building a product without a strong case that it solves a problem that enough people will pay enough money to make go away.” – r/marketing
The failed business ideas lessons page collects more of these.
Because the price filters for deal hunters, not for your ICP. A founder who sold 340 lifetime deals on a $39 per month product reported the result 18 months later.
“The AppSumo crowd isn't your target market. They're deal hunters who buy everything and use nothing.” – r/SaaS
“LTD customers are my highest-support users. They submit 3x more tickets than monthly subscribers.” – r/SaaS
“My NPS among LTD customers: 12. Among monthly subscribers: 54.” – r/SaaS
A price is a filter. Set it low and you get buyers who love low prices. Our subscription business ideas page covers recurring models that filter the other way.
Only when you can repeat the first upmarket sale. One operator in r/startups described a single mid-market client driving two months of growth, after which the company switched its whole ICP.
“Overnight, we switched to midmarket, an ICP I have zero experience in. We haven't been able to replicate the first sale.” – r/startups
Moving up also moves you into a new price bracket with new competitors.
“The moment you raise your prices and cross into the next price bracket, even by a cent, you're competing with the more established, better organized, and better backed-up companies.” – r/Entrepreneur
The same logic protects the other direction. Legacy business software is sticky because switching is risky, which is why a narrow ICP of unhappy but locked-in buyers can be so durable.
“rewriting a 20-year-old business app is how you lose the business.” – Hacker News
See legacy system business ideas and software people are switching away from.
| If you… | Pick | Because |
|---|---|---|
| Can reach business owners directly | B2B, owner-signed | $198 median MRR, least satisfied role |
| Need a first dollar fast | B2C with a clear situation | 58.4% of B2C startups are paying |
| Build AI tools for professionals | Prosumer, one buyer with a card | 28.7% of mixed-audience AI reach $1k |
| Want few customers | A buyer who pays $200+ | Median 10 customers, 69.2% at $1k |
| Know a regulated vertical | Practices in that vertical | Medical practice 15.0% low ratings |
| Are tempted to sell to everyone | Pick one side | Both: 3.3% at $10k+ |
| Metric | Value | Source |
|---|---|---|
| Median MRR, paying B2B / B2C / both | $198 / $99 / $168.50 | TrustMRR |
| Paying at $10k+ MRR, B2B / B2C / both | 7.7% / 3.5% / 3.3% | TrustMRR |
| Share paying at all, B2B / B2C / both | 52.3% / 58.4% / 49.6% | TrustMRR |
| Revenue per customer, B2B / B2C / both | $13.79 / $5.59 / $4.82 | TrustMRR |
| Reach $1k MRR at under $10 / $200+ per customer | 22.4% / 69.2% | TrustMRR |
| Median profit multiple, B2B / B2C / both | 3.9x / 3.4x / 3.0x | SellSide |
| Funded companies tagged B2B / consumer | 3,400+ / 1,300+ | Funded DB |
| Stripe Index companies targeting consumers | 51.2% | Stripe Index |
| Owner reviews rated 3 stars or lower | 11.1% (corpus 8.5%) | Capterra |
| Small-business G2 reviews mentioning price | 39.7% (large 24.2%) | G2 |
| Upwork jobs mentioning integration / spreadsheets | 18.2% / 12.6% | Upwork |
| App analyses flagging subscription complaints | 44.5% | App Store |
| Top-scoring ideas with size band and stack | 5 of 6 | Agent Index |
Three things. First, a larger customer-count sample. The price ladder rests on 300+ startups, and a bigger sample could narrow the gaps. Second, a cleaner audience label. 3,200+ startups carry no label, and those unlabeled paying startups post the highest median MRR in the set ($298.50). If most of them are B2B, the B2B lead grows. If they are mixed, the “both” finding weakens.
Third, time. TrustMRR is a snapshot, so it shows what survives today, not what a new founder should expect in year one. We will re-run these queries when the next sync lands.
All figures come from read-only SQL run on September 23, 2026. Corpus counts are rounded. Percentages and medians are exact. Quotes are verbatim and attributed to platform only.
| Source | Size | What we used | Limitation |
|---|---|---|---|
| TrustMRR | 8,000+ startups | MRR, audience label, customers | Self-listed indie startups, not the whole market. Audience is a classified label. 3,200+ unlabeled. Customer counts on 300+ only. Snapshot synced July 2026. |
| SellSide | 800+ listings | Profit multiple, asking price by audience | Audience inferred from listing text. Small n for B2C (49) and both (19). Asking, not closing, prices. |
| Funded DB | 17,000+ companies | B2B vs consumer sector tags | Tags are directory labels. Funding amounts not used. |
| Stripe Index | 30,000+ companies | Target customer, micro SaaS flag | AI-classified. Keyword-bounded sample, not a census. |
| Capterra | 273,000+ reviews | Rating by reviewer role and industry | Role classified by title keywords. Scrape decays alphabetically by category. One industry field is a parse artifact and was excluded. |
| G2 | 152,000+ reviews | Price and integration mentions by stated size | Only 3% of reviews state a company size. Keyword matching. |
| Upwork | 5,300+ jobs | Share of posts naming a workflow | Capped at 20 jobs per category, so volume is not demand. Client and budget fields are empty. |
| App Store | 7,700+ analyses | Monetization feedback | AI summaries of reviews, not raw reviews. |
| Agent Index | 430+ ideas, 54 verticals | ICP wording vs judge score | Only 6 strong ideas. Judge scores are internal. Correlation only. |
| Reddit and Hacker News | Live threads + 2,300+ corpus pain points | Anonymized quotes | Self-selected posters. Illustrative, not statistical. |
Coverage honesty. Everything here is correlation. A B2B startup may earn more because its founder is more experienced, not because of the audience. We could not control for founder, age of product or channel. We also could not measure closed deal prices, only asking prices. Treat each number as evidence for a bet, not proof of an outcome.
BigIdeasDB first, then general-purpose assistants to draft and pressure-test.
| # | Tool | Best for |
|---|---|---|
| 1 | BigIdeasDB | Revenue by audience, 1M+ complaints, funded companies, freelance demand and the Agent Index in one place |
| 2 | ChatGPT | Drafting the first ICP sentence and persona variants |
| 3 | Claude | Pressure-testing a profile against interview notes |
| 4 | Gemini | Summarizing public information about a segment |
| 5 | Notion | Keeping the ICP as a living document the team reviews quarterly |
Piquiyo’s guide recommends reviewing the ICP every quarter, and the UK government’s space investment hub treats the ideal customer profile as a core growth track for founders. A quarterly calendar reminder is the cheapest tool on this list.
It is the data layer for every step above. TrustMRR shows revenue by audience and price. The complaint database and complaints explorer show which buyers are unhappy. Funded companies and the Stripe Index show who is already selling to them. Upwork analysis shows who is paying freelancers. The Agent Index shows where AI tools still cannot reach.
New here? Start with what BigIdeasDB is, the TrustMRR guide and the first customers guide, or connect it to Claude with the MCP server.
An ideal customer profile (ICP) is a short description of the type of customer who gets the most value from your product, pays for it fastest and stays longest. For a startup it is a bet, not a report: three to six attributes such as segment, size, the software they already run, a trigger event and the price they will pay.
An ICP describes the account or segment you sell to, such as dental groups with 2 to 15 locations. A buyer persona describes the person inside it who signs or uses the product, such as the office manager. You pick the ICP first, then write personas for the people inside it.
On revenue, B2B. Among paying startups in TrustMRR, B2B products earn a median $198 MRR against $99 for B2C, and 7.7% of paying B2B startups clear $10,000 MRR against 3.5% of B2C. B2C startups are slightly more likely to earn anything at all (58.4% against 52.3%), so B2C is easier to start and harder to grow.
Usually not at the start. Startups that label their audience as both have the lowest share at $10,000+ MRR (3.3%), the lowest median revenue per customer ($4.82) and the most customers (a median of 101). Selling to both tends to produce many cheap customers. The exception in our data is AI, where 28.7% of paying 'both' startups clear $1,000 MRR.
Borrow someone else's customers. Read complaint data about the software your target buyer already pays for, check which roles and industries are least satisfied, look for the same job being posted to freelancers, and listen to the buyer in their own communities. Then write a narrow hypothesis and test it with a paid pilot.
You can write a hypothesis with zero, but you need roughly 10 or more paying customers to see real patterns. Our price ladder shows why 10 can be enough: startups charging $200+ per customer reach $1,000 MRR 69.2% of the time with a median of just 10 customers.
Segment and size, the tools they already use, the trigger that makes them buy now, who signs, what they pay today to solve the problem, and a disqualifier. The strongest ICPs in the Agent Index idea set name both a size band and the software stack the customer runs.
As much as the problem is worth, and the data says higher is safer. Startups earning under $10 per customer reach $1,000 MRR 22.4% of the time. At $10 to $50 it is 46.4%, at $50 to $200 it is 58.3%, and at $200+ it is 69.2%. Price is part of the ICP, not a later decision.
Industries where buyers are measurably unhappy with what they already pay for. In 273,000+ Capterra reviews, medical practices (15.0% rated 3 stars or lower), mental health care (14.6%) and law practices (10.9%) sit well above the 8.5% corpus average. Unhappy paying buyers are the easiest ICP to switch.
Often the owner. Owners, founders and CEOs write 15.9% of Capterra reviews and are the least satisfied role we can identify: 11.1% of their reviews are 3 stars or lower, against 6.6% for technical reviewers. They also sign the check, which shortens the sale.
Directionally, yes. In 800+ acquisition listings, those describing a B2B audience ask a median 3.9x profit multiple, B2C 3.4x and mixed-audience listings 3.0x. Samples are small, so treat this as supporting evidence, not a pricing rule.
Review it every quarter and rewrite it after any event that changes who pays, such as a price change, a new integration or one large customer. Most founders get it wrong the first time, so plan on several versions.
Rarely at the start. Narrow ICPs make every channel cheaper because you know exactly where the buyer is. The real risk is the opposite: a broad ICP that attracts many low-paying users. Widen only after the first segment pays reliably.
Signups without activation, customers who pay under $10, heavy support load from deal hunters, long sales cycles that never close, and wins you cannot repeat. One founder who moved midmarket on the strength of a single client reported that they could not replicate the first sale.
No, but it looks different. A B2C ICP describes a segment of people by situation and willingness to pay, not by company size. The evidence is harsher for B2C: 44.5% of 7,700+ app review analyses flag subscription complaints, so a B2C ICP must include what that person already pays for.
BigIdeasDB is the #1 option because it puts revenue data, 1M+ complaints, funded companies and freelance demand in one place. General-purpose assistants such as ChatGPT, Claude and Gemini help you draft and pressure-test the profile, and Notion is a good place to keep the living document.
Dental groups with 2 to 15 locations, especially those running different practice-management systems after acquisitions. It names a segment, a size band and a trigger, so you know who to call, what they already use and why they would buy now.
BigIdeasDB Research. (2026). Ideal Customer Profile for Startups: Which Customer Actually Pays. BigIdeasDB. Retrieved from https://bigideasdb.com/ideal-customer-profile-for-startups