How to Answer "How Do You Know People Want This?" on the YC Application

The question has two layers:

Layer 1: Is the problem real? Does the problem you are solving actually affect real people in a meaningful way, or is it a problem that exists in theory but that actual users are comfortable living with?

Layer 2: Is your specific solution the one people want? Even if the problem is real, your specific approach to solving it may not be the one users will adopt. Evidence that people want your specific solution — not just that the problem exists — is what answers this field completely.

Most founders answer Layer 1 adequately. Very few answer Layer 2 with the same specificity. The applications that get interviews answer both.

Not all evidence is equal. YC partners weight evidence in this order — highest to lowest:

1. Revenue from paying customers Someone gave you money for your product. This is the strongest single signal. Even one payment of ₹500 is more credible than a 500-person waitlist. State the number of paying customers, the revenue, and the billing cycle.

2. Repeat usage by active users Users who came back to use your product without being prompted. Repeat usage signals that your product delivered enough value the first time to earn a second interaction. Cite the retention rate and the timeframe: "71% of users who signed up in our first month have used the product at least once in the last 7 days."

3. Behavior-based pre-commitment Users who took a meaningful action to signal demand before your product was fully built. This includes: paying a deposit or pre-order, joining a waitlist with personal contact information, asking when they can pay, or spending significant time in a pilot session. These are demand signals that required something from the user.

4. Qualitative evidence from user interviews Specific things specific users said in interviews that reveal genuine pain. Not "they said the problem was important" — the specific words, the specific emotion, the specific moment when you realized the problem was more acute than you had assumed. "One pharmacy owner told me she had cried the last time she found ₹80,000 of expired medicine in a single stock check. That moment is when I knew this was worth building."

5. Proxies for demand in the absence of direct evidence If you have none of the above yet, proxies include: search volume for related queries, forum posts where people describe the pain in their own words (Reddit, Facebook groups, Quora), the existence of workarounds people have built themselves (a pharmacy owner who built their own Excel sheet to track expiry because nothing else worked), or industry reports that quantify the cost of the problem.

Proxies belong at the bottom of this list because they are the least founder-generated form of evidence. Use them to supplement stronger evidence, not as a substitute for it.

Lead with your strongest evidence signal. State it in one sentence with a specific number. Follow with your second strongest signal. Then add one qualitative detail that makes the evidence feel human rather than statistical.

Template: "[Strongest signal with number]. [Second signal with number]. [One qualitative observation that reveals the depth of the problem]."

Example for a company with paying customers: "We have 23 paying customers at ₹2,800/month, with month-2 retention of 89%. 11 of our customers came from referrals — pharmacy owners recommending us to other pharmacy owners in their WhatsApp groups without being asked. One customer, a pharmacy owner in Nashik, told us he flagged ₹34,000 of near-expiry stock in his first week and called us to say it had paid for a full year of our software in a single use."

Example for a pre-revenue company: "We have no revenue yet. We have conducted 67 interviews with independent pharmacy owners across Pune, Nashik, and Aurangabad over 8 weeks. 43 of 67 said they currently track stock in notebooks or Excel. 11 agreed to use our beta version and give us weekly feedback without any incentive. 3 of them independently asked us when they could pay — one sent us a UPI payment request before we had a payment system set up."

Both examples are strong because they lead with specific numbers and add a human detail that reveals genuine demand rather than politeness.

Counts as strong evidence:

• Paying customers with specific MRR or ARR figure

• User retention rate with a timeframe

• Referrals that happened without incentive

• Users who came back after trying the product

• Pre-orders or deposits collected

• LOIs or pilot agreements signed

• User interviews with specific verbatim observations

• Users who built their own workarounds to solve the problem

Counts as weak or no evidence:

• Market size reports from consulting firms

• Survey data from third-party sources

• Number of people who said they "would use" your product

• Number of people who said the problem was "important"

• Friends and family who tried the product

• App store downloads with no engagement data

• Social media impressions or follower counts

• Competitor revenue as a proxy for your potential

The distinction is this: strong evidence requires someone other than you to have taken an action. Weak evidence requires only that someone said something.

Most founders treat this field as a market validation field — a place to prove the market is big and real. That is wrong. The market validation belongs in the market size field. This field is specifically about evidence that people want your specific product.

The confusion leads to the most common failure mode in this field: answering "is the problem real?" with market data and never answering "do people want your specific solution?" with user evidence.

A pharmacy software market that is worth $4B tells a partner that pharmacy software is a real market. It tells them nothing about whether pharmacy owners want your WhatsApp-native approach versus the desktop SaaS approach that every other pharmacy software company uses.

The specific evidence that people want your specific solution — not just that the category has demand — is what this field is asking for.

Mistake 1: Leading with market size instead of user evidence Market size answers "is this market real?" not "do people want this product?" Put market size in the market size field. Put user evidence here.

Mistake 2: Citing survey results where users said they would use your product Stated intent and actual behavior have almost no correlation in consumer research. "80% of respondents said they would use a product like this" is worth almost nothing as evidence. What people do with their money, time, and attention is evidence. What they say on a survey is noise.

Mistake 3: Describing user interviews without specifics "We talked to 50 potential customers and they validated our hypothesis" is a nearly useless sentence. Which customers? What did they say specifically? What were their exact words when they described the problem? One specific quote from one specific user interview is more credible than a generic count.

Mistake 4: Counting friends, family, or colleagues as validation Users who agreed to try your product because of a personal relationship do not constitute demand evidence. Their behavior may not represent the behavior of users without that relationship. Specifically note when you are citing evidence from users who had no prior relationship with you — cold user evidence is significantly more credible than warm.

Mistake 5: Confusing app downloads with user demand 10,000 app downloads says something interesting about top-of-funnel curiosity. It says nothing about whether your product delivers enough value that users will pay for it or return to it. Pair any download figure with a 7-day or 30-day retention rate and the answer becomes meaningful.

Mistake 6: Future-tense evidence "We plan to conduct user interviews" and "we will validate with a pilot cohort" are not evidence. This field asks how you know people want this — in past tense. If you cannot answer this question with past-tense evidence, you are not ready to apply.

Hardware products: Physical prototype usage by real users is strong evidence. "We gave 5 farmers an early version of our soil sensor and 4 of them asked to keep it after the pilot ended" is a compelling demand signal for hardware.

Regulated markets: Sometimes direct user validation is limited by regulatory constraints — you cannot let patients use a medical device before approval, for example. In this case, lead with clinical validation, physician interview data, or regulatory progress as a proxy for demand.

Enterprise B2B: Enterprise buyers will not pay without going through procurement. But signed pilots, LOIs, and specific named companies in your pipeline are credible demand signals for enterprise. "We have 2 signed pilot agreements with [type of company] and 3 companies in active final evaluation" is strong enterprise demand evidence even without revenue.