How to Do Market Research for a Startup (With Real Data)

To do market research for a startup, test the idea against four kinds of evidence in order: what customers complain about, how many software products already serve them, whether search demand is growing, and what comparable products earn. Then talk to 10 to 15 buyers. Stop at the first test the idea fails. This guide runs that method on one real idea, an estimating and lead follow-up tool for small HVAC and home-service contractors, using live numbers from BigIdeasDB's 1M+ complaint corpus, the Stripe directory and TrustMRR revenue data.

The result is not a clean yes. The complaints are strong, the niche is thinner on software than most, search demand is flat, and revenue is real but modest. That mix is what honest market research looks like, and it is why the verdict at the end is "interview before you build".

How do you do market research for a startup?

What do most market research guides leave out?

They tell you to form a hypothesis, run a survey, interview customers and estimate market size, and they give you no demand data to run any of it on. The pages that rank for this question are well written and generic. Government guides such as the SBA's business planning resources and Census Bureau data are good for the size and shape of an industry. They cannot tell you whether the specific buyer you have in mind is annoyed enough to pay.

Founders notice. A recurring thread in r/startups, r/smallbusiness and r/Startup_Ideas asks how to do this, and the most upvoted answers say the same thing: skip the reports and go where the market complains.

"The trick that worked for me was to skip the reports and go where the market complains. Find the 5-10 subreddits, facebook groups or review sections where your buyer already vents, and read 50 threads before you open a single market-size pdf."
via r/startups

That is the method here, with the counting done for you. If you want tools rather than method, our list of the best market research tools for startups compares them. This guide is the how-to.

Step 1: What exactly are you trying to find out?

Write one research question that names a buyer, a job and a price they might pay. "Is there a market for HVAC software?" is too broad to answer. "Will owners of 2 to 15 person HVAC and home-service shops pay for a tool that turns estimates into follow-ups?" can be answered with evidence.

Our worked example uses that second question. We picked it from the data rather than from taste: in Capterra, HVAC software has a market gap score of 8.0 on its top complaint, the Stripe directory shows few software companies serving trades, and the buyer is easy to identify. It is a deliberately ordinary idea, because market research is mostly about ordinary ideas.

Write down what would make you stop. For this idea: fewer than half of the products in the category share a major complaint, or software already makes up a large share of the niche, or no comparable product earns above $1K a month. Deciding the kill criteria before you look is how you avoid arguing yourself into a bad idea. For a longer treatment of this, see our guide to validating a startup idea.

Step 2: What do customers already complain about?

Count how many existing products share the same complaint, and how severe it is. A complaint that appears across many competitors is a market gap. A complaint about one product is a product bug.

BigIdeasDB holds a 1M+ complaint corpus built from Capterra and G2 reviews, Reddit pain points, App Store reviews and more. For the HVAC example we read the Capterra systemic pain points for the HVAC category, which covers 12 products and 250+ analyzed reviews.

The finding: lead tracking is the single most shared gap, and it sits right next to the idea. Two thirds of the HVAC products Capterra analyzed leave customers without automated lead tracking, and a further 7 of 12 fall short on client communication. Both point at the gap between an estimate going out and a job being booked, which is where our example idea lives.

Check the same complaint outside review sites. In BigIdeasDB's Reddit pain points, contractors describe the pricing side of the same workflow:

"...clients... operating on 2015 pricing" and "The price you offered didn't account for that risk"
via r/construction

Two independent sources, review sites and a trade forum, describe friction around estimates and follow-up. That is the standard we hold a complaint to before moving on. A single viral thread is not evidence. For more on mining complaints, see how complaint analysis works and our guide to Reddit market research.

Pass rule for step 2: at least half of the products in the category share the complaint, severity is 4.0 or above, and a second source confirms it. The example passes on all three.

Step 3: How crowded is the market, really?

Measure software density, meaning the share of companies in a niche that sell software, not the raw number of companies. A niche with 1,000 companies and 15 software products is not crowded. It is full of operators and empty of tools.

The Stripe directory lists 30,000+ real companies, and BigIdeasDB scores each one for category and business model. We compared the trades niche against the whole directory.

In the Home Services & Trades category, 52.5% of companies are services businesses and 1.6% are software, against 26.0% and 21.6% across the whole directory. The niche is a place where people sell labor, not tools. HVAC specifically looks closer to normal at 15.2% software, which is a useful correction: the thinness is strongest in cleaning, lawn care and general trades, and weaker in HVAC, where several tools exist. For why density beats raw counts, see our market saturation analysis and the Stripe Index page.

This is where a generic guide would say "analyze your competitors". The useful version is a ratio you can compare. If your niche's software share is far below 21.6%, the buyers are underserved or cannot be served profitably. Steps four and five tell you which.

Pass rule for step 3: software share below the directory average, or a clear wedge against the tools that exist. The example passes at the trades level and is borderline for HVAC alone, so the wedge has to be specific. See our guide to competitive landscape analysis for how to find it. An existing competitor is validation, not a verdict.

Step 4: Is demand rising or falling?

Use Google Trends for direction and timing, never for volume. Trends reports interest on a 0 to 100 scale indexed to the peak of the terms you compare, so two separate runs are not comparable.

The finding: interest in HVAC software is flat to falling, and the most specific term, "hvac estimating software", barely registers. Both of the larger terms dropped sharply in the same week of July 2026, which looks as much like a change in how the data was sampled as a change in demand. We treat it as flat, not as a collapse.

What a low reading means depends on the buyer. Contractors rarely search for software by category. They ask other contractors, or they search for a brand. A flat Trends line for a trades product is a caution, not a veto. It does mean you cannot count on search to acquire customers, which changes how you plan distribution. Our guide to using Google Trends inside Claude and ChatGPT covers the setup and the gotchas.

Pass rule for step 4: the term is not in structural decline, or you have another way to reach the buyer. The example is flat, so it passes with a flag that acquisition will not come from search.

Step 5: What do comparable products earn?

Look up what products aimed at the same buyer earn, because revenue sets the ceiling on what the market is worth to a small team. If nothing comparable earns more than a few hundred dollars a month, the buyers may not pay.

TrustMRR holds verified revenue for thousands of startups. We filtered to products whose description or audience names contractors, plumbers, HVAC, roofers, landscapers, electricians, cleaning companies, handymen or field service.

The finding: this niche pays, but the middle is thin. 7 of 19 comparable products earn $1K or more a month, and 4 earn $5K or more. That is enough to say buyers will pay for software in the trades, and not enough to say a new entrant will reach the top. Only 19 of the 47 report any revenue at all, so most products aimed at this buyer earn nothing we can see. For how to read revenue benchmarks safely, see our SaaS revenue benchmarks and the revenue intelligence help page.

Pass rule for step 5: at least a few comparable products above $1K a month, so a price point exists. The example passes.

Step 6: What do 10 to 15 buyers say?

Interview 10 to 15 people in the exact buyer role, and ask what they did the last time the problem happened. Steps two to five told you where to look. This step tells you whether anyone will pay.

Founders in the research threads converge on the same rules. Do not ask whether they would use your product. Ask about behavior:

• What did you do the last time this happened? A specific story beats an opinion.
• What do you use today, and what does it cost you? Money or time lost is the evidence.
• Have you tried to fix it yourself? A workaround is the strongest signal. As one r/startups founder put it, "if they've already hacked together some workaround, it's usually not imaginary pain."
• Who else has this problem? That names your next five interviews.

For the estimating idea, the questions become concrete: how many estimates went out last month, how many turned into jobs, and what happens to the ones nobody answers. If the answer to the last one is "nothing, we just wait", the pain is real. If it is "we call every one of them", the problem is already solved.

"Surveys ask people to predict what they'd do, and people are bad at that... Stated interest is free and mostly worthless, revealed interest costs something."
via r/smallbusiness

Test willingness to pay with something small and real: a waitlist with a deposit, a pre-order, a landing page that asks for a card. Another commenter drew the line plainly: "People saying 'that's useful' is worthless." Silence counts as an answer too. As one commenter observed, one of the biggest failure points is not understanding that silence is an answer.

Two practical notes. First, do not post surveys in subreddits such as r/smallbusiness, whose automated rules ask people not to conduct market research on the community. Read the existing threads instead, which is what steps two and three already did. Second, if you have never worked in the industry, run the interviews as a learner, not a seller, and read how to validate a business idea in an industry you don't know.

The right number of interviews is smaller than most founders fear. One r/Startup_Ideas commenter said there is a huge difference between a week of 10 customer interviews and half a year analyzing market segments. After 5 or 6 calls you usually start hearing the same complaints.

Step 7: How big is the market, from the bottom up?

Size the market last, from the bottom up: reachable buyers multiplied by what each will pay, multiplied by the share you can realistically win. A top-down figure such as "the field service market is worth billions" tells you nothing about whether your product has customers.

Here is the formula with placeholder inputs, which are illustrative arithmetic and not data:

1. Reachable buyers. The shops you can actually contact. Say 5,000 small HVAC and home-service businesses in your target states.
2. Price they will pay. Take it from interviews and the $1K+ MRR products in step 5. Say $60 a month, or $720 a year.
3. Share you can win. A new entrant with no search demand might reach 2% in three years: 100 customers.

That gives 100 customers at $720 a year, or $72,000 in annual revenue. The point is not the answer. It is that every input is something you can check, and the output tells you whether the business is a side income or a living. If the bottom-up number is under what you need, no top-down market size will fix it. Our guide to calculating market size for a startup covers TAM, SAM and SOM in detail.

What does the worked example say?

Verdict: interview before you build. Pain and willingness to pay pass, saturation is mixed, demand is flat. Here is the scorecard.

Read the table honestly. The idea has a documented gap and a proven price point. It does not have an easy way to find customers, and the niche is not as empty of software as the category numbers suggest. The next move is 10 to 15 interviews with shop owners, asking the step 6 questions, before any code. If a majority describe a manual follow-up process they hate, build a landing page with a deposit. If they shrug, drop the idea and re-run the method on the next one in an afternoon.

If you have no idea yet, start with how to find startup ideas and bring the shortlist back here.

Can you do market research with AI?

Yes, but Claude and ChatGPT can only analyze evidence they can see, and they cannot reliably read Reddit threads, store reviews or Google Trends by themselves. Ask a chat assistant for the market size of HVAC software and you get a confident paragraph with no traceable source. Give it 300 collected reviews and ask it to group and count the complaints, and you get research.

That split is the whole method. Collection is the hard part, and it is what steps two to five depend on. BigIdeasDB Desktop is a local-first Mac and Windows app that collects the evidence on your own computer: Reddit and community threads, App Store and Google Play reviews, G2 and Capterra reviews, Google Trends, search demand, YouTube, app marketplaces and more. It then exposes everything to the AI agent you already use, whether Claude, Claude Code, ChatGPT desktop, Codex or Cursor, through a local MCP server.

• No API key and no AI bill from us. There is no AI key inside the app. The analysis runs on the agent and plan you already pay for.
• Your evidence stays on your machine. Projects and collected rows are saved locally.
• Counted findings, checked quotes. Deep Research reports count what was found and check each quote word for word against a stored row, so a number in the report traces to collected evidence.
• Price. Desktop is in Beta. It is included with Basic and Pro, or sold as a one-time add-on, and can be activated on up to 3 computers. The live price is on the pricing page.

A prompt that works once Desktop is connected: "Start a project on an estimating and follow-up tool for HVAC contractors. Collect Reddit threads from the trades subreddits and the newest reviews of the top field service apps. Group the complaints, count each group, and quote two real lines per group. Then compare Google Trends for hvac software and field service software." The agent does the analysis. Desktop supplies the rows.

Setup guides and live runs are in our posts on giving Claude G2, Capterra and App Store reviews, connecting Google Trends to Claude and using an MCP server for Reddit market research. The Desktop help page walks through the first run, and our broader guide to using AI for market research covers prompts and limits.

What are the most common market research mistakes?

• Starting with market size. A $40 billion top-down figure says nothing about whether your buyer will pay. Start with complaints and finish with sizing.
• Treating one thread as evidence. Require the same complaint from at least two independent sources, such as review sites and a forum.
• Counting companies instead of software. A crowded niche of services businesses is an opening. A niche with 20 funded tools is not. Measure density.
• Reading Trends as volume. It is relative. Use it for direction and seasonality, then find the buyer another way if the line is flat.
• Asking whether people would use it. Ask what they did last time and what they paid. Opinions are free.
• Surveying a community that does not want to be surveyed. Read existing threads and reviews first. Honest anger in a one-star review beats a polite survey answer.
• Never writing the kill criteria. Decide in step 1 what result would make you stop, or every result will look like a yes.

Methodology and data sources

What this data cannot tell you: whether a specific buyer will pay you, how many shops you can reach, or what a buyer thinks of your particular solution. The worked example covers steps one to five on one idea. Step six, the interviews, is deliberately left to you.

Frequently Asked Questions

Related Reading

BigIdeasDB Research. (2026). How to Do Market Research for a Startup (With Real Data). BigIdeasDB. Retrieved from https://bigideasdb.com/how-to-do-market-research-for-a-startup