How To Size A Market Using Public Data And Basic Math

Top-down market sizing is a lie you tell investors. Bottom-up sizing is the truth you tell yourself. Buying a $4,000 report from a research firm gives you a useless billion-dollar aggregate figure. You cannot deposit a total addressable market into a bank account. You can only deposit revenue from specific people paying for a specific solution. To size a market, you must multiply the exact number of reachable customers by the annual price they are willing to pay.

This process does not require a proprietary database. The internet leaks customer data constantly. Every public review, job posting, open-source repository, and forum thread is a breadcrumb. You just need to know how to count them.

The Competitor Review Multiplier

The fastest way to size an existing market is to count the people already paying for a solution. Private companies hide their revenue, but they cannot hide their public reviews.

Let us look at a real app category. Shopify merchants need age verification tools to legally sell wine or vape products. We want to know if building a better age verification app is worth the engineering time.

Go to the Shopify App Store. Look at the top three apps in this niche. The leading app has roughly 600 reviews. The second has 200 reviews.

Software applications typically see review rates between 1 percent and 5 percent. We use 2 percent to remain conservative. This means for every single review, there are 50 active users.

We multiply 600 reviews by 50 to get 30,000 active users for the top app. We multiply 200 reviews by 50 to get 10,000 for the second. The proven, active market is at least 40,000 users.

Next, we look at their pricing. The average paid tier for these apps is $10 per month.

Multiply 40,000 users by $10 a month. That is $400,000 in monthly recurring revenue. Multiply that by 12 to get a $4.8 million annual recurring revenue market just for the top two apps.

This is a real market you can attack. You do not need to guess if people will pay for this. The math proves they already are. You can apply this same multiplier logic across almost any marketplace. Look at the Google Workspace Marketplace, the Atlassian Marketplace, or the WordPress plugin directory. The math remains consistent. Find the reviews, apply a conservative multiplier, and calculate the active user base.

The Ecosystem Drop-off Method

Sometimes there are no direct competitors to count reviews for. You must start from the total platform size and filter down using public constraints.

Imagine you are building a debugging tool for GitHub Actions deployment failures. GitHub publicly states they have over 100 million developers. That number is completely useless. You need the number of engineering teams willing to pay for continuous integration tools.

Look at public repositories. You can use the GitHub API to search for repositories containing a specific workflow directory. Running a sampled API script reveals that roughly 15 percent of active organizations use GitHub Actions.

If there are 4 million active organizations on GitHub, 15 percent gives you 600,000 organizations.

Now filter by the specific problem. How many of these organizations experience painful deployment failures? Look at demand signals across Stack Overflow and GitHub Issues. Search for specific error codes related to memory limits or timeout failures.

If a search query for a specific error returns 50,000 recent issues, you have a baseline of organizations experiencing the pain. If you plan to charge $50 a month for your debugging tool, your immediate addressable market is 50,000 multiplied by $600 a year. That equals $30 million.

This method forces you to define your exact customer. You are not selling to developers broadly. You are selling to organizations using GitHub Actions that struggle with memory limit errors.

Search Volume Triangulation

Search volume tells you exactly how many people are actively trying to solve a problem right now. You can access this data using free tools like Google Keyword Planner or the free tiers of SEO software like Ahrefs.

Do not look at broad terms. A search for "project management software" is useless because the intent is too scattered. Look at long-tail, transactional queries. Look for searches like "Jira alternative for hardware teams" or "export Figma to React Native".

Let us size a market for a Figma to React Native plugin. The search term "Figma to React Native" gets roughly 2,500 searches a month globally.

Assume a 3 percent click-through rate if you manage to rank in the top three results. That is 75 visitors a month from your primary keyword.

Assume a 2 percent conversion rate from visitor to paid user. That is 1.5 new customers a month.

This sounds terrible. It is terrible. This is exactly why bottom-up sizing is mandatory. It prevents you from spending six months building a tool that only generates two sales a month.

If you want to make $10,000 a month, the math tells you exactly what must change. You either need a product that costs $1,000 a month, or you need to find 50 more high-intent keywords to target. The arithmetic does not care about your enthusiasm.

Scraping Public Directories

Business-to-business markets often have public directories. Dentists, plumbers, independent pharmacies, and specialized e-commerce stores are all listed publicly.

If you are building a tool for independent pharmacies, do not search Google for a pharmacy market size report. Go directly to the National Community Pharmacists Association website. They publicly state there are 19,400 independent pharmacies in the United States.

You plan to sell a compliance software package for $200 a month.

Multiply 19,400 pharmacies by $2,400 a year. The total theoretical market is $46.5 million.

You will never capture 100 percent of the market. A realistic penetration rate for a successful bootstrapped software company is 1 percent.

Calculate 1 percent of 19,400. That is 194 customers.

Multiply 194 customers by $2,400 a year. That is $465,600 in annual revenue.

This arithmetic tells you exactly what a realistic success case looks like. If your goal is to build a $10 million company, this market is too small. If your goal is to build a highly profitable solo business, this market is perfect.

Sizing Through Job Boards

Job postings are public declarations of budget. If a company is hiring a full-time employee to handle a specific problem, they are willing to spend $80,000 to $150,000 a year to make that problem go away.

Let us size the market for a specialized Salesforce automation tool. Go to Indeed or LinkedIn. Search for "Salesforce Administrator".

If there are 10,000 open roles, that means 10,000 companies are currently feeling enough pain to allocate a full-time salary to managing their customer relationship management software.

If your software automates 30 percent of a Salesforce administrator's job, you are not selling a $10 a month productivity tool. You are selling a $1,000 a month tool that delays the need for a new hire.

Multiply 10,000 companies by $12,000 a year. That is a $120 million immediate addressable market.

This method works perfectly for internal tooling and enterprise software. You do not need a research firm to tell you the market size. You just need to count the open job requisitions and price your software as a fraction of the salary.

Analysing Demand Signals

Raw numbers alone do not prove willingness to pay. You must read the demand signals across the web.

Go to Reddit, Hacker News, or specialized industry forums. Look for people discussing the specific problem your software solves.

Count the number of times people mention paying for a workaround. If users are cobbling together Zapier, Airtable, and a virtual assistant to complete a task, they have a dedicated budget.

Add up the cost of the workaround. Zapier costs $30 a month. Airtable costs $20 a month. The virtual assistant costs $200 a month. The current fragmented solution costs $250 a month.

When evaluating these demand signals, you must ignore feature requests and focus entirely on pain. A user asking for a dark mode interface is not a demand signal. A user stating they just spent four hours manually updating CSV files is a massive demand signal. You are looking for friction that costs time or money.

Once you find the friction, you quantify it. If a mid-level employee makes $40 an hour, and a manual process takes them four hours a week, that process costs the company $640 a month. Your $150 a month software is a bargain. You then multiply that $150 by the number of users you found in your ecosystem drop-off analysis.

Calculating The Ceiling

Bottom-up sizing is just as valuable for telling you when a market is too small.

Assume you want to build a specialized analytics tool for creators who sell Notion templates.

How many people sell Notion templates full-time? Look at Gumroad public data, Etsy search results, and Twitter communities. You might find roughly 500 serious creators making a living this way.

If you charge $20 a month, your maximum theoretical revenue is 500 multiplied by $240 a year. That is $120,000 a year.

That is the absolute ceiling. If you capture an aggressive 10 percent of the market, you make $12,000 a year.

This is a side project. It is not a venture-scale business. It is barely a full-time income. Knowing this before you start writing code saves you years of frustration.

The Danger of Top-Down Thinking

Top-down sizing relies on broad, meaningless categories. A paid research report might claim the Creator Economy is a $100 billion market.

This figure includes YouTube advertising revenue, hardware sales of cameras and ring lights, and venture capital funding for new social platforms. It has absolutely nothing to do with your software application for podcast editing.

Top-down numbers are designed to sell reports to enterprise strategy teams. They are not designed to help a developer decide what to build this weekend.

Bottom-up sizing forces you to confront reality. It forces you to identify exactly who will buy the product, where they currently hang out, and exactly how much they will pay. The arithmetic is brutal, but it never lies.