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Sizing a local market with public business data means estimating how much room is actually left inside one specific trade area. It is not the same as copying a national TAM number into a city or treating Google review counts as revenue.

This method is for local SEO agencies scoping a client’s territory, franchise teams comparing candidate locations, business owners reviewing a second location, and sales teams deciding whether a city or category is worth targeting.

It is not built for investor TAM slides.

Investors usually expect industry-report-sourced TAM, formal assumptions, and broader market data. This method is for a more practical question:

Is this specific local market worth entering, selling into, or expanding across?

Most local market sizing fails for two reasons.

First, teams scale a national number down by population and ignore local supply.

Second, they treat Google review counts as demand, even though review behavior changes heavily by category.

A better approach is to define the real trade area, pull the local competitor set, use reviews for relative strength, add population and category demand inputs, and calculate a realistic range instead of a guess.

Who This Method Is Actually For

This method is for practical local decisions where the question is not “How big is the national market?” but “How much opportunity exists in this specific area?” It works best for agencies, franchise teams, small business owners, and sales teams comparing real territories.

The problem is that teams often use the wrong market sizing method for the decision they need to make.

A franchise team comparing three possible territories does not need a national TAM slide.

A local SEO agency scoping a campaign does not need a global industry number.

A small business owner deciding between two neighborhoods does not need a 40-page market report before making a first-pass decision.

They need a bottom-up local estimate that shows supply, competitor strength, demand assumptions, and realistic room to win.

Good Fit
Poor Fit
Agency scoping a client territory
Investor TAM slide
Franchise team comparing 3–5 candidate territories
National revenue forecast
Business owner deciding on a second location
Public-company market model
Sales team choosing a prospecting area
Global industry valuation
Local SEO team mapping competitors
Long-term macro demand forecast

The fix is to separate this article’s use case clearly.

Use this method for go/no-go local decisions.

Do not use it as the only source for a funding round, board presentation, or national TAM claim.

Step 1: Draw the Trade Area by Drive Time, Not a Radius Circle

The first step in local market sizing is defining the trade area. If the boundary is wrong, every competitor count, population estimate, and revenue assumption after it becomes weaker.

The common mistake is drawing a flat 3-mile or 5-mile radius around a location.

That looks simple, but customers do not travel in perfect circles. They travel by road access, traffic, parking, transit, convenience, and travel time.

A 10-minute drive-time area can cover a few blocks in a dense city and several miles in a suburban or rural market.

That difference changes the number of people, competitors, and comparable businesses inside the market.

Category Type
Starting Trade Area
Coffee shop
5–10 minutes
Quick-service restaurant
5–10 minutes
Gym or fitness studio
10–15 minutes
Dental clinic
10–20 minutes
Med spa
15–30 minutes
Furniture store
20–40 minutes
Specialty service provider
20–45 minutes

These are starting points, not fixed rules.

A convenience category usually needs a shorter trade area.

A destination category can justify a longer trade area.

The fix is to define the market by drive time or a carefully drawn trade boundary before you pull competitor data.

For a first-pass go/no-go estimate, a basic drive-time boundary or isochrone tool is enough. You do not need enterprise GIS software just to avoid the radius-circle mistake.

Step 2: Pull Every Competitor and Comparable Inside That Boundary

The competitor set is the supply side of the local market. You need to know how many businesses already serve the category inside the trade area before estimating how much room is left.

This is where manual research usually breaks.

A person opens Google Maps, searches a category, copies a few business names, checks ratings, checks websites, copies phone numbers, and stops when the work becomes repetitive.

That creates a partial market view.

A partial view can make a crowded market look open.

It can also make an open market look empty if the wrong category terms or locations were searched.

A better workflow is to collect structured Google Maps business data for the category and trade area.

Use the Google Maps Scraper to collect competitor records with fields like:

  • business name
  • category
  • address
  • website
  • phone number
  • rating
  • review count
  • business status
  • Google Maps URL
  • opening hours
  • location data

The goal of this step is not to call the business count “demand.”

The goal is to build the supply map.

Field
Why It Matters
Business name
Identifies each competitor clearly
Category
Confirms whether the business belongs in the market
Address
Confirms location inside or near the trade area
Rating
Shows public customer sentiment
Review count
Helps compare visibility inside the same category
Business status
Removes closed or inactive listings
Website
Helps review digital maturity
Phone number
Helps validate contact paths for sales or research
Pull the Competitor Set Before You Estimate the Market

Use Outscraper to collect Google Maps business records inside your target category and location before building the estimate. This solves the first major market-sizing problem,

You stop guessing how many competitors exist.

Step 3: Rank Competitors by Relative Strength, Not Revenue

Review count helps rank competitors, but it should not be treated as revenue. A business with more reviews is not automatically making more money than every lower-review competitor.

This is one of the biggest mistakes in local market sizing.

Review behavior changes by category.

Restaurants and cafes often collect many reviews because customers visit frequently and review casually.

Dentists, HVAC companies, accountants, legal services, and B2B providers may have fewer reviews even when revenue is high.

That means review count is not a demand number.

It is a relative visibility signal inside the same category and area.

Use reviews to answer:

  • Which competitors have the strongest local presence?
  • Which businesses dominate attention in this category?
  • Which locations have unusually high or low review volume?
  • Which competitors may be stronger than a simple count suggests?
  • Which market has one dominant player versus a fragmented field?

A cleaner way to use reviews is to calculate share of voice:

Competitor
Reviews
Share of Voice
Competitor A
1,200
40%
Competitor B
600
20%
Competitor C
450
15%
Competitor D
300
10%
Competitor E
250
8%
Others
200
7%

This does not mean Competitor A earns 40% of the revenue.

It means Competitor A owns 40% of the review visibility in that local category.

The fix is to separate what each metric can and cannot prove.

Metric
Use It For
Do Not Use It For
Review count
Relative visibility
Revenue
Rating
Public sentiment
Proof of sales volume
Business count
Supply density
Total market demand
Website presence
Digital maturity
Proof of budget
Phone number
Contact path
Qualification by itself

This keeps the estimate honest.

Step 4: Get Population and the One Number That Is Not Usually Free

Public business data shows local supply. It does not show full market demand by itself. To size the market, you still need population, income, category penetration, and average spend inputs.

This is where many estimates fall apart.

Teams get the competitor count, look at reviews, and jump straight to a revenue number.

That skips the demand layer.

A defensible local market estimate needs these inputs:

Data Point
Where It Actually Comes From
Free?
Business count and competitor ranking
Google Maps business data
Yes
Population inside trade area
Census ACS or block-group data
Usually free
Median household income
Census ACS or demographic source
Usually free
Category penetration or spend rate
Census County Business Patterns, IBISWorld, trade association, internal benchmark, or paid report
Often paid or estimated
Average annual category spend
Trade report, internal data, or industry benchmark
Often paid or estimated

Be clear with clients or stakeholders here.

Everything through population and income can often be gathered from public or free sources.

The input that usually needs a paid source, internal benchmark, or clearly labeled estimate is category penetration.

Category penetration answers:

What percentage of people or households in this trade area are likely to buy this category?

Not every person in a trade area buys boutique fitness, dental implants, accounting services, med spa treatments, HVAC services, or legal services in a given year.

If you guess category penetration without labeling it as an estimate, the entire model becomes weak.

The fix is to label every input by source type.

Number
Label It As
Competitor count from business export
Observed public data
Review share
Relative public visibility
Population
Public demographic data
Income
Public demographic data
Category penetration
Sourced report, internal benchmark, or estimate
Annual spend
Sourced report, internal benchmark, or estimate

This makes the estimate easier to defend because the assumptions are visible.

Step 5: Calculate SAM, Then a Weighted SOM

SAM shows the serviceable available market inside the trade area. SOM shows the realistic share of that market a business can capture after considering competitor strength.

The common mistake is splitting the market evenly.

If there are 9 competitors, the weak shortcut is:

100% divided by 9 = 11.1% per business.

That looks clean, but it is rarely realistic.

One competitor may dominate local visibility.

Another may have a better location.

A new entrant usually does not capture an even share in year one.

Use this structure instead:

Step
Formula
Estimated buyers
Population in trade area × category penetration rate
SAM
Estimated buyers × average annual category spend
Relative competitor strength
Competitor review share inside category
Realistic SOM
SAM × realistic capture share

Worked Example

This example is illustrative. Replace it with a real scrape, sourced penetration rate, and real spend input before using it in a client report.

Metric
Value
Competing studios in a 12-minute drive-time area
9
Total category review share pool
100%
Top competitor share of voice
34%
New entrant realistic year-one share of voice
6–8%
Population in trade area
38,500
Estimated category penetration
6%
Estimated buyers
2,310
Average annual category spend
$900
SAM
$2,079,000
Realistic SOM, weighted not flat split
$125,000–$166,000
Flat 1/9 split for comparison
About $231,000

The flat split makes the market look bigger than the first-year capture is likely to be.

The weighted SOM is more conservative because it reflects competitor strength.

Bar chart showing Austin fitness studios ranked by review share of voice
Public Google Maps business data was collected with Outscraper, then organized with ChatGPT to calculate review-based share of voice. In this Austin fitness studio sample, the top listing holds about 10.3% of review visibility, not revenue.
See What Each Google Maps Business Record Can Include.

Review the available fields before building your local market model.

Step 6: Compare Markets Before Picking One

A single local market estimate is useful, but comparing two or three trade areas is stronger. The same model can show which area has more realistic room to enter.

The problem with one-market analysis is that it has no reference point.

A market with 12 competitors may look crowded until another nearby market has 35 competitors.

A market with low review volume may look weak until you see that every competitor in the category has low review volume.

A market with fewer competitors may still be difficult if one player dominates local visibility.

Use the same model across each candidate area.

Metric
Area A
Area B
Area C
Competitor count
9
14
7
Population
38,500
52,000
31,000
Top competitor review share
34%
18%
51%
Category penetration
6%
6%
6%
SAM
$2.1M
$2.8M
$1.7M
Realistic first-year SOM
$130K–$170K
$210K–$280K
$60K–$90K

Area C has fewer competitors, but one dominant competitor controls visibility.

Area B has more competitors, but the market is more fragmented.

Area A may be acceptable, but it may not be the strongest choice.

The fix is to compare markets before making the decision.

The goal is not to make the number look bigger.

The goal is to choose the market with the clearest path to capture share.

Where This Method Still Breaks

This method breaks when teams treat estimates as facts, use the wrong boundary, or skip the demand input. Public business data improves the supply-side estimate, but it does not remove the need for judgment.

The biggest risk is false precision.

A spreadsheet can make a weak assumption look scientific.

That does not mean the assumption is good.

Here are the failure points to check before using the number:

Mistake
Why It Breaks the Estimate
Better Fix
Using a radius instead of drive time
Counts businesses outside the real customer area
Use drive time or a carefully drawn trade boundary
Treating reviews as revenue
Review behavior varies by category
Use reviews only for relative strength
Guessing penetration rate
One assumption can swing the entire SAM
Use a trade report, internal benchmark, or clearly labeled estimate
Splitting SOM evenly
Competitors are not equally strong
Weight capture share by local visibility
Ignoring closed listings
Inflates supply
Filter by business status
Not refreshing data
Local markets change
Re-pull before final decision

The fix is to label each number clearly:

  • observed public data
  • sourced demographic data
  • trade report input
  • internal benchmark
  • estimate

That makes the final number more useful and more honest.

How Outscraper Fits in the Market Sizing Workflow

Outscraper helps with the local business data layer of market sizing. It does not replace census data, trade reports, or business judgment.

Its role is to make the supply side faster and cleaner.

Instead of manually copying businesses from Google Maps, Outscraper helps collect structured business records by category and location.

For this workflow, the useful Outscraper pages are:

The workflow is:

Define trade area → collect business data → rank competitors → add demand inputs → calculate SAM → weight SOM → compare markets

That is more defensible than guessing from a national average.

It is also more practical than manually copying every competitor into a spreadsheet.

Final Takeaway

Sizing a local market with public business data is not about finding one perfect number.

It is about replacing guesswork with a defensible range.

Start with the trade area.

Pull the competitor set.

Use reviews for relative strength, not revenue.

Add population, income, category penetration, and spend.

Calculate SAM.

Weight SOM based on competitor strength.

Then compare markets before making the decision.

The number will still have assumptions.

But the assumptions will be visible.

That is what makes the estimate useful.

A local market size estimate should help someone decide what to do next:

enter the market, avoid the market, compare another territory, or collect better data.

That is the point.

Not a bigger number.

A better decision.

Want to build the supply side of your local market estimate first?

Use Outscraper to pull competitor records, ratings, reviews, websites, phone numbers, and location data before you calculate opportunity.

Frequently Asked Questions

Most frequent questions and answers

You size a local market by defining a trade area, counting competitors, adding population and income data, estimating category penetration, calculating serviceable available market, and weighting realistic share by competitor strength.

Public business data such as business name, category, address, rating, review count, website, phone number, business status, and location can help map local supply and compare competitor strength.

Google review counts should not be used as direct market demand or revenue. They are better used as a relative visibility signal within the same category and trade area.

A radius is often too simple because customers travel by roads, time, traffic, and convenience. A drive-time boundary usually gives a better trade area for local market sizing.

SAM is the serviceable available market inside the trade area. SOM is the realistic share of that market a business can capture after considering competitor strength, visibility, and entry position.