Market Sizing
Market sizing helps estimate the economic potential of an opportunity before launching a product or scaling an initiative.
It is not a full strategic framework, but a tool to support decisions around sales, growth, and go-to-market.
Top-Down Market Sizing
Components
Macro data
Population, GDP, number of businesses, revenue, production volumesSegmentation
Customer types, usage, geography, age, incomeEconomic value
Purchase frequency, average price per unit
Approach
Macro data: Start from broad top-level numbers.
Segmentation: Apply logical filters to narrow down to the target market.
Economic value:
Estimate market revenue.
The target market can be calculated in different ways depending on the context:
- customers × purchase frequency × price
- total industry revenue × target segment share
Penetration: Apply a penetration rate if needed.
Sanity check: Compare with real data or benchmarks to validate the result.
Example
Market: running shoes in Italy
Macro data
Population: 60M
Segmentation
Regular runners: 10%
Target market = 60M × 10% = 6M
Economic value
Purchase frequency: 1.5 pairs/year
Average price: €100
Market size = 6M × 1.5 × €100 = €900 M
Penetration
Penetration: 10%
Penetrated market = €900M × 10% = €90 M
Bottom-up Market Sizing
Components
Micro data
Units sold per store or channel, active customers, average orders, production capacityEconomic value
Average price per unit, purchase frequency, average order size, customer spendAggregation
Combine volumes or revenues across channels to estimate total market size
Approach
Micro data: Estimate data from the field (stores, customers, average orders, production).
Economic value:
Calculate revenue using unit prices and frequencies.
The market can be calculated via:
- number of customers × frequency × price
- units sold × price
- average orders × quantity per order × price
Aggregation: Sum all channels to obtain total market size
Penetration: Apply a penetration rate if needed.
Sanity check: Compare with real data or benchmarks to validate the result.
Example
Market: running shoes in Italy
Micro data
Physical retail
- Number of sporting goods stores: 1,500
- Average annual sales per store: 3,000 pairs
- Average price: €100
E-commerce
- Active online customers: 500,000
- Purchase frequency: 1.5 pairs/year
- Average price: €100
Economic value
Retail market: 1,500 × 3,000 × €100 = €450 M
E-commerce market: 500,000 × 1.5 × €100 = €75 M
Aggregation
Total estimated market = 450M + 75M = €525 M
Penetration
Penetration: 10%
Penetrated market = €525M × 10% = €52.5 M
