---
type: method
slug: market-sizing-tam-sam-som
title: "Size a market (TAM, SAM, SOM)"
category: "Business Strategy & Planning"
subcategory: "Market & industry research"
level: intermediate
source: https://deepstoryresearch.com/method/market-sizing-tam-sam-som
publisher: Deepstory Research
---

> **How to use this file:** attach it to ChatGPT, Claude, Gemini or Copilot (or paste the prompt section), replace every [PLACEHOLDER] with your details, and add any data or Deepstory evidence files the method needs.

## When to use this method
- You need a credible market size for a pitch deck or business plan.
- You want to check whether a niche is big enough to be worth pursuing.

## Prompt

# Size a market (TAM, SAM, SOM)
Method by Deepstory Research: deepstoryresearch.com/method/market-sizing-tam-sam-som

You are a market-sizing specialist who has built models for venture investors. Follow the method below step by step. Goal: A top-down and bottom-up market size with TAM, SAM and SOM, reconciled and sensitivity-tested.

## My inputs
- Product or service: [PRODUCT_OR_SERVICE]  (example: B2B invoice-financing app)
- Target customer: [TARGET_CUSTOMER]  (example: SMEs with 10–200 staff)
- Geography: [GEOGRAPHY]  (example: India)
- Pricing: [PRICING]  (example: 1.5% fee per invoice)

Before you start: if any input above is still in [BRACKETS] or missing, ask me for it in one short numbered list and wait. Do not guess. If I attached files (data, briefs, Deepstory evidence files), treat them as the primary source.

## Steps to follow
1. Restate the product, customer and geography in one sentence and list what you assume.
2. Top-down: start from a published total (industry revenue or population) and narrow with explicit percentages.
3. Bottom-up: number of target customers × adoption × price × frequency.
4. Define TAM, SAM (reachable with this model and channel) and SOM (realistic 3–5 year share).
5. Reconcile the two approaches and explain any gap larger than 30%.
6. Run a sensitivity table on the two assumptions that move the answer most.
7. List the data you would buy or collect to replace the weakest assumption.

## Deliver the output in this structure
- Assumptions table (value, source, confidence)
- Top-down calculation
- Bottom-up calculation
- TAM / SAM / SOM summary
- Sensitivity table
- Data gaps to close

## Quality rules
- Every number is labelled FACT, ESTIMATE or ASSUMPTION.
- Units and currency stated on every line.
- SOM must be justified by channel capacity, not a flat "1% of the market".
- Label every number as FACT (with source and date), ESTIMATE (show the calculation) or ASSUMPTION.
- If a Deepstory evidence file is attached, use its figures as the reference values and cite its source references; tag claims that are not from it as [UNVERIFIED].
- End with: the 3 assumptions that matter most, what would change the answer, and the single best next step.

## Evidence you can attach
- E-Commerce Share of US Retail: https://deepstoryresearch.com/data/us-ecommerce-share (AI context file: https://deepstoryresearch.com/context/us-ecommerce-share.md)
- Global EV Adoption: https://deepstoryresearch.com/data/global-ev-adoption (AI context file: https://deepstoryresearch.com/context/global-ev-adoption.md)
- UPI vs Visa & Mastercard: India’s Payments Rewiring: https://deepstoryresearch.com/data/upi-vs-cards (AI context file: https://deepstoryresearch.com/context/upi-vs-cards.md)
- Six-Economy Macro Baseline: https://deepstoryresearch.com/data/global-macro-baseline (AI context file: https://deepstoryresearch.com/context/global-macro-baseline.md)

---
Deepstory methods are process guidance for AI tools. Review AI output before relying on it; legal, tax, medical and investment matters need a qualified professional.