Market sizing with explicit assumptions

Estimate TAM, SAM and SOM using bottom-up and top-down methods, with every assumption listed and a sensitivity range.

Change note: Initial version

Prompt

Estimate the market size for {{offer}} in {{geography}}.

Customer definition: {{customer}}
Revenue per customer per year: {{price}}
Data I already have: {{data}}

Do the work in this order:
1. **Customer definition**: define the buyer precisely and state what you exclude.
2. **Bottom-up estimate**: number of target customers x realistic adoption x annual revenue per customer. Show each step as a labelled line with the number and the reason for it.
3. **Top-down cross-check**: start from a broader known market or spend category and narrow it with percentages. Show each step.
4. **TAM, SAM, SOM**: give a figure for each. Define SOM for a {{timeframe}} horizon, assuming a small team and modest marketing.
5. **Assumption register**: a table listing every assumption, your confidence (high/medium/low), the likely direction of error, and the cheapest way I could verify it.
6. **Sensitivity**: low, base and high scenarios, and the two assumptions that move the answer most.
7. **Sanity check**: compare the result with known comparable companies or spend, and say whether it passes.

Rules: label every number as "given", "estimated" or "recalled (verify)". Never present a recalled statistic as verified. Show the arithmetic and round sensibly.

Variables

• {{offer}}Product or servicetextrequired

  Default: an online platform for booking certified home energy audits

• {{geography}}Geographytextrequired

  Default: United States

• {{customer}}Customer definitiontextrequired

  Default: owners of single-family homes built before 2000 who may do energy upgrades

• {{price}}Revenue per customer per yeartextrequired

  Default: $350 per audit, about one audit per household every 5 years

• {{data}}Data you already havelong

  Default: About 80 million single-family homes in the US (recalled); roughly half were built before 2000.

• {{timeframe}}SOM horizonselectrequired

  Options: 1 year, 3 years, 5 years

  Default: 3 years

Example output

**Customer:** owners of pre-2000 single-family homes in the US; rentals and condos excluded.

**Bottom-up**
- Single-family homes: 80M (recalled, verify)
- Built before 2000, about 50%: 40M (estimated)
- Owner-occupied, about 80%: 32M (estimated)
- Likely to audit within 5 years, 15%: 4.8M homes (estimated)
- 4.8M x $350 = $1.68B over 5 years, or about $336M per year

**Top-down check:** US residential energy-efficiency services spend is in the tens of billions per year (recalled, verify). If audits are 1-2% of it, that gives roughly $300-600M. Consistent with the bottom-up figure.

**TAM / SAM / SOM**
- TAM: about $336M per year.
- SAM: the roughly 25% of homes in states with strong rebates, about $84M per year.
- SOM at 3 years: 1.5% of SAM, about $1.3M per year.

| Assumption | Confidence | Error direction | Verify by |
|---|---|---|---|
| 15% will audit within 5 years | Low | Probably high | Survey 200 owners |
| $350 average price | Medium | Either | Collect 10 local quotes |
| 25% of homes in rebate states | Medium | Probably high | Check state programme lists |

**Sensitivity:** low $170M, base $336M, high $520M. The intent rate and audit frequency move the result most.

**Sanity check:** passes; consistent with the scale of existing audit marketplaces (verify).

Notes

Labelling every figure as given, estimated or recalled keeps the model from passing off remembered statistics as facts. The assumption register tells you exactly which numbers to go and verify first.