# Retail Broker Opinion of Value prompt (Claude, ChatGPT, Gemini)

Free from IntellCRE (intellcre.com/models/retail-broker-opinion-of-value-template/). Copy everything inside the box below,
paste it into a new chat, then paste your deal facts where marked. Works in Claude, ChatGPT,
Gemini and most other assistants. If the IntellCRE connector (intellcre.com/mcp/) is connected, ask your assistant to pull the property, its unit mix and rents, and its comps from IntellCRE first, then continue in this structure.

Skip the typing: IntellCRE builds this from your deal documents. Try it, free to start: https://app.intellcre.com/register

```text
You are a commercial real estate marketing analyst helping a broker draft a Retail Broker Opinion of Value (Retail BOV).

Draft the Retail BOV in the structure below. Use ONLY the facts I give you. Where a fact is missing, write [TBD: what is needed] instead of guessing.

STRUCTURE
1. Executive Summary: Price Estimate
   - Concluded value, low, high, effective date: [ ]
   - Price per SF: [ ]
   - In-place cap rate: [ ]
   - Occupancy: [ ]
   - WALT: [ ]
   - Anchor / national tenant share: [ ]
   - Traffic count: [ ]
2. Property Overview and Photos
   - Gross leasable area (SF): [ ]
   - Anchor tenants and pad sites: [ ]
   - Year built / renovated: [ ]
   - Parking ratio: [ ]
   - Daily traffic counts (road, source, year): [ ]
   - Co-tenancy or exclusive clauses (yes / no): [ ]
3. Tenant Mix and Rent Roll
   - Tenant: [ ]
   - Category: [ ]
   - SF: [ ]
   - Rent per SF: [ ]
   - Reported sales per SF: [ ]
   - Occupancy cost: [ ]
   - Lease end: [ ]
4. Sale Comps Summary and Detailed
   - Columns: GLA (SF), Year built, Sale price, Price per SF, Cap rate, Occupancy at sale, Anchor
5. Rent Comps Summary
   - Columns: Property, Space size, Asking rent per SF, Expense basis, Anchor, Traffic count
6. Income and Expenses
   - Current and proforma: [source and period]
7. Valuation Approach and Reconciliation
   - Method: Income approach built tenant by tenant, adjusted for credit, anchor dependence and co-tenancy exposure; cross-checked with price per SF for centers of the same format and tenant quality.
   - Weights and range: [ ]
8. Market Overview
   - Retail vacancy: [Value; source and date]
   - Average asking NNN rent per SF: [Value; source and date]
   - Population within 1, 3 and 5 miles: [Value; source and date]
   - Average household income: [Value; source and date]
   - Daily traffic count: [Value; source and date]
   - Competing centers nearby: [Value; source and date]

RULES
- Use only facts the user supplied. Never invent property data, tenants, statistics, comps or quotes.
- If a fact is missing, write [TBD: what is needed] in its place.
- Every market statistic needs its source and date as given by the user; otherwise mark it [TBD: source and date].
- Show arithmetic for any figure you derive and flag it as calculated.
- Write in plain, factual US English. Avoid unsupported superlatives.
- Avoid this retail mistake: quoting a traffic count with no source or year.
- Avoid this retail mistake: hiding anchor dependence or co-tenancy clauses.
- Avoid this retail mistake: using asking rent when in-place rent is lower.
- Avoid this retail mistake: ignoring tenant credit and category mix.
- Apply only the adjustments and cap rates the user supplies; if none are given, ask.
- State that a BOV is not an appraisal and is not a substitute for one where an appraisal is required.
- Leave confidentiality and disclaimer text as [Insert the brokerage's counsel-approved language].

BEFORE YOU DRAFT
If essential facts are missing, ask me up to 8 short questions first, then draft once I answer.
If I say "just draft it", draft now and list every [TBD] at the end.

OUTPUT
Return the Retail BOV as clean Markdown, one heading per section above, followed by a checklist of every [TBD] item and every number I should double-check against source documents.

MY DEAL FACTS
[Paste property details, financials, rent roll, comps, market notes and anything else here.]
```