AI Prompt Details
A practical, ready-to-use AI prompt designed to help you solve real business problems faster—with clear steps, proven frameworks, and immediate action.
Quick Suburb Scan (Research Brief + Evidence Checklist for Investors)
Get a structured suburb research brief that tells you exactly what to look up and what evidence matters.
Problem It Solves
Most investors research suburbs randomly and end up with biased, incomplete conclusions. This prompt produces a focused research brief and evidence checklist so your suburb analysis is faster, more consistent, and less likely to miss critical signals.
Evidence-First Research Brief
Tells you exactly what evidence to collect so suburb research is structured, fast, and repeatable.
Must-Have vs Nice-to-Have Checklist
Prevents shallow conclusions by enforcing minimum evidence requirements before deciding.
Tailored Red-Flag Library
Flags suburb-level risks relevant to your intent and property type to avoid blind spots.
Decision Template Rules
Gives a fill-in framework that converts evidence into a clear buy/avoid/monitor outcome.
AI Prompt Instructions
Act as a property market research assistant.
You will NOT invent facts or numbers.
Your job is to produce a suburb research brief + evidence checklist that I can execute.
Inputs:
A) Suburb + state/city:
[PASTE]
B) Investment intent (choose): growth | yield | balanced
C) Property type (choose): house | unit | townhouse
D) Hold period (years):
[PASTE]
Required output:
1) Suburb research brief (what to collect)
- Price movement: what metric(s) to pull and from where (examples: median, index, quarterly movement)
- Supply: listings trend, construction pipeline, approvals
- Demand: days on market, clearance rates (if relevant), enquiry proxy
- Demographics: income, household formation, renter/owner mix
- Infrastructure & jobs: major projects, employment centres
- Rental market: vacancy rate, rent trend, yield range
2) Evidence checklist (must-have vs nice-to-have)
- Must-have evidence (minimum 8 items)
- Nice-to-have evidence (minimum 6 items)
3) Red flags to watch (tailored)
- At least 10 suburb-level risks relevant to the property type and intent
4) One-page decision template (fill-in)
- “If evidence says X, then decision = Y” rules
Constraints:
- If you recommend data types, give examples of credible sources to use, but do not fabricate values.
- Keep it practical: I should be able to run this in 30–45 minutes.
Expected Outcome
A suburb research brief with an evidence checklist, tailored red flags, and a one-page decision template.
Implementation Journey
Source credible suburb data fast
Use Perplexity to collect credible references and links for the suburb (price trend indicators, listings/supply signals, rental/vacancy, demographics). Save the sources you’ll rely on.
15–25 minutesTurn sources into a structured brief
Use ChatGPT to paste your notes + links and format them into the research brief and evidence checklist sections exactly as required (no new numbers added).
10–15 minutesPackage into a one-page template
Use Notion AI to convert the decision template into a reusable page you can duplicate for every suburb you evaluate.
5–10 minutesPrompt Overview
Use this before deep dives—if the suburb fails 2–3 major red-flag checks early, you save hours of unnecessary analysis.
Best AI Tools for This Prompt (4)
Prompt Stack (3)
Suburb & Market Trend Analysis Stack (Research → Score → Decision-Grade Outlook)
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