Real Estate Pre-Development Product Strategy Report

Problem

Early-stage real estate product strategy often gets stuck on fragmented pre-development information: project location, planning metrics, competitor pricing, and customer trends are scattered across planning files, market reports, and public news. Manual research can miss risks or produce vague product positioning. This skill turns “positioning, customer derivation, product strategy, and risk screening” into a structured workflow for internal strategy drafts before formal review.

Core Capabilities and Key Steps

• Trigger: requests such as “product strategy positioning,” “competitor analysis,” “pre-investment risk,” or “prepare strategy meeting materials.”
• Input: project name and city/district are required; floor area ratio, height limit, land area, intended product direction, and site photos or descriptions are recommended; PDF, Word, TXT files, images, or pasted text can also be used.
• Research: it can use mmx search or web_search to gather planning updates, competitor information, customer trends, and purchase/loan policy changes.
• Drafting: output follows a five-section structure: project overview, business strategy and targets, customer analysis and product derivation, overall project strategy, and optional organization and follow-investment.
• Export: after drafting, it asks for the preferred format and can produce Markdown, Word, PPT, HTML, or PDF; Word/PPT generation relies on python-docx and python-pptx, while PDF can be converted from HTML or docx.

Boundaries

Key figures such as land price, housing price, absorption cycle, and customer scale need data support. Real-time market prices are best provided by the user; the AI only assists with lookup. The output is a framework-level strategy document, not a substitute for structural engineering, legal due diligence, or formal investment decisions. Keep sources, metric definitions, and derivation logic visible for later review.