Retail Site Intelligence

What it does

A seven-step funnel that mirrors a retail analyst's daily workflow, from a broker lead to a deal memo — every score fully inspectable (glass-box).

• Location — geocode + map + 10-min walking isochrone + BAFU flood check
• Market — BFS demographics, Kaufkraft, premium-environment signal
• Proximity — brand-aware OSM POI classification (sport / symbiose / competitor …)
• Footfall — amenity-richness Walk Score + transit access
• Site Score — weighted 0-100, flood penalty, sustainability adjustment
• Leasehold Pro-Forma — 5-yr DCF, NPV/IRR, occupancy-cost ratio
• Export — PDF site report, deal memo, PowerPoint overview
• Brand-neutral — swap one JSON config to retarget any retailer

Step 1 — Location & flood risk

Geocoded candidate with the BAFU surface-runoff hazard overlay and curated premium-hotel layer. Niederdorfstrasse 21 sits inside the Sihl/Limmat HQ100 flood perimeter.

Step 2 — Market overview

BFS demographics for the municipality plus a live premium-environment signal — purchasing power, age structure, and curated 5★/4★ hotels in radius.

Step 3 — Proximity intelligence

One OSM query, brand-aware classification into sport / symbiose / premium / competitor / negative / partner, with curated overrides for stores OSM under-tags.

Step 4 — Footfall & accessibility

Amenity-richness Walk Score (Pandana-free, log-saturated so central locations differentiate realistically) plus transit access.

Step 5 — Glass-Box Site Score

Every dimension normalised 0-100 before weighting, with flood penalty and Bechtiger-2024 / ESI sustainability adjustment applied transparently.

Step 6 — Leasehold Pro-Forma

A leasehold cashflow model (On leases, doesn't buy) — 5-year DCF with NPV / IRR / payback, Bear/Base/Bull scenarios, live sensitivity sliders, and retail KPIs (Occupancy Cost Ratio, Cash-on-Cash, Break-even sales).

Proximity layers (all 12)

Every analytical overlay is an independent, toggleable map layer. All twelve — each isolated over the baseline — captured at Niederdorfstrasse 21.

Run the interactive tool

The live app analyses any address — this static page only shows one. Open the hosted version (free tier: may take ~30 s to wake up) or run it locally:

git clone https://github.com/TStrathaus/retail-real-estate-site-intelligence.git
cd retail-real-estate-site-intelligence
python -m venv .venv && source .venv/bin/activate   # Windows: .venv\Scripts\activate
pip install -r requirements.txt
cp .env.example .env                                 # set NOMINATIM_USER_AGENT
streamlit run app.py

Launch live app View on GitHub Scoring methodology

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