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Case Study · MENA Ride-Hailing Leader · Analytics Product 07 / 07

Geospatial Intelligence

Territory decisions, made visible: polygon zone maps for Jeddah and Riyadh built from real district-composition files, metric-selectable heatmap coloring, and 3-level hierarchical zone performance tables.

Geo AnalyticsPolygon MappingTableau SQLZone PerformanceKSA Markets
product scorecard — structural factsproduction
3
cities — Jeddah, Riyadh, Dammam tabs
9+
polygon zone groups per city map
3
levels in the zone hierarchy tables
1
metric selector recolors the whole map

Note on numbers: no figure from inside a client dashboard is presented here as an achievement. Published screenshots have absolute figures blurred.

01The Business Problem

City-level averages hide everything territory managers need: which districts perform, where coverage gaps sit, which zones deserve investment. Zone-level performance was effectively invisible — decisions about physical territory were being made from spreadsheets with no map behind them.

The goal: put the marketplace on an actual map — real district boundaries, colored by any metric the operator selects.

02My Role

Sole analyst on the product: building the polygon zone maps from district composition files, wiring the metric-selectable coloring, and designing the hierarchical zone tables that sit beside the maps.

03What I Built

KSA Discovery Zone Mapping

Interactive polygon maps of Jeddah and Riyadh, each district grouped into named zones (Central A, North B, Airport…) with real geographic boundaries — and a companion table documenting exactly which districts compose each zone group, inside the dashboard.

Zone Analysis — performance heatmaps

City maps colored by a selectable metric — pick booked orders, delivery fee, or AOV and the whole map recolors on a red-to-green gradient — beside a 3-level hierarchical table: zone group → district → totals.

Zone Performance Tables

Per-zone metrics side by side: live and active outlets, booked and delivered orders, express share, average delivery fee, AOV — with grand totals per city and per zone group.

Zone Contribution Views

Booking contribution and C/R tracked daily per named zone — down to individual malls and airport terminals — with directional coloring for trend reading.

04Signature Build Details

Zones defined from source files, not hand-drawn: the zone groups are built from real district composition files, and the district-to-zone mapping is documented inside the dashboard — territory definitions anyone can audit.
One selector, every metric: the map's coloring is driven by a metric selector — the same geography answers demand, pricing, and service-quality questions without rebuilding anything.
Map and table, never separated: every map ships with its hierarchical table — the visual for pattern-finding, the table for the exact numbers underneath.
Three cities, one architecture: Jeddah, Riyadh, and Dammam live as tabs of the same build — adding a city means adding data, not redesigning.

05KPIs Defined & Governed

Booked OrdersDelivered OrdersAOV Avg Delivery FeeExpress %Live / Active Outlets Zone Contribution %C/R by Zone

06Decisions Enabled

Territory managers saw zone-level performance on real boundaries instead of citywide averages.
Coverage and investment discussions started from a shared, auditable zone definition.
Daily zone contribution tables surfaced which specific locations moved the city's numbers.
SCREENSHOT SLOT
Jeddah polygon zone map + composition table
(blur all absolute figures)assets/geo-jeddah-zones.png

07Skills Demonstrated

Geo-spatial analyticsPolygon mapping Metric-selector UXHierarchical table design Territory data modelingAdvanced SQL
Mohamed Eltanbedawy · Business & Data Analyst — BI & Analytics
mohamed.tanbedawy@gmail.com · linkedin.com/in/tanbedawy