Datasets:

GencoDiv
/

gcc-ramadan-retail-patterns

license: mit
task_categories:
  - time-series-forecasting
  - tabular-regression
language:
  - en
tags:
  - retail
  - demand-forecasting
  - gcc
  - e-commerce
  - gulf-retail
  - synthetic
  - agentic-commerce
  - ocg-dubai
size_categories:
  - 100K<n<1M

GCC Retail Demand Forecasting Dataset v2

Built by OCG Dubai — Agentic Commerce APIs for the GCC

Dataset Description

A synthetic dataset for retail demand forecasting across 6 Gulf Cooperation Council (GCC) countries and 12 product categories. Based on real GCC market research with country-specific revenue shares, seasonal events, and shopping festivals. Gregorian calendar with event flags — no Hijri dependency.

Dataset Summary

Total Records: 210,384
Date Range: 2018-01-01 to 2025-12-31 (8 years)
Countries: UAE, KSA, Qatar, Kuwait, Bahrain, Oman
Categories: 12 (fashion_apparel, electronics_media, groceries_fmcg, beauty_cosmetics, home_furniture, luxury_goods, jewelry_watches, health_wellness, food_dining, sports_outdoor, toys_kids, travel_entertainment)

Features

Feature	Type	Description
date	string	Gregorian date (YYYY-MM-DD)
country	string	GCC country
category	string	Product category (12 types)
demand_index	float	Normalized demand (0-100)
temperature	float	Temperature in Celsius
day_of_week	int	Day of week (0=Monday)
month	int	Gregorian month
year	int	Gregorian year
is_weekend	bool	GCC weekend (Friday/Saturday)
is_ramadan	bool	Ramadan period
ramadan_week	int	Week within Ramadan (0-4)
is_eid_fitr	bool	Eid al-Fitr period
is_eid_adha	bool	Eid al-Adha period
is_shopping_festival	bool	Regional shopping festival
is_white_friday	bool	White Friday / Black Friday sales
is_national_day	bool	Country national day
is_back_to_school	bool	Back-to-school season

Product Categories

Based on actual GCC e-commerce revenue data:

Category	Revenue Share	Notes
fashion_apparel	25-38%	Largest across GCC
electronics_media	19-34%	Second largest
groceries_fmcg	15-30%	Fastest growing
beauty_cosmetics	5-10%	Social media driven
home_furniture	3-8%	Steady demand
luxury_goods	2-7%	Significant in UAE/Qatar
jewelry_watches	3-5%	Strong in UAE/KSA
health_wellness	2-3%	Growing post-COVID
food_dining	3-4%	Major F&B market
sports_outdoor	1-2%	Vision 2030 growth
toys_kids	1-2%	Seasonal spikes
travel_entertainment	1-2%	Tourism driven

Market Data

Country	Market Size (USD)	Key Events
UAE	$114B	Dubai Shopping Festival, Dubai Summer Surprises
KSA	$161B	Riyadh Season, Saudi National Day
Qatar	$19.5B	Shop Qatar, Qatar National Day
Kuwait	$22.6B	Hala February
Bahrain	$8.5B	F1 Grand Prix, National Day
Oman	$12.0B	Khareef Festival, National Day

Demand Patterns

Ramadan: Progressive increase (20-100% above baseline), peaks in weeks 3-4
Eid al-Fitr/Adha: Demand spikes for fashion, gifts, food
Shopping Festivals: DSF (UAE Jan-Feb), Riyadh Season (Oct-Mar), White Friday (Nov)
Back to School: August-September boost for kids, electronics
National Days: Country-specific celebration spending
Temperature: Summer drives indoor shopping, winter boosts outdoor/tourism

Usage

from datasets import load_dataset

dataset = load_dataset("GencoDiv/gcc-ramadan-retail-patterns")
df = dataset["train"].to_pandas()

# Filter by country
uae_data = df[df["country"] == "UAE"]

# Ramadan analysis
ramadan_data = df[df["is_ramadan"] == True]

Model: GencoDiv/ramadan-demand-forecaster — XGBoost model trained on this dataset (R²=0.992)

About OCG Dubai

OCG Dubai builds Agentic Commerce APIs for the GCC market — demand forecasting, halal compliance, smart baskets, and dynamic pricing calibrated for regional consumer behavior.

Website: ocg-dubai.ae

Citation

@dataset{gcc_retail_v2_2026,
  title={GCC Retail Demand Forecasting Dataset v2},
  author={OCG Dubai},
  year={2026},
  url={https://ocg-dubai.ae},
  note={Synthetic dataset based on GCC market research}
}