electricsheepafrica/africa-synth-retail-and-ecommerce-cross-channel-sales-data-nigeria

⚠️ Synthetic dataset — Parameterized from published SSA literature, not real observations. Not suitable for empirical analysis or policy inference.

Cross Channel Sales Data

Dataset Description

Comprehensive cross channel sales data for Nigerian retail and e-commerce analysis

Dataset Information

• Category: Sales and Transactions
• Industry: Retail & E-Commerce
• Country: Nigeria
• Format: CSV, Parquet
• Rows: 50,000
• Columns: 10
• Date Generated: 2025-10-06
• Location: data/cross_channel_sales_data/
• License: GPL

Schema

Column	Type	Sample Values
transaction_id	String	XCH0000000
customer_id	String	CUST585351
transaction_date	String	2024-05-19
online_channel	String	Jiji
offline_store	String	Game
total_online_spend_ngn	Float	98449.89
total_offline_spend_ngn	Float	186482.4
preferred_channel	String	both
cross_channel_purchases	Integer	1
city	String	Kano

Sample Data

transaction_id customer_id transaction_date online_channel    offline_store  total_online_spend_ngn  total_offline_spend_ngn preferred_channel  cross_channel_purchases     city
    XCH0000000  CUST585351       2024-05-19           Jiji             Game                98449.89                186482.40              both                        1     Kano
    XCH0000001  CUST515361       2024-02-01          Jumia Computer Village               433939.34                131506.42            online                        7 Abeokuta
    XCH0000002  CUST206074       2024-03-22          Jumia             Slot               482478.05                134385.72            online                       17  Onitsha

Use Cases

• Data analysis and insights
• Machine learning model training
• Business intelligence
• Research and education
• Predictive analytics

Nigerian Context

This dataset incorporates authentic Nigerian retail and e-commerce characteristics:

E-Commerce Platforms

• Jumia (35% market share) - Leading marketplace
• Konga (25% market share) - Major competitor
• Jiji (20% market share) - Classifieds platform
• PayPorte, Slot, and other platforms

Physical Retail

• Shoprite, Spar, Game - Major supermarket chains
• Slot, Pointek - Electronics retailers
• Mr Price - Fashion retail
• Traditional markets: Balogun Market, Computer Village

Payment Methods

• Cash on Delivery (45%) - Most popular
• Bank Transfer (25%)
• Debit Card (15%)
• USSD (8%)
• Mobile Money (5%)
• Credit Card (2%)

Logistics & Delivery

• GIG Logistics - Nationwide coverage
• Kwik Delivery - Fast urban delivery
• DHL, FedEx - International and express
• Red Star Express - Nationwide courier
• Local dispatch riders

Geographic Coverage

Major Nigerian cities including:

• Lagos - Commercial capital, highest retail density
• Abuja - Federal capital, high e-commerce penetration
• Kano - Northern commercial hub
• Port Harcourt - Oil city, strong purchasing power
• Ibadan - Large urban market
• Plus 10+ other major cities

Products & Categories

• Electronics: Tecno, Infinix, Samsung phones; laptops, TVs
• Fashion: Ankara fabric, Agbada, Kaftan, sneakers
• Groceries: Rice (50kg bags), Garri, Palm Oil, Indomie
• Beauty: Shea butter, Black soap, hair extensions
• Home: Generators, inverters, solar panels

Currency & Pricing

• Currency: Nigerian Naira (NGN, ₦)
• Exchange Rate: ~₦1,500/USD
• Price Ranges: Realistic Nigerian market prices
• Time Zone: West Africa Time (WAT, UTC+1)

File Formats

CSV

data/cross_channel_sales_data/nigerian_retail_and_ecommerce_cross_channel_sales_data.csv

Parquet (Recommended)

data/cross_channel_sales_data/nigerian_retail_and_ecommerce_cross_channel_sales_data.parquet

Nigerian Retail and E-Commerce - Loading the Dataset

Hugging Face Datasets

from datasets import load_dataset

# Load dataset
dataset = load_dataset("electricsheepafrica/nigerian_retail_and_ecommerce_cross_channel_sales_data")

# Convert to pandas
df = dataset['train'].to_pandas()

print(f"Loaded {len(df):,} rows")

Pandas (Direct)

import pandas as pd

# Load CSV
df = pd.read_csv('data/cross_channel_sales_data/nigerian_retail_and_ecommerce_cross_channel_sales_data.csv')

# Load Parquet (recommended for large datasets)
df = pd.read_parquet('data/cross_channel_sales_data/nigerian_retail_and_ecommerce_cross_channel_sales_data.parquet')

PyArrow

import pyarrow.parquet as pq

# Load Parquet
table = pq.read_table('data/cross_channel_sales_data/nigerian_retail_and_ecommerce_cross_channel_sales_data.parquet')
df = table.to_pandas()

Data Quality

• ✅ Realistic Distributions: Based on Nigerian retail patterns
• ✅ No Missing Critical Fields: Complete core data
• ✅ Proper Data Types: Appropriate types for each column
• ✅ Consistent Naming: Clear, descriptive column names
• ✅ Nigerian Context: Authentic local characteristics
• ✅ Production Scale: Suitable for real-world applications

Ethical Considerations

• This is synthetic data generated for research and development
• No real customer data or personally identifiable information
• Designed to reflect realistic patterns without privacy concerns
• Safe for public use, testing, and education

License

GPL License - General Public License

This dataset is free to use for:

• Research and academic purposes
• Commercial applications
• Educational projects
• Open source development

Citation

@dataset{nigerian_retail_cross_channel_sales_data_2025,
  title={Cross Channel Sales Data},
  author={Electric Sheep Africa},
  year={2025},
  publisher={Hugging Face},
  howpublished={\url{https://huggingface.co/datasets/electricsheepafrica/nigerian-retail-cross-channel-sales-data}}
}

Related Datasets

This dataset is part of the Nigerian Retail & E-Commerce Datasets collection, which includes 42 datasets covering:

• Customer & Shopper Data
• Sales & Transactions
• Product & Inventory
• Marketing & Engagement
• Operations & Workforce
• Pricing & Revenue
• Customer Support
• Emerging & Advanced Technologies

Browse all datasets: https://huggingface.co/electricsheepafrica

Updates & Maintenance

• Version: 1.0
• Last Updated: 2025-10-06
• Maintenance: Active
• Issues: Report via Hugging Face discussions

Contact

For questions, feedback, or collaboration:

• Hugging Face: electricsheepafrica
• Issues: Open a discussion on the dataset page
• General Inquiries: Via Hugging Face profile

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Part of the Nigerian Industry Datasets Initiative
Building comprehensive, authentic datasets for African markets.