electricsheepafrica/africa-synth-retail-and-ecommerce-loyalty-program-activity-data-nigeria

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

Loyalty Program Activity Data

Dataset Description

Comprehensive loyalty program activity data for Nigerian retail and e-commerce analysis

Dataset Information

• Category: Marketing and Engagement
• Industry: Retail & E-Commerce
• Country: Nigeria
• Format: CSV, Parquet
• Rows: 400,000
• Columns: 9
• Date Generated: 2025-10-06
• Location: data/loyalty_program_activity_data/
• License: GPL

Schema

Column	Type	Sample Values
activity_id	String	LOYAL0000000
customer_id	String	CUST496720
activity_date	String	2024-01-08
activity_type	String	bonus_points
points_change	Integer	-2122
current_points_balance	Integer	47485
tier	String	silver
order_id	String	ORD3487404
reward_redeemed	String	discount

Sample Data

 activity_id customer_id activity_date activity_type  points_change  current_points_balance   tier   order_id reward_redeemed
LOYAL0000000  CUST496720    2024-01-08  bonus_points          -2122                   47485 silver       None        discount
LOYAL0000001  CUST331246    2024-09-02  bonus_points           -522                   11963 bronze ORD3487404            None
LOYAL0000002  CUST921278    2024-08-02 points_earned          -1109                   29282 bronze       None   free_shipping

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/loyalty_program_activity_data/nigerian_retail_and_ecommerce_loyalty_program_activity_data.csv

Parquet (Recommended)

data/loyalty_program_activity_data/nigerian_retail_and_ecommerce_loyalty_program_activity_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_loyalty_program_activity_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/loyalty_program_activity_data/nigerian_retail_and_ecommerce_loyalty_program_activity_data.csv')

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

PyArrow

import pyarrow.parquet as pq

# Load Parquet
table = pq.read_table('data/loyalty_program_activity_data/nigerian_retail_and_ecommerce_loyalty_program_activity_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_loyalty_program_activity_data_2025,
  title={Loyalty Program Activity Data},
  author={Electric Sheep Africa},
  year={2025},
  publisher={Hugging Face},
  howpublished={\url{https://huggingface.co/datasets/electricsheepafrica/nigerian-retail-loyalty-program-activity-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

---

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