electricsheepafrica/africa-synth-retail-and-ecommerce-email-marketing-performance-data-nigeria

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

Email Marketing Performance Data

Dataset Description

Comprehensive email marketing performance data for Nigerian retail and e-commerce analysis

Dataset Information

• Category: Marketing and Engagement
• Industry: Retail & E-Commerce
• Country: Nigeria
• Format: CSV, Parquet
• Rows: 500,000
• Columns: 12
• Date Generated: 2025-10-06
• Location: data/email_marketing_performance_data/
• License: GPL

Schema

Column	Type	Sample Values
email_id	String	EMAIL0000000
campaign_name	String	Email_Campaign_Promo
send_date	String	2024-05-10
subject_line	String	Suggest society mind already poor.
emails_sent	Integer	25421
emails_delivered	Integer	24620
emails_opened	Integer	4488
unique_clicks	Integer	935
unsubscribes	Integer	30
open_rate	Float	0.1765
click_through_rate	Float	0.2083
bounce_rate	Float	0.0404

Sample Data

    email_id           campaign_name  send_date                           subject_line  emails_sent  emails_delivered  emails_opened  unique_clicks  unsubscribes  open_rate  click_through_rate  bounce_rate
EMAIL0000000    Email_Campaign_Promo 2024-05-10     Suggest society mind already poor.        25421             24620           4488            935            30     0.1765              0.2083       0.0404
EMAIL0000001 Email_Campaign_Reminder 2024-06-06 However hundred stuff wait sport land.        49838             47582          12177           2996           446     0.2443              0.2460       0.0432
EMAIL0000002    Email_Campaign_Promo 2024-08-21  Certainly brother it receive similar.        57139             55319          22465           3705           315     0.3932              0.1649       0.0198

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/email_marketing_performance_data/nigerian_retail_and_ecommerce_email_marketing_performance_data.csv

Parquet (Recommended)

data/email_marketing_performance_data/nigerian_retail_and_ecommerce_email_marketing_performance_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_email_marketing_performance_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/email_marketing_performance_data/nigerian_retail_and_ecommerce_email_marketing_performance_data.csv')

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

PyArrow

import pyarrow.parquet as pq

# Load Parquet
table = pq.read_table('data/email_marketing_performance_data/nigerian_retail_and_ecommerce_email_marketing_performance_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_email_marketing_performance_data_2025,
  title={Email Marketing Performance Data},
  author={Electric Sheep Africa},
  year={2025},
  publisher={Hugging Face},
  howpublished={\url{https://huggingface.co/datasets/electricsheepafrica/nigerian-retail-email-marketing-performance-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.