electricsheepafrica/african-streaming-consumption

---
license: cc-by-4.0
tags:
- entertainment
- streaming
- media
- sub-saharan-africa
- synthetic
- digital
- music
- video
- subscriptions
- mobile-money
size_categories:
- 10K<n<100K
task_categories:
- tabular-classification
- regression
pretty_name: African Streaming Consumption
language:
- en
- fr
---

# African Streaming Consumption Dataset

Synthetic dataset modeling streaming media consumption across 12 Sub-Saharan African countries, covering 8 major platforms and 3 scenarios (baseline, Netflix expansion, data affordability).

## Dataset Summary

| Property | Value |
|----------|-------|
| Countries | 12 |
| Platforms | 8 |
| Scenarios | 3 |
| Records per scenario | 10,000 |
| Total records (combined) | 30,000 |

## Countries

Nigeria, South Africa, Kenya, Ghana, Tanzania, Ethiopia, Uganda, Côte d'Ivoire, Senegal, DR Congo, Rwanda, Cameroon

## Platforms

- **Video:** Netflix, Showmax, iROKOtv, YouTube
- **Audio:** Spotify, Apple Music, Boomplay, Audiomack

## Scenarios

| Scenario | Description |
|----------|-------------|
| baseline | Current market conditions |
| netflix_expansion | 2x Netflix investment in Africa (80% more subs, 60% more MAU, 100% more revenue) |
| data_affordability | 40% more streaming hours, 50% more data consumption, 20% more MAU |

## Variables

| Variable | Type | Description |
|----------|------|-------------|
| record_id | int | Unique identifier |
| country | string | Country name |
| year | int | 2022-2025 |
| quarter | string | Q1-Q4 |
| platform | string | Streaming platform |
| content_type | string | movies, series, music, podcasts |
| subscriber_count_millions | float | Paid subscribers (millions) |
| monthly_active_users_millions | float | Monthly active users (millions) |
| avg_hours_per_user | float | Average monthly hours per user |
| local_content_share_pct | float | Percentage of local content consumed |
| revenue_usd_millions | float | Platform revenue in USD (millions) |
| arpu_usd | float | Average revenue per user (USD) |
| churn_rate_pct | float | Monthly churn rate (%) |
| mobile_streaming_pct | float | Percentage of streaming on mobile |
| data_consumption_gb_per_user | float | Monthly data consumption per user (GB) |
| content_language | string | Primary content language |
| genre_preference | string | Most popular genre |
| payment_method | string | mobile_money, card, or bundle |

## Market Characteristics

- **South Africa:** Showmax dominance in video streaming (higher local content share for Showmax)
- **Nigeria:** Nollywood-driven high local content share (55-80%) for movies and series
- **East Africa:** Swahili content prevalence, strong mobile money integration
- **Francophone Africa:** French content emphasis, emerging markets

## Methodology

Dataset is fully synthetic, generated with seeded randomness (seed=42). Country-specific parameters reflect estimated market conditions including GDP per capita, mobile penetration, and platform popularity. Scenario modifiers are deterministic multipliers applied to baseline distributions.

## License

CC-BY-4.0