tamensa06/UniHive-Africa-Revenue-Analysis

Comprehensive time series analysis of UniHive-Africa EdTech platform revenue. Uncovers seasonal patterns driven by academic calendar. ARIMA modeling forecasts optimal expansion timing. Transforms perceived failure into strategic growth roadmap for Nigerian universities. ## UniHive-Africa Revenue Analysis ### Comprehensive Time Series Analysis of an EdTech Platform in Nigeria #### 📌 Project Overview This project presents a comprehensive time series analysis of UniHive-Africa’s revenue performance from October 2023 to October 2025. The objective is to uncover hidden revenue patterns, diagnose perceived business decline, and provide data-driven expansion and launch timing strategies for Nigerian universities. Using academic-calendar-aware time series modeling (STL + ARIMA), the analysis reframes what initially appeared to be business failure into a predictable, sector-driven seasonal cycle, enabling confident strategic planning. #### 🏢 Company Background Mission UniHive-Africa believes every individual has the potential to succeed but lacks equal opportunity. The platform exists to bridge this gap by transforming how African students reinforce classroom learning. #### Vision To democratize academic success across Africa by providing scalable, curriculum-aligned digital learning tools for higher education institutions. #### 🎓 Product Description UniHive-Africa is an EdTech platform that enables students to: Reinforce classroom learning Practice course-specific questions Access assessments aligned with university curricula Content is tailored to each institution, ensuring relevance and adoption. #### 🚀 Current Status Pilot Institution: Federal University Lokoja Launch Date: October 2023 Operational Period Analyzed: October 2023 – October 2025 (25 months) Expansion Goal: Scale across Nigerian universities and eventually Africa ### ❗ Business Challenges 1. Revenue Volatility . Peak revenue: ₦92,700 (April 2024) . Revenue decline to ₦9,360 (October 2025) . Three months of near-zero sales (Oct–Dec 2024) 2. Lack of Pattern Understanding . Management lacked clarity on: . Whether revenue drops signaled failure . Drivers of high vs. low performance . Viability of the business model 3. Expansion Timing Uncertainty . …