This project delivers a fully interactive operational performance dashboard for PayPal's Middle East & Africa (MEA) business, analysing 768 transactions across 8 countries, 3 regions, and 4 payment categories from January 2023 to December 2024.
PayPal MEA grew Total Payment Volume (TPV) +9.7% YoY to $2.23B in 2024, generating $57.0M revenue and $14.2M net profit at a 21.0% average margin. The portfolio is structurally split, mature, high-profit GCC markets (28.5% avg margin) versus high-growth African markets led by Kenya (+22.4% YoY). Cross-border transactions generate 47.4% of all revenue despite representing only 34.9% of TPV.
Strategic direction: Invest aggressively in Kenya, optimise Egypt's unit economics, control BNPL risk, and make a decisive strategic decision on Jordan's viability.
PayPal's MEA regional leadership requires a monthly operational review that answers two questions simultaneously:
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How is the business performing operationally? : tracking TPV, revenue, profit, churn, and customer satisfaction across 8 diverse markets with very different profiles.
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Where should the business focus to grow? : identifying which markets have the most untapped potential, which are profitable but saturating, and which are generating volume without sustainable profit margins.
If leadership can't see the full picture, they might confuse a failing market with one that just needs more time to grow. This analysis solves that problem by showing exactly where to invest, where to optimize, and where to cut losses.
To deliver these insights, this project provides a complete strategic suite: an interactive dashboard that combines operational KPIs with market opportunity indicators, an executive presentation tailored for high-level decision-making, and a comprehensive report detailing the underlying unit economics.
The project follows a clean 3-layer analytics pipeline:
paypal-mea-operations-analysis/
├── analysis/
│ ├── paypal_mea_full_analysis.xlsx ← Main Excel workbook
│ ├── paypal_mea_analysis_report.pdf ← PDF export of analysis
│ └── excel_dashboard_overview.png ← Excel dashboard preview
│
├── presentation/
│ ├── paypal_mea_executive_presentation.pptx ← Editable slide deck
│ ├── paypal_mea_executive_presentation.pdf ← View-only slide deck
│ ├── 01_ppt_kpi.png
│ ├── 02_ppt_product_mix.png
│ ├── 03_ppt_risk_churn.png
│ └── 04_ppt_reco.png
│
├── data/
│ ├── paypal_mea_raw_data.csv ← Raw dataset (CSV)
│ └── paypal_mea_raw_data.xlsx ← Raw dataset (Excel)
│
├── docs/
│ ├── data_dictionary_&_naming_conventions.pdf ← Definitions & business rules
│ └── paypal_mea_data_architecture.png ← Data architecture diagram
│
├── LICENSE ← MIT License
└── README.md ← Project documentation
- Synthetic dataset built from publicly available MEA market data (World Bank, IMF, UAE Central Bank, SAMA, CBE reports)
- 768 rows × 39 columns: 8 countries × 24 months × 4 payment categories
- Calculated columns added to Working_Data tab:
| Column | Formula | Purpose |
|---|---|---|
revenue_per_user |
revenue_USD / active_users |
Revenue efficiency per customer |
net_profit_USD |
revenue_USD × (net_margin_pct / 100) |
True profitability per row |
growth_opportunity |
unbanked_pop_pct / market_share_pct |
Untapped market potential index |
cac_to_revenue |
customer_acquisition_cost / revenue_per_user |
Acquisition efficiency ratio |
retention_score |
100 - churn_rate_pct |
Positive framing of churn |
period |
YEAR & "-" & MONTH_NUM |
Sortable chronological key |
quarter |
Q1–Q4 derived from month_num |
Quarterly grouping |
month_label |
Jan 2023 format |
Clean chart axis labels |
| Analysis | Method | Business Question |
|---|---|---|
| Country Performance | Pivot aggregation (SUM + AVERAGE) | Which country drives the most volume and profit? |
| Growth Trends | 24-month time-series pivot + line chart | Is the business growing? Which region is accelerating? |
| Product Mix | Category decomposition + clustered column | Which product earns the most? Which is riskiest? |
| Profitability Matrix | Unit economics (CAC, margin, rev/user) | Which markets are genuinely profitable? |
| Market Opportunity | Custom opportunity score index | Where should PayPal invest next? |
| Risk Heatmap | Country × Category cross-tabulation | Which combinations are highest risk? |
- 6 pivot tables with conditional formatting (Red → Yellow → Green color scales)
- 6 charts built from helper tables: horizontal bar, clustered column, smooth line
- Executive dashboard with 6 KPI cards + 8 linked charts + 5 strategic recommendations
- 11-slide PowerPoint deck with data-validated findings
| Feature | Application |
|---|---|
| Pivot Tables | 6 pivot tables with Sum vs Average logic per field |
| Pivot Charts | Live-linked PivotCharts from pivot cache |
| Helper Tables | Chart source tables using =cell_reference cross-sheet formulas |
| SUMIF / AVERAGEIF | KPI Summary — year-on-year comparisons |
| Conditional Formatting | Color scales on churn, margin, dispute, opportunity columns |
| Named Tables | tbl_working structured table for [@column] references |
| Calculated Columns | [@revenue_USD]/[@active_users], [@unbanked_pop_pct]/[@market_share_pct] |
| Number Formatting | Custom formats: $#,##0, 0.00"%", $#,##0,,"M" |
| Dashboard Design | KPI cards, section banners, gridline-free canvas layout |
| Data Governance | Protected Raw_Data tab — locked source of truth |
- Executive-level 11-slide strategic deck
- Data-driven visual storytelling (KPI cards, product mix, risk heatmaps)
- PayPal brand color system
- Chart integration via Paste Special (Enhanced Metafile)
- Operational Business Intelligence (BI) dashboard design
- Unit economics analysis (CAC, revenue per user, CAC-to-revenue ratio)
- Custom market opportunity scoring (unbanked population ÷ market share)
- Risk matrix construction (churn × dispute cross-tabulation)
- Time-series trend analysis and Q4 seasonality identification
- Strategic framework: Defend / Invest / Fix / Review
- Digital payments mechanics: TPV, take rate, BNPL, cross-border flows
- MEA market dynamics: GCC maturity, Africa mobile-first adoption, fintech landscape
- PayPal product portfolio: Merchant Payments, P2P Transfers, Cross-border, BNPL
| Metric | 2023 | 2024 | Change |
|---|---|---|---|
| Total TPV | $2.03B | $2.23B | +9.7% |
| Total Revenue | $52.4M | $57.0M | +8.7% |
| Net Profit | $13.2M | $14.2M | +7.7% |
| Avg Net Margin | 21.0% | 21.0% | Stable |
| Active Users | 6.27M | 7.17M | +14.3% |
| Avg Churn Rate | 3.05% | 3.07% | +0.02pp |
| Country | Region | TPV 2024 | Net Margin | Churn | YoY Growth |
|---|---|---|---|---|---|
| UAE | GCC | $615.6M | 29.9.0% | 2.28% | +7.0% |
| KSA | GCC | $542.4M | 26.9% | 2.44% | +9.4% |
| Qatar | GCC | $265.8M | 29.0% | 2.40% | +4.9% |
| Egypt | Africa | $224.0M | 13.9% | 3.97% | +15.0% |
| South Africa | Africa | $207.3M | 18.1% | 2.94% | +13.3% |
| Kenya | Africa | $157.3M | 13.0% | 3.31% | +22.4% |
| Bahrain | GCC | $151.7M | 28.2% | 2.18% | +4.8% |
| Jordan | Levant | $62.7M | 9.0% | 4.98% | +17.6% |
| Product | TPV Share | Revenue Share | Take Rate | Avg Churn | Avg Dispute |
|---|---|---|---|---|---|
| Cross-border | 34.9% | 47.4% | 3.49% | 3.49% | 2.08% |
| Merchant Payments | 30.2% | 29.5% | 2.50% | 2.68% | 1.08% |
| P2P Transfers | 22.6% | 8.9% | 1.00% | 2.88% | 0.78% |
| BNPL | 12.3% | 14.3% | 2.99% | 3.19% | 2.76% |
1. DEFEND GCC 🏆 — GCC delivers 28.5% avg margin on $3.05B total TPV (71.5% of portfolio). Market share already 32–38%, leaving minimal acquisition headroom. Focus on take rate optimisation and BNPL cross-sell to existing users. No heavy acquisition spend.
2. INVEST KENYA 🚀 — Fastest growing market (+22.4% YoY) with $19.94 CAC, 42.0% unbanked population, and 92.3% mobile adoption. Opportunity Score of 4.19 confirms significant headroom. Priority: accelerate merchant acquisition, partner with mobile money ecosystem, expand BNPL in Nairobi.
3. FIX EGYPT 💡 — 1.73M active users (largest base outside GCC) generating only $4.6M revenue on $224M 2024 TPV. P2P take rate of just 1.01% drags the average. Action: tiered pricing, upsell cross-border services (3.49% take rate), reduce $22.04 CAC through local partnerships.
4. CONTROL BNPL
5. REVIEW JORDAN 🔍 — Jordan grew +17.6% YoY but has unsustainable unit economics: 9.0% margin, $38.74 CAC (3.2× UAE), 5.00% churn, NPS 35.2, net profit only $147K. KPI gate: if monthly churn stays above 3% and margin below 12% by Q2 2025, reallocate capital to South Africa (18.1% margin, 2.94% churn).
Strategic Direction: Grow in Africa. Protect in GCC. Fix/Review in Levant.
Screenshots from the Excel dashboard and PowerPoint deck
| Executive KPIs | Product Mix |
|---|---|
 |
 |
| Risk & Churn Matrix | Strategic Recommendations |
|---|---|
 |
 |
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Revenue Forecasting — Build a 12-month TPV and revenue forecast using the 24-month trend data, incorporating seasonal coefficients (Q4 +15–20% observed) and country-specific growth rates to project 2025 performance scenarios.
-
Competitive Intelligence Layer — The
local_competitor_indexcolumn exists in the dataset but was not fully utilised. A deeper analysis overlaying competitor pressure against market share trajectory would sharpen the investment prioritisation framework. -
Cohort Analysis — Current analysis treats all active users equally. Breaking users into acquisition cohorts (by quarter and country) would reveal whether newer users have higher churn than established ones — critical for distinguishing structural from acquisition-quality issues.
-
BNPL Credit Risk Scoring — Build a matrix combining
dispute_rate_pct,churn_rate_pct, andregulatory_risk_scoreby country to create a BNPL market-readiness score — determining exactly which markets are safe to scale BNPL in. -
Power BI Migration — The Excel dashboard is fully functional but a Power BI version would enable real-time data refresh, drill-through capabilities, and geospatial mapping of MEA performance for improved executive usability.
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Synthetic Dataset — All data was generated to simulate realistic PayPal MEA operational patterns based on publicly available market data. Actual PayPal operational data is proprietary and confidential.
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Static Snapshot — The dataset covers Jan 2023 – Dec 2024 only. Macroeconomic events (currency devaluations in Egypt, regulatory changes in Jordan) are approximated through the
regulatory_risk_scorecolumn rather than modelled explicitly. -
Merchant-Side Gap — The dataset focuses on consumer-side metrics. Merchant acquisition, merchant churn, and B2B revenue streams are not fully captured, which limits the completeness of the two-sided network analysis.
-
CAC Simplification — Customer Acquisition Cost is modelled as a market-level average. In reality, CAC varies significantly by channel (digital, partnership, organic) and by product — a granularity not available in this dataset.
-
Opportunity Score — The custom Growth Opportunity Index (Unbanked % ÷ Market Share %) is a simplified proxy. A full market sizing model would incorporate TAM, GDP per capita, smartphone penetration, and regulatory environment as weighted inputs.
| Section | Details |
|---|---|
| Requirements | Excel 2016+ (pivot tables) · PowerPoint 2016+ |
| Open Workbook | 1. Open PayPal_MEA_Transactions_Project.xlsx 2. Click Enable Content 3. Use tabs: README (overview) → Dashboard (summary) → PT1–PT6 (analysis) |
| Refresh Pivot Tables | 1. If empty: Right-click pivot → Refresh OR Data → Refresh All 2. Raw_Data is protected (do not edit) 3. Working_Data uses [@column] structured references (no macros) |
| Dashboard View | 1. Open Dashboard tab (last, orange) 2. No gridlines (intentional) 3. All KPI cards reference KPI_Summary via cross-sheet formulas 4. Charts linked to PT helper tables |
📄 Click here to view the full Data Dictionary & Naming Conventions (PDF)
Note: This is a synthetic dataset simulated from publicly available MEA market data (World Bank, IMF, regional central bank reports). All values reflect realistic patterns, not actual PayPal operational data.
PayPal MEA Digital Payments Operations. The project demonstrates end-to-end analytical capability: from dataset design and data governance through to executive dashboard and strategic recommendations.
Tools: Microsoft Excel (Advanced) · Microsoft PowerPoint
Domain: Digital Payments · MEA Markets · Operational BI
Dataset: 768 rows × 39 columns · 8 countries · 4 product categories · Jan 2023 – Dec 2024