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E-KB-N/betekbn-ghana-cx-analytics

Domain:

digital infrastructure

Record type:

project
Creator:
E-K
Host:
An end-to-end Power BI analytics solution designed to evaluate customer onboarding friction, identity verification (KYC) bottleneck points, and support resolution performance for BETEKBN Ghana. # BETEKBN Ghana – CX & KYC Onboarding Analytics An end-to-end Power BI analytics solution designed to evaluate customer onboarding friction, identity verification (KYC) bottleneck points, and support resolution performance for **BETEKBN Ghana**. ## Executive Summary As digital onboarding scales across iGaming and fintech platforms, verification delays directly impact customer retention and initial deposit conversions. This project analyzes a 30-day operational dataset from **BETEKBN Ghana** to identify manual review triggers, evaluate support escalation rates via Jira, and pinpoint key drivers behind CSAT fluctuations. ### Key Highlights: * **Total Registrations Analyzed:** 1,000 * **Auto-Approval Rate:** 76% * **Jira Escalation Rate:** 24% * **Average Resolution Time:** 2.12 Hours ## πŸ” Key Analytical Insights 1. **KYC Bottlenecks:** Ghana Card accounts for the vast majority of manual verification reviews and rejections. 2. **Primary Trigger:** Approximately **38%** of manual review escalations stem from **Blurry Ghana Card Uploads**. 3. **CSAT Impact:** Customer satisfaction drops sharply from **4.75** for automated approvals down to **1.29** for rejected registrations, emphasizing the need for real-time document quality checks during upload. ## πŸ—οΈ Technical Architecture & Data Pipeline This project is built as an end-to-end data pipeline simulating an enterprise analytics workflow at EKBN Gaming (Betekbn): (Python generator $\rightarrow$ SQL schema $\rightarrow$ Power BI report). β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ 1. Python Data Layer β”‚ ──► β”‚ 2. SQL Warehouse Layer β”‚ ──► β”‚ 3. Power BI Visual Layer β”‚ β”‚ generate_cx_dataset.py β”‚ β”‚ schema_and_queries.sql β”‚ β”‚ betekbn_cx_dashboard.pbix β”‚ β”‚ (Raw Customer Logs & Syntheticβ”‚ β”‚ (Snowflake/Postgres Schema & β”‚ β”‚ (DAX Measures, Data Model, β”‚ β”‚ Verification Data) β”‚ β”‚ Analy …