A Prominent Online Payment
Solutions Provider Achieved
$5M+ in New Revenue 

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Results in Terms of Numbers:

The Beinex Model Enabled for the Client 

A Self-service Analytics Ecosystem 
Implemented a visually-aided self-service analytics ecosystem. 
  • 25% increase in data analysis speed. 
  • 20% more insights generated due to improved visualisation capabilities.
Data Monetisation Enhanced
Enhanced the system for comprehensive data monetisation. 
  • 30- 50% increase in revenue from data services. 
  • $5M+ increase in additional annual revenue.
AI and ML Models Introduced
Introduced AI and ML models to optimise merchant acquisition strategies. 
  • 30%-50% reduction in customer acquisition costs for the merchant. 
  • Reduced merchant churn to the tune of 28%. 
A Robust Data Handling and Analysing System
Upgraded to a robust system capable of handling and analysing vast amounts of data efficiently. 
  • 40% improvement in data handling efficiency. 
  • 60% reduction in time to actionable insights. 
Client & Requirement:

Delivering Beinex Excellence to Our Clients

The client, a prominent online payment solutions provider in the MENA region, aimed to achieve data monetisation by leveraging AI & ML solutions to generate new revenue streams and improve overall business performance and profitability. 
Highlights of the Beinex Solution
Improved data monetisation capabilities leading to a substantial increase in revenue: approximately 5M+ USD in additional annual income. 
Analysed and visualised customer and merchant transaction data using Tableau. 
Identified key metrics and KPIs relevant to merchant profitability.  
Before and After Beinex:

Transforming Challenges into Success Stories

Before Beinex
>
After Beinex
High churn rate, losing merchants frequently. 
Merchant Retention 
Improved merchant retention. 
Legacy system with limited flexibility and scope for variable analysis. 
Analytics System 
Enhanced visual, dynamic, and interactive capabilities. 
Slow and dependent on manual processes, significant delays. (1-2 hours to obtain data) 
Data Analysis
Enabled faster analysis and reduced dependencies. 
Limited ability to monetise data. 
Data Monetisation
Enhanced data monetisation, generating ~5M+ USD in new revenue streams. 
High acquisition costs. 
Customer Acquisition Costs 
35% reduction in customer acquisition costs for merchants. 
Low merchant stickiness. 
Merchant Stickiness 
30% improvement in merchant stickiness. 
Limited analysis, new dimensions could not be added. 
Insights and KPIs 
Comprehensive insights into revenue, costs, and overall profitability, with 200+ tracked attributes. 
Inefficient transaction monitoring, limited insights into patterns and anomalies. 
Transaction Monitoring
Detailed tracking of sales, transaction declines, geospatial dimensions, and customer spending behaviour. 
Huge data volume (3-4M+ transactions/day) with slow processing. 
Data Volume Handling 
Efficient handling and analysis of 80M+ transactions monthly. 
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Results in Terms of Numbers:

Resolving Complex Issues with Precision

Struggled with merchant retention 

  • Improved merchant retention to a significant margin.

Inefficient legacy system lacking visual and interactive capabilities resulting in limited data-driven analysis 

  • Implemented visually aided self-service analytics ecosystem, an industry game-changer enabling timely insights-generation.

Limited ability to monetise data 

  • Enhanced data monetisation capabilities aiding significant uptick in revenues. 

High costs due to inefficient customer acquisition strategies 

  • Faster turnaround for generating actionable insights resulted in better customer services and offerings.

Difficulty in managing and analysing large data volumes

  • Instituted a system for efficient handling and analysis of 2-3 billion records a year.
Powering Success:

The Crucial Role of Technology

User-friendly Dashboards from Tableau
Installed and configured Tableau Server/ Desktop and established connections to relevant data sources. Data integration and validation were done by importing and validating sample datasets in Tableau. Visualisation creation focused on designing visualisations for key profitability metrics and developed comprehensive dashboards for sales, management, and merchants, incorporating predictive analytics. Profitability analysis was conducted to examine key profitability indicators and enable detailed exploration into merchant segments. Finally, user interaction and exploration were assessed to ensure the dashboards were interactive and user-friendly. 
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