Raja Ponnan

Campaign Lift Analysis and Revenue Attribution

• Designed and implemented a Campaign Lift Analysis model to measure incremental revenue generated from campaign-engaged vs. non-engaged customers, benchmarked against the same period last year.
• Built a revenue attribution framework based on reseller engagement across multiple marketing channels to identify top-performing and underperforming customers for each campaign.
• Delivered insights to internal teams and vendor partners, enabling data-driven campaign optimization and performance reporting.

Product Recommendation Model for Cross-Sell Analysis

• Developed a predictive product recommendation model to identify cross-sell opportunities based on resellers’ previous year purchase patterns.
• Considered a 7-day purchase window for end users and restricted cross-sell product prices to within 25% of the trigger product’s price to ensure relevancy and affordability.
• Calculated support, confidence, and lift values for each product combination and assigned priority rankings, improving targeting accuracy and campaign effectiveness.

Campaign A/B Testing for Performance Evaluation

• Implemented an A/B testing framework for marketing campaigns by creating a 5% control group of resellers to measure campaign impact.
• Analyzed performance differences between control and test groups to quantify the true incremental value delivered by each campaign.
• Provided actionable insights that helped the organization assess campaign effectiveness and optimize marketing investments.

Marketing Campaign Analytics Support (Ingram-Led & Vendor-Funded)

Provided end-to-end analytics support for multiple Ingram-led and vendor-funded campaigns to improve targeting, engagement, and conversion.

• Cross-Sell: Delivered product recommendation insights to identify cross-sell opportunities based on reseller purchase patterns.
• Dormant Reactivation: Identified inactive resellers across Ingram, vendor, and Vxantage platforms; segmented them into low, medium, and high engagement tiers for targeted reactivation campaigns.
• Loyalty Program: Created country-specific customer segmentation models (Essential, Advanced, Elite) using revenue, annual recurring revenue, and engagement scores to support loyalty-based marketing.
• Reseller Demand Generation: Identified target resellers and matched them with end-user opportunities derived from transaction history to enhance campaign precision.

• Developed and automated analytical scripts using UNIX for client reporting and data monitoring.
• Supported analytics automation and data mining activities to enhance client insights and reporting efficiency.

• Supported LYCA Online Sales Reconciliation System to ensure data accuracy between online transactions and customer balances.
• Improved reconciliation processes to maintain financial integrity and minimize reporting discrepancies.

• Created automated reporting procedures and implemented data mining techniques to support product and pricing decisions.