Finding USD 100K in Marketing Waste with Incrementality Testing
How incrementality A/B tests across TikTok, Meta, and Google at Careem surfaced potential annualized marketing burn reduction of USD 100,000.
Read article →Field notes on applying AI, machine learning, and pricing science to real commercial problems — drawn from roles at Good Glamm Group, Careem, Goldman Sachs, and J.P. Morgan.
How incrementality A/B tests across TikTok, Meta, and Google at Careem surfaced potential annualized marketing burn reduction of USD 100,000.
Read article →How an in-house, AI-driven dynamic pricing system reduced discount dependency by 35% and expanded contribution margin by 25% — without trading off volume.
Read article →A practical look at how ML-driven inventory placement reduced shipment splits by 75% across a multi-warehouse network — with zero additional headcount.
Read article →What it takes to put large language models into production for customer service — and how in-house AI agents lifted NPS by 14% without ballooning support costs.
Read article →What due diligence and integration work looked like across 10+ acquisitions with 800Cr+ combined deal value at Good Glamm Group.
Read article →How investment banking analysis at Goldman Sachs — 75+ investor materials per quarter and automated deal reporting — shaped a career in GTM, pricing, and applied AI.
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