AI-Driven Customer Journey Optimisation Driving Profitable Growth
Challenge Overview
Faced high customer acquisition costs (CAC) and low conversion rates within the lead-to-trading funnel (Lead -> eKYC -> Funding -> Trading) due to increased competition.
Impact Metrics
50% Improvement in Lead-to-Account Opening closure rates
2X Improvement in Funding-to-Margin Addition Ratio
Solution
Data Foundation & Feature Engineering
Utilised Google Cloud and raw user behaviour data from Google Analytics 4. Engineered diverse features from user interactions (time on site, device type, page views, content engagement, referral sources) to understand user intent and quality.
ML-Powered Quality Signal
Developed a predictive lead quality scoring model using CatBoost (gradient boosting algorithm).
Real-Time AI Guidance & Activation
Delivered a real-time predictive quality signal for each lead generated through the website/app acquisition journey.
Optimised Activation
Feed the quality signal to the Call Centre CRM for prioritised lead handling and to Ad platforms (Google Ads, Meta) to enable Value-Based Bidding (VBB), shifting the focus from broad reach to targeting high-potential leads and optimising budget allocation.
Role & Responsibilities
Provided strategic oversight, structured the approach, and provided strategic recommendations to improve efficiency and enhance the feature set variables.