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The Challenge
The client faced the pervasive challenge of stagnant conversion rates and untapped revenue potential, stemming from an outdated recommendation system that offered generic, rule-based product suggestions. This lack of true personalization led to user disengagement, high bounce rates, and a failure to capitalize on cross-sell and upsell opportunities.
The core technical hurdle lay in processing an immense volume of heterogeneous user data – including clickstreams, purchase histories, and session durations – in real-time. The existing infrastructure struggled with scalability, data latency, and the computational demands required for advanced machine learning models, hindering any meaningful personalization efforts.
