Project - Machine Learning Propensity Model
Customer acquisition for niche investment products is hard with over 90% of customers who started the onboarding journey dropping out.
Our value goal was to significantly increase the customer acquisition and revenue using machine learning, enabling a far better understanding of a customer’s propensity to buy.
Applying the predictive model, we identified a large pool of previously unidentified leads, significantly increased the onboarding success rate and incremental revenue of £20m.
The average onboarding journey time was reduced by 25%, saving time and cost.
Process and profile visualisation
Data visualisation of the typical journeys of completions and drop outs identified success indicators.
Transactional behaviour profiling
Aggregated behavioural profiles identified new insights that changed existing beliefs and actions.
Predictive machine learning models
Machine learning algorithms predicted which customers would successfully complete an onboarding journey.