Project - Machine Learning Propensity Model

Summary

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.

Impact

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.

Mudano’s Approach

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.

This site uses cookies and by using this site you are consenting to this. Find out why we use cookies and manage your settings here.