The Results
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The Execution
The client, a credit service company, offers a range of credit and finance products, managing the personal data of approximately 2 million actively transacting customers.
As the largest credit services provider in Malaysia, the client wanted to enhance existing growth strategies by gaining a deep understanding of customer data and increasing Customer Lifetime Value (LTV) through targeted cross-selling campaigns. Project initiation objectives include boosting incremental sales through accelerated product cross-selling.
The client faced challenges in effectively cross-selling to their existing customer base. The marketing team faced difficulties in identifying customers with a higher propensity to purchase their products.
ADA helped consolidate data from multiple systems, unified them, and fine-tuned the predictive models, thereby increasing the accuracy of the models for more relevant and effective campaigns.
The Approach
Utilising the centralised Treasure Data Customer Data Platform (CDP), we ingested data from various systems and silos. The source systems included customer information (CRM), customer transactions and billing data (Billing system / data mart), customer finance and repayment data, and customer spending in stores (SKU data system).
We unified data from all systems to create a customer 360 view. ADA has developed six distinct predictive models, each tailored to a specific product category:
- Credit card
- Prepaid card
- Personal finance
- Motor finance
- Objective finance
- Auto finance
Our data scientist, equipped with expertise in machine learning, fine-tuned these models. Through meticulous feature engineering, we have significantly increased the accuracy of the models.
New customer attributes, indicative of the products they are most likely to purchase, have been developed and used to target the customers with the most relevant campaigns.
The effectiveness of the campaign was measured by ingesting and analysing the response data.
