With the implementation of the Customer Data Platform (CDP), the client could unify customer data from all sources, cleanse it, and make it available for analysis, segmentation, and activation. The solution enabled the client to personalise interactions and deliver a better customer experience. By consolidating customer data into a single source of truth, they could perform credit criteria analysis and improve the SLA / abandoned rate when handling customer inquiries. Furthermore, the CDP solution eliminated the need for multiple tabs to view customer information in our core system, thereby increasing productivity.

The Master Segment Creation feature was used to develop a Centralised Customer Data Repository. This repository efficiently stores all relevant customer data, including personal details, contact information, current active product details, past application history, card transaction details, loan repayment history, etc. Additionally, a comprehensive Data Dictionary was created for business users.

This implementation provided the client with a unified 360-degree view of customer data, significantly enhancing data integrity and management. It aided in the accurate creation of customer segments, enhancing marketing and customer service strategies.

To address the challenge, ADA developed three automated dashboards using Power BI, exporting unified customer data from the CDP. These dashboards include a Single Customer View Dashboard, a Cross-Sell Campaign Report, and a Customer Demographic Dashboard. The primary goal was to reduce the reliance on the BI team by providing direct access to essential data visualisations and insights.

The dashboards featured performance metrics, interactive filters, and clear data visualisations to track progress towards specific goals, customising views based on individual needs, and displaying data in an easily understandable format.

This implementation enabled business unit teams to take swift actions, reduced the turnaround time for generating insights, and ensured data accuracy by eliminating manual processes. The prioritisation of these dashboards was determined by the project team, aligning with the specific needs of different business units within the company.

With the implementation of the Customer Data Platform (CDP), the client could unify customer data from all sources, cleanse it, and make it available for analysis, segmentation, and activation. The solution enabled the client to personalise interactions and deliver a better customer experience. By consolidating customer data into a single source of truth, they could perform credit criteria analysis and improve the SLA / abandoned rate when handling customer inquiries. Furthermore, the CDP solution eliminated the need for multiple tabs to view customer information in our core system, thereby increasing productivity.

The Master Segment Creation feature was used to develop a Centralised Customer Data Repository. This repository efficiently stores all relevant customer data, including personal details, contact information, current active product details, past application history, card transaction details, loan repayment history, etc. Additionally, a comprehensive Data Dictionary was created for business users.

This implementation provided the client with a unified 360-degree view of customer data, significantly enhancing data integrity and management. It aided in the accurate creation of customer segments, enhancing marketing and customer service strategies.

The client employed the Audience Studio feature for seamless customer segmentation creation. An advanced Propensity Scoring model at the Product Category Level was developed. This model assigns propensity scores to customers for each product SKU or scheme, assessing the likelihood of a customer successfully applying for specific products across six main product categories. The scores range from 0 to 1, indicating the level of fit between the product category and the customer’s needs and preferences.

The function streamlined the segmentation process, allowing for quick and intuitive creation and management of customer segments. Meanwhile, the Propensity Scoring model provided a quantifiable measure of a customer’s likelihood to engage in cross-selling campaigns.

This dual approach not only improved the accuracy and efficiency of targeting in marketing campaigns but also optimised resource allocation by focusing efforts on customers with the highest propensity to convert, significantly enhancing the effectiveness of marketing strategies.