One of the largest telecommunications companies in Australia collected and stored data across more than 20 siloed sources. Eliminating these siloes would allow the company to increase its data quality and consistency, boost data-access speeds, and improve the customer experience. It would also enable data scientists to spend time creating models that could bolster the company’s cross-selling/upselling efforts and ROI.
The telecommunications leader envisioned a system that provided a 360-degree view of the customer and eliminated the need for data scientists to spend more than 80% of their time organizing, formatting, and cleaning data. With improved customer data quality and access, business users could spend more time developing analytics, use cases, and models that allowed them to better track and improve customer churn analytics, estimate customer lifetime value, and provide personalized product and content recommendations. In short, the transformation would make the Australian company a customer-centric enterprise.
Wipro eliminated the data silos and created an easily accessed single source of truth by implementing an Informatica master data-management (MDM) solution across business, governance, data, and technology functions. This approach, coupled with a data-governance strategy and ETL tools, resulted in a master repository that provided a 360-degree view of the Australian company’s 85+ million customers.
The solution then accelerated data-science workflows by implementing feature engineering as a separate process. This enabled data scientists to reduce their model-building times and deploy analytical models more quickly, avoiding the previous time commitments for non-analytical work.
With this easily accessible and simple-to-use data product, analysts could complete daily tasks without complex programming skills. Meanwhile, the MDM solution provided a seamless customer experience with real-time marketing updates via a self-service portal, and it improved customer serviceability via consolidated customer addresses.
The new customer-centric view eliminating the need for manual efforts from data scientists, delivering 87% accuracy in customer match rates and 400 transactions per second in the customer-data hub. It also generated more cross-selling/upselling opportunities and increased marketing effectiveness by 60% due to seamless data flow to the campaign management system, which created better insights. Existing customer data quality improved by more than 90%, increasing ROI from data science projects. The solution also improved business experience with API-based self-service for marketing, billing and customer care teams to access customer data in real time.