Business Need :

Our client was dependent on third party vendor for all their analytics needs. The customer data was managed by third party leading to limited control on data, lack of traceability, long turnaround times, data quality issues and limited analytics capability (e.g., No visibility of usage data and other customer patterns). Data not easily available for targeted marketing. Complex processes, limited access to data hindered customer services. There was no analytics solution and capability. No integration of historic data, CRM data and had no metadata.

Solution :

• Built a secure and robust cloud-based data analytics platform on Azure cloud with

• comprehensive data management, data quality and governance framework, automation.

• Spend and usage prediction for all types of customers (Residential, Industrial, Govt. etc.) across 37+ TOTs.

• Customer Data, Invoice, Feed processed data to Salesforce(CRM) for User Analysis and historical tracking.

Benefits :

• Yearly cost savings of approx. 700K on analytics.

• Faster execution

• Better visibility and control on data

• Low operational cost

• Better customer service

Azure-Based Analytics Platform for Customer Data Sovereignty

Introduction

In the digital age, data analytics has become a pivotal element in understanding customer behavior, enhancing service delivery, and driving business strategy. However, for our client, reliance on third-party vendors for analytics presented several challenges that hindered their capacity to fully leverage customer data. These challenges included limited control over data, poor traceability, slow turnaround times, and subpar analytics capabilities. The absence of an internal analytics framework resulted in ineffective targeted marketing and customer service operations.

Business Challenge

The client's dependence on an external analytics provider led to several critical pain points:

• Limited Data Control: Data managed by a third party curtailed the client's autonomy over their own information.

• Lack of Traceability: The client struggled with tracking data origins and transformations.

• Extended Turnaround Times: Delayed access to data analysis impaired swift business decision-making.

• Inferior Data Quality: Persistent data quality issues diluted the reliability of analytics outputs.

• Inadequate Analytics Capability: The lack of robust analytics tools limited insight into customer usage patterns.

• Complex and Inaccessible Processes: Complicated procedures and restricted data access obstructed customer support efforts.

• Disparate Data Ecosystem: The client's historical data and CRM data existed in silos, with no overarching metadata strategy.

Solution Overview

In response to these challenges, we engineered a comprehensive solution on the Azure cloud platform:

1. Azure Cloud-Based Data Analytics Platform

A secure and scalable data analytics platform was built on Azure, offering a robust environment for comprehensive data management. The platform integrated a data quality and governance framework and introduced automation to streamline processes.

2. Advanced Prediction Models

We deployed sophisticated algorithms capable of predicting spend and usage across diverse customer segments, including Residential, Industrial, and Government, covering more than 37 types of customer categories.

3. Integration with Salesforce CRM

For API-based data sources, an IT Service Management (ITSM) Databricks pipeline was leveraged. This pipeline not only ingests data but also processes it, preparing it for analytics and reporting. The use of Databricks here underscores the solution's emphasis on flexibility and processing power.

Key Benefits

The shift to an Azure-based data analytics platform delivered tangible benefits:

• Significant Cost Savings: The client realized annual savings of approximately $700K in analytics expenses.

• Expedited Execution: Faster data processing and analytics execution enabled more agile business responses.

• Enhanced Data Visibility and Control: The platform provided the client with comprehensive oversight and management of their data.

• Reduced Operational Costs: Streamlined operations and automation led to lower ongoing expenses.

• Improved Customer Service: The integration of customer data with Salesforce improved customer service by enabling more personalized and timely interactions.

Conclusion

The implementation of a cloud-based data analytics platform on Azure marked a turning point for our client. By bringing analytics in-house and creating a centralized data governance structure, they gained critical visibility and control over their data. The ability to predict customer spend and usage patterns across various segments, coupled with the integration of this data into Salesforce, equipped the client with the tools to transform their customer service and marketing strategies. The platform not only reduced costs and increased operational efficiency but also set a new benchmark for data-driven decision-making within the organization.