Reference no: EM133411434
Case Study: Real-time customer insight and foresight with analytics - Making the right call
Read the case study on how Deloitte helped a large wireless telecommunications company implement platforms to collect, store, and analyze data from across millions of customers and billions of transactions to achieve real-time marketing effectiveness.
Extracts from it are given below.
Summary
"In this wireless telecommunications case study, a large telecom needed to more effectively leverage its vast stores of data for timely customer analytics. They also faced increased churn and decreased share. Now you can see how Deloitte helped them tackle these complicated challenges. Our strategy included implementation of several platforms that collected, stored, and analyzed data from millions of customers and billions of transactions. The outcome: real-time marketing effectiveness to better serve existing customers and open the door for new ones.
" The Challenge:
"Big data is becoming increasingly critical to generate unique market insights for consumer oriented companies. This company is no exception. The company has sizeable vo0lumes of data but no way to perform meaningful analysis on that data. They were facing problems with data latency as well, with an imposed reporting lag time of 45 days on current operational data. The company requires more current data to generate insight for analysis to help them better understand their customer base and open new markets. They also need to integrate new CRM competencies to stave off churn. They also desire foresight capabilities to explore how to shape new revenue streams and capture more aggressive market share."
Read the rest of the case study at: at:
Question: Develop strategies to address the following questions for the real-time data streaming case study given below.
1. How can the company launch an effort to exploit social media?
2. How can the company leverage social media to understand the customer sentiment better to achieve more effective CRM, respond more quickly to customer issues, and efficiently monitor the success of its marketing campaigns?
3. How can the company make an appropriate marketing decision given only the partial view of the high-velocity transactional data?
4. How can the company handle 'concept drift' in high-velocity streaming data analytics?