How To Use Big Data And Analytics For Csp (China Mobile)

Transcription

1 Big Data Analytics use cases Zhao Lifen China Mobile

2 Opportunities for big data and analytics Which areas offer the most promising opportunities for big data and analytics? Source: Managing and mining big data (TMF Insight research)

3 Value of Big Data for CSP CSP should extract value of big data based on cloud computing technology and advantages of CSP. For China Mobile, the following are our priorities. Improve Customer Experience Customer QOE Customer Perception Layer Customer Behavior Traffic requirements Revenue Management KQI Service quality layer KPI Network Performance Layer PI Network Element Layer End-to-End of Service Network Value Network Quality and Performance Assist Marketing Decisions Optimize Network Performance

4 Use Case1:Improve Customer Experience query of bill and detailed record CDR process CDR query Process CDR queries from all channels, portal, customer service hotline, self- service terminals, etc. Traditional solution: UNIX server +disk array,-- --High cost,difficult scale- out,low performance when heavy load,etc. Based on Hadoop and Hbase, the system architecture can: High-efficiency query Scale-out easily Agile statistics Implementation Architecture

5 BTS/NodeBBSC/RNC enodeb Use Case2: Assist Marketing Decisions customer tags SGSN AC CG Billing CDR Gn DPI 1 Interface: Gn GGSN/SAE-GW Gateway Billing System Big Data Analytics System 2 WLAN logs Accurate customer tags, including customer s features& preference, range of activities. This will help us to: Know customer better Do customer care Recommend appropriate product to customers Remind customers about the usage of resources in time Interface: A BTS BSC 3 Location info MSC

6 1 Choose target users for e-coupons Based on customer s info, including: tags sex age ARPU range of activities usage of Internet usage of voice call,sms, etc social attribute browsing history on related e- commerce website Shopping history on related e- commerce website Use Case2: Assist Marketing Decisions precision marketing Target users of Starbucks Coffee Bar Target users of the shopping mall 2 Define rules about when to send e-coupons Near shopping mall on weekends At Central Business District on workdays There is Starbucks Coffee Shop nearby(for example, within 200 meters) At 11:30 Send e-coupons of the shopping mall to customers Send e-coupons of Starbucks Coffee Bar to customers 3 example Big Data Analytics System 1 2 Analytics and pick up the target users Signaling, User location info User-defined settings: 1)receive or not 2)parameters Match and decide the target users(near real-time) Precision Marketing Platform Marketing Scene Settings 1 Send electronic e-coupons Choose time slot 1 Dinner time on weekdays 2 Night time near shopping malls Personal Recommend -action Engine 1 Algorithm 2 Rules 3 Send e-coupons of Starbucks Coffee Shop to this person

7 Use Case3:Optimize Network Performance synergic utilization and expansion of 2G/3G/WLAN networks With the development of digital service, digital traffic puts strain on 2G network. Based on the following model, we can analyze the network,service,customer and terminal info under 2G/3G/WLAN and support the synergic utilization and expansion of these networks. Network coverage analysis 3G coverage analysis Service analysis Service component analysis Performance High analysis Fit for TD Fit for WLAN No Abnormal 2G cells with high load Yes High Traffic analysis of associated TD cells Low No TD quality analysis normal TD terminal analysis few many Low/normal end WLAN coverage analysis High Yes Traffic analysis of associated WLAN hotspot Abnormal Low AP quality analysis normal WIFI terminal analysis few many