How to Gain Competitive Advantage with Advanced Analytics in Telco Market Apr 2015

Transcription

1 How to Gain Competitive Advantage with Advanced Analytics in Telco Market Apr 2015 Luiz Rodolfo M. Pires SAS Senior Consultant Telecom Industry Specialist

2 Communications TRENDS Data is key revenue growth driver steady voice decline Missing opportunity to monetize data tsunami Reduce growth in traffic Reduce network costs and improve efficiency Increase revenues via new pricing models Churn continues Global networks reaching their limits investments needed, prioritization Infrastructure deals between CSPs

3 Data Traffic Challenges Data traffic growth significantly outpacing revenue growth Data Revenue Revenue and Data Traffic Indexed to 100 Data Yields not commensurate with the network investments Customers using a larger portion of their data buckets Also lower yields on added data buckets Approaches to improve data yields, in conjunction with LTE deployments Content Providers 3 rd party pays (800 data QoS premium services) Revenue sharing models Location/ Commerce Services advertising/ contextual Subscribers content Tiered pricing plans Shared Device Plans BYOD Offers Optimize network efficiency Wifi/ 3G offloading Network Throttling Granularity required to: Dynamic offers Spend caps Off peak pricing Network Operations Application Tiering Video rate limiting Pacing Deliver/ monitor and control unique experiences Pricing/ offer management Monitoring and delivering against targeted QoS

4 Carriers - Ubiquitous Broadband Coverage: Increasing speeds & connectivity wireless, wireline Rapid smart-device adoption Exploding wireless traffic Video First! Plans 50% % Smartphones Tablets/ Modems 62% mobile market penetrated Smartphones accounted for 85-92% of postpaid quarterly phone sales Additionally, 70% home broadband penetrated Sources: CTIA, The wireless association semi-annual survey, October 11, 2012,

5 Leveraging Advanced analytics to improve functional efficiencies as well as cross-functional impacts Core Business Areas CUSTOMER MGMT. MARKETING MGMT. NETWORK & OPERATIONS DATA MONETIZATION Acquire/ Upsell Detect Churn earlier Social Network Impacts Promoter Insights Optimize Offers and Marketing Campaigns Audience Intelligence IMPROVE existing processes Pricing Modeling Revenue Assurance Credit Risk Demand Forecasting Fraud Prevention Intelligent Store Clustering Capacity Planning & Deployment Network Optimization Service Assurance/ SQI Analytics Call Center Analytics (force, volume planning) Capacity Planning & Optimization Field Operations Supporting Functions Intelligent Messaging Mobile Commerce Location Based Offers Enrich Loyalty Card Programs Real Time EXPLORE new areas COLLECTIONS/ FRAUD & ASSURANCE Collections Analytics Customer Risk Assessment Fraud Assessment FINANCE & TREASURY Profitability Management (Product & Segment) Risk Management Pension/ Investment Portfolio Management HUMAN RESOURCES Workforce Analytics SUPPLY CHAIN Forecast/ Demand planning for handsets/ data cards and other inventory Copyright 2012, SAS Institute Inc. All rights reserved.

6 CSP Market Situation & Role of Analytics Churn Management: leveraging unstructured & upstream churn detection Care/ Operations leveraging unstructured analytics Network Analytics Location Analytics Data Monetization Integration between SAS and esri

7 CSP Market Situation & Role of Analytics Churn Management: leveraging unstructured & upstream churn detection

8 Adding new sources/categories to improve customer management The data categories to analyze below is organized by data sources (groups) CRM Customer (CRU/ IRU/ Bus Owners, Household, etc.) Credit score Sales channel Subscription date Contract Expiration date (for all lines) Upgrade eligibility date Port Date Billing & Payment activities [Rate Plan data incl upgrade, discount history] # lines Life events SOC data Dispute data Customer survey data* Copyright 2012, SAS Institute Inc. All rights reserved. CDR/ IPDRs Calls/ SMS trends To & From Number Date & Time Call Duration Drop calls Text patterns Usage trends Data usage IP Address Sites visited Apps used Up/ Down Speeds Etc. Handset & Network Handset Make Handset Model Handset Technology Operating System IMSI IMEI Lat/ Long Geo location SGSN/ GGSN Cell Technology Clarify (Contact Centers) Calls Problem code hierarchy Resolution code CSR Workgroup Avg call handle time CSR Notes* The data category above is a proxy for Interaction management, i.e. all channel interaction (e.g. stores, contact centers, etc.) Competitive info. Competitive promotions by channel/ geography Web (.com) Bundled billing info Visitor ID Offer bundles Subscriber ID (video all Visit recency services, HSI, Session count voice, etc.) Session avg Promotion Engagement level Session affiliate Social Media Support Twitter Facebook Other sites Legend: Orange font: Potential new data sources to mash on these customers to understand churn prediction * Unstructured (text fields)

10 Agenda CSP Market Situation & Role of Analytics Care/ Operations leveraging unstructured analytics

11 2 Innovation Leveraging Text Analytics Case Description Field Notes Text: Detect emerging topic, with or without prior knowledge of topic Call Center Notes: Summarize what customers are talking about bases on taxonomy Identify emerging topics over time Online Data (social media and help documents): Extract social media and summarize key issues and influential users Index help documents for enhanced search and relevance Surveys: Leverage survey response and associated demographics to predict ratings and net promoter scores

12 2 Chat Analysis SENTIMENT & TONAL ANALYTICS Operationalizing the Insight Distinguish chats that are service-related vs ad-hoc questions and quantify the value Enhance understanding of conversion impact and serve as data input for modeling efforts (campaign response models, forecasting, etc. Consistent reporting leveraging an intuitive/ relevant taxonomy (chat categories and subcategories) Forecast topics and proactively generate alerts highlighting issues

13 2 Opportunities for Early Discovery Monitor Trouble ticket Topics over time High volume topics: Internet Services Down Internet Slow Connection Return Modem Wireless Network Internet Security Certificate topic disappears in this timeframe Copyright 2012, SAS Institute Inc. All rights reserved.

14 Agenda CSP Market Situation & Role of Analytics Network Analytics

15 Analytics Role APPLYING ANALYTICS TO 3 KEY AREAS OF NETWORK MANAGEMENT I Improve Network Planning/ Efficiency II Service Management: Focus on QoE III Reduce Data loss/ nonbilled revenue

16 Analytics Enabled Data Service Planning Network Planning/ Efficiency Network Traffic & Saturation probability 3 months 9 months Music 1% Apple OS 1% WhatsApp 1% Apple 2% skype 2% Traffic Trend By Application Windows Update 1% Gtalk 1% Other 13% Facebook 37% Other 3% edonkey 3% Video 3% Mail 4% BitTorrent 9% HTTP 10% YouTube 11% Handset capabilities (2G,3G, 4G) with underlying assets 63% of 3G handsets got only 2G network service Copyright 2012, SAS Institute Inc. All rights reserved.

17 Agenda CSP Market Situation & Role of Analytics Data Monetization

18 Clients (SAMPLE) Services Data Monetization (Insights to LBS Services) Raw Data Annonymized DSP like model Processed Data Aggregated Data Storage/ Management Insights Data Mining/ Science Analytics/ Predictive modeling Presentation Insight in intelligible formats BI/ Performance Mgmt. Software LBS Services Interaction with consumers (offers, loyalty) APIs access platform & data Connected Lifestyle Low High Data value Data volume High Low Dynamic Insights

19 Initiatives AT Mobile operators & Others Communications/ Cable/ Others Address 1:1 marketing through mobile devices and measurement for markets Use SAS to mash VZ data, Experian, BlueKai (demographics) and AirSage, NewField (location) for DMA level insights Success with NFL Customer Insights Platform Testing 6 use cases with pilot customers Leveraging location information & Prism (Neilson) segmentation data Re-engaging with SAS SAS UK, largest IT/ Operations partner --- chose SAS for integrated stack Success with location based loyalty, offers/ coupons Very interest lessons on data management (privacy), location/ geo fencing, realtime analytics & message delivery (xms channel) Founded by 3 US wireless carriers, AT&T, T-Mobile & Verizon Started with NFC based payment service Early signs to work with SAS for their mcommerce/ madvertising platform Customer Insights Platform

21 Identifying the customer & their prior multi-channel interactions based on opt-ins Targeted/ analytically driven offers and messages delivered to consumer Geofence tripped; offers and messages sent in real-time. Location and context considered in real-time Cross-sell/ Upsell offers delivered to customer upon checkout (multi-channel) As customer engages, send targeted content based on context and analytics Post-sale triggered messages delivered to drive loyalty, likelihood to return and repeat purchase Copyright 2012, SAS Institute Inc. All rights reserved.

22 Campaigns designed and Planned with SAS Customer Intelligence & Data Mgmt. Outbound campaign designed and executed in Customer Intelligence Studio CI Studio (Outbound) Visual Analytics Event detected Inbound/Realtime Campaign(s) invoked Marketing Operations Post-sale triggered messages delivered to drive loyalty, likelihood to return and repeat purchase CI Studio (Real-time Decision Manager) CI Studio (Outbound/Inbound) Analyze Campaign Effectiveness Copyright 2012, SAS Institute Inc. All rights reserved.

23 Integration between SAS and esri

24 Location Analytics for SAS Duas Abordagens SAS Bridge for ESRI SAS Server SAS Bridge for ESRI SAS Bridge for ESRI ArcGIS Desktop software ESRI Map Component SAS BI OLAP Clients SAS Visual Analytics ArcGIS Server

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