THE CUSTOMER DECISION HUB IMPORTANCE OF CUSTOMER FEEDBACK OCTOBER 2014
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1 THE CUSTOMER DECISION HUB IMPORTANCE OF CUSTOMER FEEDBACK OCTOBER 2014 C op yr i g h t , S A S I n s t i t u t e I n c. A l l r i g h t s r es er v e d.
2 ABOUT MYSELF Customer Intelligence Director at SAS for the SWE region Worked for several multinationals on CRM Transactional CRM Analytical Customer Insight Interactive Marketing Marketing Accountability Main focus on Telco, Retail, Finance and Utilities Development of roadmaps towards customer centricity Strong interest in Digital Intelligence
3 THE CHALLENGES
4 SOLUTION: THE CUSTOMER DECISION HUB CUSTOMER DECISION HUB
5 THE CUSTOMER DECISION HUB Rules Design Environment Reporting Environment Optimization Engine CUSTOMER DECISION HUB Batch Engine Real-Time Engine
6 THE CUSTOMER DNA
7 ADVANCED ANALYTICS IN CUSTOMER DNA Response Modeling Cross and Up Selling Churn Prediction Customer Segmentation KPI Forecasting Customer Lifetime Value Web Mining Credit Scoring Fraud Detection Marketing Optimization Market Basket Analysis Customer Link Analytics Social Media Analytics Location Analysis Marketing Mix Analysis
8 ONLINE CUSTOMER PROFILE DATA: WEBSTREAM Site Behaviour Variables Customer/prospect New/return visitor All click data Tools usage Previous Product interests Searches Previous online purchases Previous Campaign exposure Previous Campaign resp. Temporal Variables Time of day Day of week Recency Frequency Length of visit Environment Variables IP address Country of origin Time zone Operating system Browser type Mobile type Referrer Variables Referring domain Campaign ID Affiliate Natural search Search keywords Direct/bookmark
9 CHALLENGE IN DIGITAL STREAM Facebook Token: AAADKJHCKACN Login: Twitter ID: MDK2005 Fixed Line: Skype ID: MiniMie410 Person: Mieke De Ketelaere Mobile: Apple ID:
10 PSYCHOGRAPHIC OR IAO VARIABLES: SOCIAL DATA Psychographic/IAO (Interest/Activities/Opinions) variables Attributes relating to personality, values, attitudes, interests, or lifestyles. O Explicit data (directly given by user) Movies/Books Sports Implicit data (indirectly given by user) Context - Relationship analysis Content Categorisation/ Context Extraction Sentiment Analysis Network Analysis Mood Detection
11 RESULT OF SOCIAL INSIGHT IN DNA: SOCIAL PROFILES Source: Sas Whitepaper Please to meet you Why different customers prefer different channels
12 THE CUSTOMER DECISION HUB Customer Care Marketing Sales
13 CURRENT LIMITATIONS IN CUSTOMER INTERACTIONS Lifetime Value Revenue Share of Wallet Individual value Social value Sales Influence Revenue in social circle Size of social circle Example 1: What if a customer spends a lot, but is unprofitable... What is the same customer has lots of Facebookfriends, million of followers, and is considered as an opinion leader, so someone with INFLUENCE
14 CURRENT LIMITATIONS IN CUSTOMER INTERACTIONS Lifetime Value Customer Care Revenue Share of Wallet Individual value Social value Size of Influence social circle Revenue in social circle Example 2: What if a customer is very active on social media, has a limited network around him and is being very negative What if the same customer is not profitable, is using different channels to express his emotions and cost a lot of personalised customer care time
15 SOCIAL INTERACTIONS: FUTURE POTENTIAL High Financial Value Core Buyers Ambassadors Low Missers Influencers Low Social High Value
16 THANK YOU C op yr i g h t , S A S I n s t i t u t e I n c. A l l r i g h t s r es er v e d.
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