B2B opportunity predictiona Big Data and Advanced. Analytics Approach. Insert

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1 B2B opportunity predictiona Big Data and Advanced Analytics Approach Vodafone Global Enterprise Manu Kumar, Head of Targeting, Optimization & Data Science Insert

2 Agenda Why B2B opportunities are hard to spot And traditional approaches don t work.. Taking a big data view of the opportunity space Hypothesis vs. Discovery Insights & actions Challenges What's next..

3 Why B2B opportunities are hard to spot. Traditional approaches to B2B opportunity identification can miss the big picture Data systems are limited CRM & Marketing automation systems focus on potential future events ERP systems focus on past events Marketing and sales operations teams face pressures Analyst reports can be non specific Experts are hard to come by. Opportunities Iceberg What your datasets, systems, intuition, experience etc. shows you What else is out there

4 Current VGE datasets VGE (& B2B) selling can be Revenue Contribution complex Buying Centers Granular; 12% Granular; 9% 100+ products to sell across 70 countries to 1800 of the worlds biggest companies Local, Regional, Global buying centres Multiple stakeholders & influencers Lengthy sales cycles Perfect data does not exist. Non Granular; 88% Non Granular; 91% Purchase history Pipeline Capability TARGET Field Intelligence Market intelligence 17/10/14 1. Investments 2. Focus Areas

5 Sales Opportunity Prediction Engine Adapt sophisticated algorithms Machine learning Mobile, Social, Secure Cant sell? Interested? Opportuni ty? High penetration: upsell High potential: Invest Underpenetration: deep sell customer s Selling? propensity : cross sell cts u d ro p Leverage data sources to uncover universe of unexplored opportunities Step2: Create an Opportunity Universe High Step 1: Answer 4 questions For every customer, for every product and every geography High propensity whitespace: primary sell

6 Data Security & Encryption VGE is committed to keeping all of its data secure Subscriber details are anonymized All granular data is encrypted Applications use state of the art credentials & encryption systems None of the data ever leaves the organization In fact, good data driven insights are a competitive advantage

7 Demo- TARGET (PC)

8 TARGET Focus areas for sales & marketing aligned to business priorities Delivered securely on host of platforms Metrics & KPI s monitored real time Local intelligence crowd-sourced Prediction accuracy up to 78% Pipeline built in first 2 quarters of implementation $34Mn & wins total over $9Mn

9 (Big) Data Science Volume, Variety and Velocity N=All Comprehensive profiling Buying journey maps Complex event processing Algorithmic selling Constant learning Optimal resource allocation Targeted investment strategy Analytical complexity Hypothesis vs Discovery Use cases for marketing & sales Pre scri ptiv e (wh at do we do nex Predictive t?) (what will happen and why) Investments & focus areas Descriptive (what happened) Data Foundation Churn, Propensity, Indicators, Patterns etc. Performance management: Dashboards, scorecards, reports Data integration into marts, warehouses or lakes

10 Our secret sauce: Algorithms Algorithms unlock value in datasets TARGET 2.0 Leverage the affinity between Beer and diapers Learning from Retail & Gaming industry Decision trees Collaborative Filtering applied to B2B Same model as Amazons recommendation engine Propensity to buy Variants of plane balancing problem TARGET 1.0 Ask Someone Product Team Sales Team Marketing Team Consultants Parametric Weighting Market Basket Affinity Models Random Forest Collaborative Filtering Hybrid Market Basket Affinity Models Propensity to Buy Regression Clustering Under development: Complex Event M apping Social sentiment analysis Unstructured dataset analysis

11 Demo 2: TARGET with recommendation engine 17/10/14

12 Demo- New Tool (Poptimizer)

13 Learning You will fail more often than you succeed Going in with a hypothesis can sometimes be counterproductive Avoid over-fitting your model Let the data drive you Get a sponsor Complex models and great insights are pointless unless people use it

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