Data Analytics – B2B vs. B2C


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This talk was held at the 12th meeting on July 22 2014 by Karen Zhang.

Customers in business-to-consumer (B2C) and business-to-business (B2B) markets go through similar buying journey: need, search, evaluate, and finally order. Thus similar customer analytics approaches are applicable to both scenarios. However company’s go-to-market strategies are usually different in B2C vs. B2B. This study discusses unique characteristics of analytic methodologies applied in B2B vs. B2C. Two case studies will be presented to illustrate similarities and differences.

Published in: Technology, Business

Data Analytics – B2B vs. B2C

  1. 1. Data Analytics Applications B2B vs. B2C Karen Zhang, PhD July 2014
  2. 2. Outline Framework Data and Analytics Case Studies Summary 15 minutes Q&A
  3. 3. 1 Business Questions Data Sources Analysis/ Modeling Test&ActionKPIGreater Consumer Population HP Loyal Life CycleDriversDataInsightsActionMeasure TUP Forreste r TUP Acxiom Acxiom TUP Survey Omniture HHO ASTRO HHO CKM Prospects Customers Techno/ Attitude Readiness Product Awareness In market for next product 1st Order 2nd Order 3rd OrderReturn/Support Who do our best customer look like What channels, products, features they prefer What do they own, research, will consider Where do they come from, navigate to, abandon What they bought, where, how much, what else Why and how did they return or call support What else do they buy, where, how, how satisfied What is their level /value of loyalty and sphere of influence Customer Decision Making Process Customer Valuation Propensity Measures Current Value Future Value Influencer Measures Acquisition Marketing Propensity In-Market Timing Retention Marketing Migration Strategy Better Targeting Differentiated Treatment Up sell / Cross sell Re-activation Attrition Alerts Re-targeting Reward Customer & Channel Propensity for acquisition Response model by channel Channel Mix model Product Offering Optimization model CES product propensity PSG Segmentation Customer Valuation Current LTV Future LTV Influencer Power Customer Loyalty Define Best Customer Model for acquisition Model for migration • Quality of traffic • Open/click- thru rate • Conversion • Order size • Attach value • Repeat Traffic/ visit • CSAT • Cross/up sell value • CES measures • CES Measures • Brand aware Measures • Data Quality/ accuracy • Awareness measures • Consideration measures HHO CKM B2C Customer Analysis Framework 1:1. Real-Time. Interactive.
  4. 4. B2B Sales Funnel Orders Marketing Sales Business Objectives: • Increase the lead quality • Accelerate the funnel speed. • Broaden the funnel Business Functions: • Marketing • Sales
  5. 5. B2B Data Domains Firmographic /Contact Pipeline Competitive Sales Transaction (Direct & Channel) Customer Reference Campaign/Event Response Social Data Contract/Agreement s/Support/ Licenses Online Primary /Secondary Research/IT spends Product /Price
  6. 6. Berkeley Data Analytics Stack (BDAS) Apache Spark Shark BlinkDB SQL HDFS / HBase / Hadoop / GlusterFS Apache Mesos/YARN Resource Manager Spark Streamin g GraphX ML Tachyon
  7. 7. Recommender System • Markov Chain Model application • Collaborative Filtering    x| XxXxxX| XxX tttttttt   111111 PrPr 
  8. 8. Who is likely to buy? When is likely to purchase? What is the next purchase? How will be purchased? B2C Customer Holistic Understanding
  9. 9. End to End Intelligent Marketing Campaign HP Channel Partners Customers2 3 1 4 1 Market Size Estimation 2 Direct Channel Analytics - Identifying likely customers using historical transaction and firmographic information for targeting campaigns 3 Indirect Channel Analytics: Identifying likely channel partners to be activated using channel partner transaction information 4 Enriching the multi-channel strategy: Using unstructured product sentiment information A unique analytical solution comprising of predictive model on structured & unstructured data to drive targeted marketing through multi-channel sales motion 5 Post-Campaign Tracking and Measurement 5 GTM Campaign Tracking and Measurement Process Market Size Estimation
  10. 10. Summary B2B analytics have to be closely aligned with sales strategy, organizational structure, and process Complex product and service bundles in B2B require sophisticated analytics approach Multiple seller-buyer interactions in lengthy B2B sales cycles provide opportunities and challenges
  11. 11. Thank you Contact: Karen Zhang Zurich Mobile 41 (0) 76 517 79 59
  12. 12. • Apache License, Version 0.4.1 (Feb 2014) • 40+ contributors from 15+ companies. • Being deployed at multiple companies • In Fedora 21 • Spark and MapReduce applications can run without any code change • Project Website: • Source Code: Open source status