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.

1. Data Analytics Applications
B2B vs. B2C
Karen Zhang, PhD
July 2014

2. Outline
Framework
Data and Analytics
Case Studies
Summary
15 minutes Q&A

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
HP.com 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. B2B Sales Funnel
Orders
Marketing
Sales
Business Objectives:
• Increase the lead quality
• Accelerate the funnel speed.
• Broaden the funnel
Business Functions:
• Marketing
• Sales

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. 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
https://amplab.cs.berkeley.edu/

7. Recommender System
• Markov Chain Model application
• Collaborative Filtering
   x| XxXxxX| XxX tttttttt   111111 PrPr 

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. 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. 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. Thank you
Contact：
Karen Zhang
Zurich Mobile 41 (0) 76 517 79 59
www.linkedin.com/in/zhangkaren/

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: http://tachyon-project.org
• Source Code: https://github.com/amplab/tachyon
Open source status