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Integrated Marketing Analytics & Data-Driven Intelligence
• Bruce Swann • Manager, CI / Integrated Marketing, SAS
• Scott Briggs • Principal Solutions Architect, Customer Intelligence, SAS
• Suneel Grover • Sr. Solutions Architect, Integrated Marketing Analytics, SAS• Adjunct Professor, The George Washington University (GWU)
Module 4: Emerging Analytical Approaches for Integrated Marketing
AgendaI. High-performance marketing optimizationII. Social media analytics and real-time actionsIII. Social network analytics and community influence
HIGH-PERFORMANCE MARKETING OPTIMIZATION
Marketer’s Have Been Searching for the Holy Grail…
The Right Offer…To The Right Customer…
In the Right Channel…At The Right Time…
The Marketing Assignment Problem
Customers & Prospects
Offers, Services, and Pricing
ChannelsWeb Email Mail Mobile Phone Branch ATM Advisor
Acquisition
Which customer gets what offer?Through what channel?
At what time?
Awareness RetentionSpecial Offers Win Back
Social
The Core of the Problem is a Big Data Challenge
High Performance Marketing Optimization Helps Solve this
Problem
Let’s Break it Down…
High Performance
Vertica
Teradata
Greenplum
Oracle
Microsoft PDW
Hadoop
$- $20,000 $40,000 $60,000 $80,000 $100,000
Today 2009
Cost of Storage, Memory, Computing • In 2000 a GB of Disk $17 today < $0.07• In 2000 a GB of Ram $1800 today < $1• In 2009 a TB of RDBMS was $70K today < $ 20K
2011 – 2012 “Big Data” Technology Advances • Greenplum MapR (May ‘11) • IBM Big Insights (May ‘11) • Microsoft and Hadoop (Oct ‘11) • SAP Sybase IQ & Hadoop (November ‘11) • Oracle & Cloudera Appliance (Jan ‘12) • Teradata Partners w. Hortonworks (Feb ‘12) • SAS LASR Server on Hadoop (Mar‘12)
In-Memory Technology • SAS HP Solutions Announced (Nov 2010)• SAP HANA (December 2010) = $160M in 2011 • Oracle Exalytics (October 2011) • SAS LASR In-memory Server (March 2012)
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 $- $2 $4 $6 $8
$10 $12 $14 $16 $18 $20
Cost per Gigabyte
Marketing Optimization
Customer Offer A Offer B Offer C1 100 120 902 50 70 753 60 75 654 55 80 755 75 60 506 75 65 607 80 70 758 65 60 609 80 110 75
Objective Maximize projected profit
Constraints1 offer per customer3 customers per offer
Campaign Prioritization
Campaign Prioritization = $655
A Simple Example
Customer Offer A Offer B Offer C1 100 120 902 50 70 753 60 75 654 55 80 755 75 60 506 75 65 607 80 70 758 65 60 609 80 110 75
Objective Maximize projected profit
Constraints1 offer per customer3 customers per offer
Campaign Prioritization = $655
Customer Prioritization = $715
Customer Prioritization
A Simple Example
Customer Offer A Offer B Offer C1 100 120 902 50 70 753 60 75 654 55 80 755 75 60 506 75 65 607 80 70 758 65 60 609 80 110 75
Objective Maximize projected profit
Constraints1 offer per customer3 customers per offer
Campaign Prioritization = $655
Customer Prioritization = $715Campaign Optimization = $745
Campaign Optimization
A Simple Example
High Performance Marketing Optimization Solves Previously Unsolvable Problems
Example
• 26 million customers• 910 potential offers• 21 business constraints • 52 million rows of contact history
1 captain1 thread
128 captains 4 threads Improvement
Load data 1hr 24min 1hr 24min
Prepare input data 1hr 1min 30sec 122x
Execute Optimization 5hr 29min 6min 15sec 53x
Total optimization time 6hr 30min 6min 45sec 58x
A Previously Unsolvable Problem
1 captain1 thread
10 captains4 threads
124 captains 4 threads
Improvement
Load data 7hr 7hr 7hr
Prepare input data 9hr 35min 38min 3min 10x
Execute Optimization Can’t be solved 2hr 5min 17min 7x
Total optimization time
3hr 53min 20min 8x
• 50 million customers• 1000 potential offers• 100 business constraints
• Financial Services– Cross-sell and up-sell in retail banking: savings accounts, home equity
loans, credit cards, lines of credit, etc. – Insurance policy offers– Deciding credit line increases– Deciding what APR to offer on balance transfer offers
• Telecom– Complex cell phone or calling plan offers– Bundled service offers– Cross channel offers with different costs of execution
• Others – Loyalty offers (Hotels, Casinos) – Personalized coupons (Retail)
Use Cases
How much $$ are you leaving on the table without optimization?
SOCIAL MEDIA ANALYTICS AND REAL-TIME ACTIONS
http://www.youtube.com/watch?v=TXD-Uqx6_Wk
The Ask…
1. What’s working?2. Are we responding adequately?3. Are we growing our reach and driving
revenue?
The Opportunity 1. Know how many visits, leads, and customers each individual
social channel is generating…2. Improve the customer experience…3. Leverage social networks and communities…
Social Intelligence
Listening
Data Mining
Correlation & Forecasting
Text Mining Natural Language Processing
TaxonomiesInfluence & Engagement
Sentiment AnalysisCategorization
Portals CRM
CollectClean
IntegrateOrganize
Accessible by All
Analytics, Classify, Segment, Sentiment,
Natural Language Processing
iPad apps
Dataset Export
WebData
SurveyData
CallLogs
Text Analytics
Social Media Analytics
• WHAT are consumers saying about your brand? About the competition?
• WHO is creating content about your brand…Journalists? Bloggers? Forum members?
• WHO among these authors is a threat to reputation? An opportunity for advocacy?
• WHERE are consumers talking?• Is volume trending up or down?
• WHICH sites matter most?• WHICH sites are more positive?
Negative?
• WHAT aspects of your business drive satisfaction and loyalty?
• WHAT questions and unmet needs emerge?
• HOW do perceptions differ across the various channels through which customers give you feedback?
The Business Need
How can I ensure it’s accurate and relevant to my
business?
How do I cut out the noise and get to the true insights
and action? How can I customize it to understand my business,
my brands and competitors?
How does social media fit with my other business
intelligence?
How can social data augment what I already know?
How can it help me get a clearer picture of my business as it changes?
How do I use social media to drive my business forward?
Where does it fit within my
business strategy?Where can I focus for the
best returns? How can I use it to get a
competitive edge? How do I monetize it?
Engage
1. CRM2. Outbound/Inbound Marketing3. Integrated Marketing
Engage
Engage
Increase Engagement Across Email, Then All Channels
Website Visitor Analysis
Targeted Email Collection Content
1 2 3
Sign-up Incentive
Loyalty Program Email and/or Mobile Capture Call-to-Action
Engage
Optimized Performance
Return-trip Propensity Model
Targeted Cross-sell Messaging
1 2 3
2x Email Open Rate
72% Increase in Conversion Rate
Targeted Email OfferPush to
Conversion
Post to Social
Targeted
Message• Email & Mobile activity• Online behavioral data• Survey results• Social profile• Customer service events
Engage
0%
10%
20%
30%
0 1 2 3 4 5 6 7+
Per
cen
t o
f T
ota
l F
ile
# of Social Networks
Social Participation
Seg 1
Seg 2
Social Network Engages
Social | Email Influencers
Create Friend-centric Message
1 2 3
0%
10%
20%
30%
40%
0 1 2-3 4-10 11-19 20+
Per
cen
t o
f T
ota
l F
ile
# of Friends
Social Reach
Seg 1
Seg 2
32%28%
40%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
Inactive Opener Clicker
Email Activity Segments - 20+ Friends
Engage
Enable customer care agents monitoring social media to communicate with
consumers in order to…
Address the consumer’s service issues and questions
Mitigate or respond to negative comments or threats
Reinforce a customer’s positive sentiment• Broadcast comments to
other customers• Reward with offers
Facilitate customer consideration process • e.g. consumer comparing
hotel options for a vacation
Engage
SOCIAL NETWORK ANALYTICS AND COMMUNITY INFLUENCE
Social Network Analysis
‘A social network is a social structure made up of individuals, which are
connected by one or more specific types of interdependency, such as
friendship, kinship, common interest, financial exchange‘ etc.
Social Network Analysis
Social Network Analysis
Data feeds: ETL to data environment
1 Data Management: Cleanse, parse, categorize, and standardize social media data around “Vail Customers”
2
HUBEpic Mix
Social Media Chatter(e.g. Twitter, Facebook)
3
4
Executive Insights: Explore results in Visual Analytics
5
Social Network Analysis
Social Media Analytics Data
Social Media Analytics Data
Batch ETL
HUB
Outbound
Inbound
Customer DB (or EDW)
Non-matched/Possible matchedSocial/Customer data
Mastered data with Social Info Appended
Matched customer Info (is this possible?)
Community Influence
Social Media Analytics Extract
Social Media Analytics Extract
Data Available
Fuzzy Match Processing
Facebook Twitter
MDM
Community Influence
SarahCasinoVisitor
Sarah’sSocial Network
• Semi-frequent Visitor
• High Value
• Large Friend Network• Content Creator and
Contributor
• Active Social Elements• Encourages Sharing• Friend-centric
Targeted Email Campaign to Sarah
SarahEngages
• Engages with Email• Forwards to Friends• Posts Content
• Network Engages and Converts
• Individuals begin to contribute content (blogs, reviews, etc.)
Sarah’s Network Engages
Community Influence
Virality is the effect of influencers on followers.
In particular, what is the increased likelihood of churn within a
community once an influencer churns.
Virality churn lift is the churn rate delta of followers.
Influencer churn
Follower churn
Social Profile
Social Audience Profile
•Number of Friends•Social Membership•Number of Profiles•Last Activity Date•Social Tenure
Map your constituent audience to social profiles
Use email address as match key
Match constituent to social behavior
Access publicly available social data
Build Social Audience Profile
Assess social engagement levels
Social Profile
0%
10%
20%
30%
0 1 2 3 4 5 6 7+
Per
cen
t o
f T
ota
l F
ile
# of Social Networks
Social Participation
Seg 1
Seg 2
Social Network Engages
Social | Email Engagers
Create Friend-centric Message
1 2 3
0%
10%
20%
30%
40%
0 1 2-3 4-10 11-19 20+
Per
cen
t o
f T
ota
l F
ile
# of Friends
Social Reach
Seg 1
Seg 2
32%28%
40%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
Inactive Opener Clicker
Email Activity Segments - 20+ Friends
Mobile PurchaseWebsiteEmail
Search SocialDisplay Ad
M
D
PE
S
W
O
Case Study
• Major US-based wireless carrier with 30+ million customers.• 89 million individuals within the overall population.• Average community size is roughly 18.• 5% of all subscribers are influencers.
• Followers’ churn rate increased by 25% when influencers churned.
• 30% model lift when SNA was used.• Campaign take rate among followers doubled when
influencers took.
Questions?