A technical guide to leveraging advanced analytics capabilities from SAP

A Technical Guide to Leveraging Advanced
Analytics Capabilities from SAP
Charles Gadalla
SAP

© 2015 SAP SE or an SAP affiliate company. All rights reserved. 1
Agenda
• Intro to Big Data and Analytics
• Big Data and Advanced Analytics – Lifecycle
• SAP Vision and Strategy – Advanced Analytics
• Advanced Analytics Solutions from SAP
• Use Cases and Customer Case Studies
• Wrap-up

Intro to Big Data and
Analytics

Big Data — The Four Vs
Customer
Data
Automobiles
Machine
Data
Smart Meter
Big Data
Point of
Sale
Mobile
Click Stream
Social
Network
Location-
based Data
Text Data
IMHO, it’s great!
RFID
Volume
Variety
Velocity
Veracity

Most
Established
KPIs too
10%
75%
Use Analytics
Today
Need
Analytics
by 2020
$2.01B
Annual revenue increase possibility if the
median Fortune 1,000 business increased
the usability of its data by just 10%
1,000%
Return on investment for every $1 spent
on analytics
Nucleus Research, Gartner, Fortune Magazine
Companies Are Missing New Signals
4

Social
In-memory
Cloud
Mobile
Real-Time
Empowerment
Explosive Demand
For Predictive
Big Data
Sensing and
Responding
Sentiment
Intelligence
Predictive Analytics
Personalized
Insights
Real-Time
Analysis
Internet of Things
?
Shift in Mindset
Competing in Today’s Marketplace Means Leveraging All Types of Data

Harnessing the Power of Big Data
Descriptive,
Predictive
and
Prescriptive
analytics
Resources
Decisions –
Tactical and
Strategic
Moving towards: Analytics-Driven
Decision Making Culture
Customer
Data
Automobiles
Machine
Data
Smart
Meter
Point
of
Sale
MobileStructured
Data
Click
Stream
Social
Network
Location
-
based
Data
Text
Data
IMHO, it’s
great!
RFID

Imagine the Business Potential …
:-)
Brand
Sentiment
360O Customer View
Product
Recommendation
Propensity to
Churn
Real-time
Demand/
Supply Forecast
Predictive
Maintenance
Fraud
Detection
Network
Optimization
Insider
Threats
Risk Mitigation,
Real-time
Asset Tracking Personalized
Care
MANU-
FACTUR-
ING
RETAIL CPG
HEALTH
CARE
BANKING UTILITIES TELCO
PUBLIC
SECTOR
25+
Industries
MARKET-
ING
SALES
FINANCE
HR
OPERA-
TIONS
SERVICE
IT
SUPPLY
CHAIN
FRAUD /
RISK
11+ LoB

Big Data and Advanced
Analytics — Lifecycle

Big Data and Analytics — Value Chain
Data
Origins /
Producers
Data
Sources
Classificati
on
Data
Storage
Data
Integration
Analytics Consumers

Big Data — Component Architecture
Data sources /
Classification
Meta data
Master data
Transaction-
al data
Weblog
Social
networks
Data storage
and
Processing
RDBMS
NoSQL
Distributed
File Systems
Files - semi-
structured,
unstructured
Images,
Audio/Video
Data
Integration/
Quality
Connectors
ETL
Messaging
CDC
Analytics
Advanced
Analytics
Map Reduce
Consumers
BI Business
Processes
LoB/
Industry
Applica-
tion
Data
Discovery
Big Data and Analytics Governance
Warehouse
Data
Producers
Enterprise
IT Systems
Machines
Devices
Sensors
Media
Internet
Sensors
Big Data –
Smart
Applica-
tionIn Memory

Big Data and Analytics — Cross Section
Customer
DataAutomobiles
Machine
Data
Smart
Meter
Point
of
Sale
Mobile
Click
Stream
Social
Network
Location
-
based
Data
Text
Data
IMHO, it’s
great!
RFID
Structured Unstructured
Semi-
Structured
Data Sources
Format
Advanced
Analytics
Data
Discovery
Query &
Reporting
Frequency
Processing
Continuous Real Time On Demand
Analysis Type Real Time
Near Real
Time
Batch

Big Data and Analytics — Core Patterns
Real-Time
Analytics
Near Real-
Time or
Interactive
Analytics
Pure Batch
High Low

Advanced Analytics — Lifecycle
Prepare
Explore
Discover
PredictModel
Operatio
nalize
Optimize
Validate

Data
Prepa-
ration
Data
Exploration
and Discovery
Predict,
Model
and
Validate
Extend – App
Dev., Partner,
Developer
Community
Operationalize -
Deploy, Manage,
Monitor and
Optimize
Evaluate
and
Decide
Personas in Advanced Analytics Lifecycle
Business
Analyst
(Horizontal)
Business
Analyst
(Vertical)
Data Scientist
Data Miner/
Statistician
Application
Developer
IT System
Admins
Business
Manager

SAP Vision and Strategy —
Advanced Analytics

How Analytics Need to Evolve to Deliver Collective
Insights
Raw
Data
Cleaned
Data
Standard
Reports
Ad Hoc
Reports
& OLAP
Agile
Visualization
Predictive
Modeling
Optimization
What
happened?
Why did it
happen?
What will
happen?
What is
the best that
could happen?
UserEngagement
Maturity of Analytics Capabilities
Self
Service BI
Generic
Predictive
Analysis
End-to-end
Easy adoption
Fast
implementation
Business focused
Enable
storytelling
CollectiveInsight

Challenges and Inefficiencies
Analysts:
Talent
Shortage
Fragmented Point
Solutions
Usability
Shortcomings
Lack of
Visualization
Model
Proliferation
High
Latency
Operational
Datastore
Sensors Mobile Archives
Social &
Text
Order
Processing
Operational
Reporting
RT Risk &
Fraud
Trend
Analysis
Sentiment
Analytics
Predictive
Analytics
Pattern
Recognition
Spatial
Processing
Analyze
Data Stores
Integrate/Load
Staging
Collect
Clean-Data
Quality
Transact
Report
Explore
Communicate
Monitor
Predict
Planning
0
1
Data
Warehouse
Geo-
Spatial
Cache Cache Cache Cache CacheCache
Business & IT: Segregated
Organization Structure
Lack of Decision
Support
Lack of Data
Governance

Analytics Solutions from SAP
Agile
Visualizatio
n
Advanced
Analytics
Big
Data
Mobile
Collaboration
Cloud
Enterprise
Business
Intelligence

Advanced Analytics
Confidently Anticipate What Comes Next to Drive Better Business Outcomes
Universally apply advanced
analytics to information,
processes and applications
to optimize actions
Make sophisticated
advanced analytics easy to
use for a broad spectrum of
users
Predict and act in real time
on Big Data
PREDICT

Three Types of Personas
• Create complex
predictive models
and simulations
• Validate predictive
business
requirements
• Publish results back
to source
Data Scientist
0.1%
Representative
User Base
• Transform and
enrich data source(s)
• Create simple
predictive models
and simulations
• Visualize results and
publish to BI
Platform
Data Analysts
~3% 97%
Executives/
Business Users
• Interact with
published predictive
analysis
• Visualize results in
context of use case
• Collaborate with
colleagues toward
closure/action

Solutions for the Entire Spectrum of Users
Business Users & LOB
Data
Scientist
Business
Analysts
Level of Skill Set – Analytics
Low HighNo
97% 3% >0.1%

Solutions for the Entire Spectrum of Users (cont.)
Business Users & LOB
Data
Scientist
Business
Analysts
Level of Skill Set – Analytics
Low HighNo
97% 3% >0.1%
Embedded Analytics
Industry & Business
Process Analytics
Custom
Analytics
SAP
Lumira
SAP InfiniteInsight (KXEN) SAP Predictive Analysis
SAP
PAL
R
Integration
SAP ADVANCED ANALYTICS

Advanced Analytics — SAP Vision
Operationalize
predictive and
optimization
models across the
enterprise
Reduce Decision
Latency with
Advanced Analytics
Bringing Predictive
Analytics to a broad
spectrum of users
Embed Smart Agile Analytics into Decision Processes
to Deliver Business Impact
Easy Fast Efficient

Advanced Analytics
Solutions from SAP

Advanced Analytics Solutions from SAP
R
Integration
SAP HANA
Search Rules Engine Text Mining
Predictive
Analysis Library
Business
Function Library
Spatial
SAP
Lumira
SAP InfiniteInsight
(KXEN)
SAP Predictive
Analysis
SAP Predictive Analytics
+

Analytics Lifecycle — Tools and Personas
SAP HANA
(Platform)
Data
Preparation
Data
Exploration
& Discovery
Predict,
Model &
Validate
Extend App
Dev., Partner,
Developer
Community
Operationalize
Deploy, Manage,
Monitor &
Optimize
Evaluate
& Decide
SAP HANA
Studio
SAP Lumira
SAP Predictive Analysis and SAP InfiniteInsight
SAP HANA
Studio AFM
SAP HANA
Studio
Personas in
Analytics Lifecycle
(Illustrative)Business Analyst (Vertical)
Data Scientist
Business Analyst (Horizontal)
Data Miner/Statistician Application Developer
IT Systems Admin
Business Manager

SAP Lumira: Visualizing Big Data
Unleash Analyst Creativity
Provides the freedom to understand
your data, personalize it, and create
beautiful content
 Download and install on your desktop in
less than five minutes
 Insight from many data sources
 Combine, manipulate, and enrich data to
apply it to your business scenarios
 Self-service visualizations and analytics to
tell your story
 Optimized for SAP HANA for real time on
detailed data
Self-Service for
Analysts
27

Self-Service for Data Scientists and Business Analysts
Provide Data Scientist and Business Analysts with sophisticated algorithms to take the
next step in understanding their business and modeling outcomes
 Perform statistical analysis on your
data to understand trends and
detect outliers in your business
 Build models and apply to
scenarios to forecast potential
future outcomes
 Breadth of connectivity to access
almost any data
 Optimized for SAP HANA to support
huge data volumes and in-memory
processing

SAP InfiniteInsight
Modeler
Build your models
Social
Find your influencers
Scorer
Deploy your scores
Factory
Improve your models
Explorer
Prepare your data
Recommendation
Personalized recommendations

Reusable  Reduces Human Error  Self-Service
Prepare
Create 1,000s of derived
attributes
Define metadata once
Select time-stamped
population
Builds analytic dataset
automatically
Analytical Data Sets with Clicks Not Code

Easy to Use  Time to Market  More Models
Build
Fully automated modeling
process
• Regression
• Classification
• Segmentation
• Time series forecasting
• Association rules
Identify key variables
Executive and operational
reports
Predictive Power in Days Not Months

Put Scores into Action
One-click deployment of scores
into production
In-database scoring (SQL)
Interface with business apps via
scoring equations in:
• Java
• PMML
• SAP HANA
• Many more
Non-Intrusive  Time to Value  Repeatable
Deploy

Refresh analytic data sets
and models automatically
Deploy scores to production
Alert on data and model
deviations
No Programming  Scale  Manage By Exception
Improve
Every Model at Peak Performance

Improve Insight  Extend Reach  Boost ROI
Social
Use social variables for
enhanced prediction
Identify communities
amongst your customers
Find influencers to make
your campaigns viral
Improve Insight with Social Networks

Adaptive Big Data Plug and Play
Recommend
Addresses any type of
business questions
Make product
recommendations,
targeting digital content
Social recommendations
(e.g., friends) and targeted
ads
Personalize the Recommendations

Improve, Unlock, Govern, and Predict
SAP
InfiniteInsight
SAP Business
Suite,
Success Factors,
RDBMS,
3rd party Apps
Text and Binary
Files, XML,
Excel, JMS, Web
Sources
Hadoop/Hive
SAP
Data Services
Native support
for 40+ sources
& interfaces
SAP HANA
(SAP In-memory
computing)
SAP Sybase IQ
• Connectivity
• Transformations
• Quality
SAP
Predictive
Analysis

In-Memory Predictive and Machine Learning
C4.5
decision tree
Weighted
score tables
Regression
ABC
classification
Spatial, Machine,
Real-time data
Hadoop/Sybase IQ,
Sybase ASE, Teradata
Unstructured
PAL
R-scripts
SQL Script
Optimized
Query Plan
Main Memory
Virtual
Tables
Spatial Data
R-Engine
KNN
classification
K-
means
Associate
analysis:
market
basketText
Analysis
SAP HANA
HANA Studio/AFM,
Apps & Tools

SAP HANA: Text Analytics for Big Data
File Filtering
 Unlock text from binary documents
 Ability to extract and process
unstructured text data from various file
formats (txt, html, xml, pdf, doc, ppt, xls,
rtf, msg)
 Load binary, flat, and other documents
directly into HANA for native text search
and analysis
Native Text Analysis
 Give structure to unstructured textual
content
 Expose linguistic markup for text mining
uses
 Classify entities (people, companies,
things, etc.)
 Identify domain facts (sentiments, topics,
requests, etc.)
 Supports up to 31 languages for
linguistic mark-up and extraction
dictionary and 11 languages for
predefined core extractions
SAP
HANA
Text &
Sentiment
Analysis
SearchAnalyze Predict

SAP HANA: Spatial Analytics for Big Data
SAP HANA
Spatial
Processing
Real-time Spatial Processing
High-performance algorithms
analyze massive amounts of
spatial data in real time
Mobility Visualization Analytics HTML 5 GIS Applications
Spatial Analytics Optimization
Columnar storage
architecture eliminates need
to create spatial indexes,
tessellation, or other
optimization techniques
Geo-content & services
Maps, geo-content, and
geospatial services for
seamless application
development and
deployment
Spatial Data Types &
Functions
Store, process, manipulate,
share and retrieve spatial
data directly in the
database
Business
Data + Spatial Data +
Real-time
Data
Geo –
Services
- Geocoding
- Base
maps
Geo –
Content
- Political
Boundaries
- POIs
- Roads
Columnar
Spatial
Processing
Calc Model
/ Views
- Joins
- Views
Spatial
Functions
- Area
- Distance
- Within
Spatial
Data Types
- Points
- Lines
- Polygons
Transact-
ion Data
Unstructur
ed Data
Location
Data
Machine
Data

Big Data Open and Flexible Architecture
SAP
HANA
Log
files
Unstructured
files
Data loading
for Pre-process
Load results
into SAP HANA
SAP Sybase IQ
(Data Services)
Query
Federation
Smart Query Access (Data
Virtualization)
SAP Sybase IQ
Integration at ETL layer
 Data Services provides
bi-directional SAP
Hadoop connectivity:
HIVE, HDFS, Push
down entity extraction to
Hadoop as MapReduce
jobs
 ETL data into SAP
Sybase IQ
Direct SAP HANA-Hadoop connectivity
 Virtual Table (SAP HANA smart data access)
– Virtual HANA table to federate a Hive table at
query time
 HCatalog integration
– Leverage Hadoop metadata to improve query
performance, e.g. partition pruning in Hadoop before
executing query
 Query federation with SAP Sybase IQ
SAP BI connectivity
 SAP BOBJ multi-
source Universe can
access
Hadoop HIVE
SAP
Predictive
Analysis
and
SAP
InfiniteInsight

R Integration
Adoption by the market
 R Integration with SAP Predictive
Analysis
 Drag and Drop – No Coding
 Custom R Algorithms –
Programming
 Access to over 5,000+ algorithms and
packages
 More algorithms and packages than
SAS + SPSS + Statsoft
 Embedding R scripts within the SAP
HANA database execution

Use Cases and Customer
Case Studies

Predictive Use Cases — Industry and LoB
•Customer
Churn/
Retention
•Cross-
Sell/Upsell
•Campaign
Management
•Lifetime Value
•Pricing Optimization
•Product Launch
Success
•Brand Sentiment and
Sales Analytics
•Cross/Up Sell
•Product Launch
Success
•Brand Sentiment
and Sales Analytics
•Regional
Forecasting
•Brand
Sentiment and
Sales Analytics
•Next Best Activity
•Cross Sell/Upsell
•Churn Reduction
•Customer
Segmentation
•Brand Sentiment
and Sales
Analytics
•Brand Sentiment and
Sales Analytics
•Credit Risk
•Fraud
Management
and
Prevention
•Credit Scoring
•Fraud Management
and Prevention
•Optimizing Product
Quality
•Credit Scoring
•Compliance
•Retail Outlier
•Fraud Management
and Prevention
Quality
•Credit Scoring
•Compliance
•Fraud
Management
and Prevention
•Optimizing
Product Quality
•Credit Scoring
•Underwriting
•Default/bankruptcy
Risk
•Tax Fraud
•Credit Card Fraud
•Insurance Fraud
•Predictive Asset
Maintenance
•Fraud Management and
Prevention
Quality
•Anomaly
Detection
•Usage
Forecasting
•Customer
Segmentation
•KPI Forecasting
•Anomaly Detection
•Usage Forecasting
•Store Segmentation
•In-Store Workforce
Optimization
•Size and Zone
Optimization
•Market Share
Prediction
•KPI Forecasting
•KPI
Forecasting
•Anomaly
Detection
•Usage
Forecasting
•KPI Forecasting
•KPI Forecasting
•Variable Margin Analysis
•Yield Management
•Equipment Effectiveness
•Labor Utilization
•Out of Stock Prediction
•Demand Forecasting
•Inventory and Logistics
Planning
•Out of Stock
Prediction
•Inventory and
Logistics Planning
•Out of Stock
Prediction
•Inventory and
Logistics
Planning
•Predictive Commodity
Management
•Improving Demand
Planning and Inventory
Management
Retail CPG Financial Services ManufacturingTelecom E-Business
Customer/
Marketing
Fraud/
Risk
Operations
Supply
Chain

eBay – Professional Service (Internet)
American Multinational Internet Consumer-to-Consumer Corporation
Product: Early Signal Detection System Powered by Predictive Analytics on SAP® HANA
Business Challenges/ Objectives
 Increase ability to separate signal from noise to identify key changes to the health of eBay’s
marketplace
 Improve predictability and forecast confidence of eBay’s virtual economy
 Increase insights into deviations and their causes
Technical Challenges
 Detect critical signals from 100 PBs of data in eBay EDW
 Highly manual process because one model does not fit all the metrics hence requires
analyst intervention
Benefits
 Automated signal detection system powered by predictive analytics on SAP HANA selects
best model for metrics automatically; increases accuracy of forecasts
 Reliable and scalable system provides real-time insights allowing data analysts to focus on
strategic tasks
 Decision tree logic and flexibility to adjust scenarios allows eBay to adapt best model for
their data
“HANA is valuable in the sense that it accelerates that speed to insight. HANA, with in-memory capability, with multicore, fast, lots of data,
all of that coming together is how I think analytics is going to work broadly in the future.” - David Schwarzbach, VP&CFO eBay North
America at eBay Inc.
“HANA system will free up all the bandwidth right now involved in figuring out what is going. The user just has to feed in their metric,
doesn’t have to really worry about which algorithm is the best and be able to use the system because it is inherently intelligent and
configurable.” - Gagandeep Bawa, Manager, North America FP&A at eBay Inc.
“ ”
Determine
with 100%
Accuracy
that a signal is
positive at 97%
confidence
Automated
Early Signal
Detection
system powered by
SAP HANA

Mitsui Knowledge Industry
Healthcare – Speed Research and Improve Patient Support
Business Challenges
 Reduce delays and minimize the costs associated with new drug discovery
by optimizing the process for genome analysis
 Improve and speed decision making for hospitals which conduct cancer
detection based on DNA sequence matching
Technical Implementation
 Leveraged the combination of SAP HANA, R, and Hadoop to store, pre-
process, compute, and analyze huge amounts of data
 Provide access to breadth of predictive analytics libraries
Benefits
 For pharmaceutical companies, provide required new drugs on time and aid
identification of “driver mutation” for new drug targets
 Able to provide a one stop service including genomic data analysis of cancer
patients to support personalized patient therapeutics
Our solution is to incorporate SAP HANA along with Hadoop and R to create a single real-time big data platform. With this we
have found a way to shorten the genome analysis time from several days down to only 20 minutes.
Yukihisa Kato, CTO and Director of MITSUI KNOWLEDGE INDUSTRY
408,000x
faster than
traditional disk-
based systems in
a technical PoC
216x faster by
reducing genome
analysis from
several days to
only 20 minutes
making real-time
cancer/drug
screening
possible
“ ”

Eldorado — Boosting Sales Forecast Accuracy
Business Challenges/Objectives
 Analyze data stored in the SAP® 360 Customer solution from over 1.5 million point-
of-sale transactions for more than 420 product groups and sales of over 8,000
products each month
 Improve forecast precision to boost sales and reduce inventory costs
Benefits
 Building approximately 500 predictive models a month, a task impossible with
traditional modeling techniques that required weeks or months to build a single
model
 Creating forecasts for assortment planning, shelf replenishment, pricing and
promotion analysis, store clustering, store location selection, and sales and
purchasing planning
 Achieving up to 82% accuracy in sales forecasts, a 10% improvement over prior
forecasting techniques
“SAP InfiniteInsight has given us a scalable approach to create accurate forecasts across our
business”
Elena Zhukova, Head of Analytics, Eldorado LLC
“ ”
82%
Accuracy in
Sales
Forecast
500+
predictive
models per
Month

Belgacom — Reduces Churn and Increases
Customer Satisfaction
 Leverage previously unseen customer insights to reduce customer churn and identify
new revenue opportunities
 Enhance churn detection, speed up deployment for predictive models, and identify
revenue potential across the customer lifecycle
Benefits
 Enables next-best-action marketing across all channels, from call centers to the Web
to retail stores
 Optimizes interactions throughout the complete customer relationship, revealing
previously unseen customer insights
 Identifies market gaps, turning them into revenue
 Increases customer satisfaction and reduces customer churn
 Raises return on marketing investments
 Accelerates modeling time from months to days
“ ”
Modeling
time reduced
from months
to days
4x increase
in campaign
response
rates
“With SAP InfiniteInsight, we can deliver the right offer to the right customer at the right time.
It’s a real competitive advantage. We’re getting the most out of our marketing dollars and a
higher return on our marketing investments.”
Filip Deroover, Business Intelligence Specialist, Belgacom Group

Banglalink — Boosts Customer Retention
Objectives
• Improve retention campaign results to combat customer churn
• Analyze Big Data coming from sources such as call detail records, product
subscriptions, voucher transactions, package conversions, and cell site locations
Why SAP
• Supports intuitive building of predictive models, even for users with no or little
experience in data science or statistics
• Includes prepackaged predictive models and a predefined analytical data architecture
to accelerate the time required to prepare analytical data, build predictive models,
and deploy resulting scores into production
Benefits
 Enabled a model to detect more than a quarter of all future churners with only a 10%
sample of the highest scores
 Deployed SAP® InfiniteInsight® solution within five months
 Gained the tools to build and deploy predictive models in hours, as opposed to
weeks or months
“Using SAP InfiniteInsight, we are able to build customer loyalty through targeted retention
programs which drive hard-line results to our business.”
Nizar El-Assaad, CIO, Banglalink Digital Communications Ltd.
“ ”
55% of future
churners
within 5% of all
subscribers
Predictive
models in
hours as
opposed to
weeks or
Month

Groupe SAMSE — Improving Marketing,
Risk Prevention, and Inventory Forecasting
 Boost marketing campaign performance, risk prevention, and inventory forecasting
across 25 brands and 290 sales outlets
 Analyze terabytes of data on over 300,000 loyalty cardholders and 30,000 enterprise
customers each day
 Build and analyze a 360-degree view of both business-to-business and business-to-
customer relationships
 Update predictive models weekly, rather than monthly, to ensure timely predictions
Benefits
 Response rate to direct marketing campaigns up by 220% • Predictive models that
require just a week, rather
 than months, to update
 Balance between systematic and flexible exploration of daily data across group
brands using predictive models
 Early-warning system for individual customer construction projects, enabling
personalized product recommendations in near-real time across multiple customer-
facing channels, including retail outlets, call centers, and sales
“SAP InfiniteInsight has helped uncover dependable patterns and insight that were previously
unattainable.”
Corentin Jouan, Head of Business Intelligence, Groupe SAMSE
“ ”
220%
increase in
marketing
campaign
responses
Predictive
models that
require just a
week, rather
than months

Aviva: Building Predictive Models with Ease
Using SAP® InfiniteInsight®
Objectives
 Leverage predictive analytics to build propensity models for individual customer groups
rather than build generic models for all customers
 Avoid contacting customers too frequently, while also improving campaign response
rates
 Increase return on marketing and campaign response rates by identifying customers
most likely to respond
Why the SAP® InfiniteInsight® solution
 Charts that help marketing experts visualize the anticipated business impact of models
 Significantly better modeling automation that allows many models to be built with ease
 Automatic analysis of the individual contributions of hundreds of variables to a model,
rather than manual inspection of a limited number of variables
Future plans
 Further improve return on marketing with uplift modeling that predicts the impact of
marketing activities on specific target groups
 Build predictive models to analyze customer acquisition and win-back
"Modeling made easy – thanks to SAP InfiniteInsight.”
Dr. Margaret Robins, Statistical Analyst, Data Analytics and Insight,
Aviva plc
Personalized
Further improve return on
marketing with uplift modeling
that predicts the impact of
marketing activities on
specific target groups
Efficient
Significant increase in the
number of propensity models
used within the company, with
more than 30 models in
production
Current
Ability to use the freshest
data to keep models up-to-
date and capture the latest
trends
30599 (14/05) This content is approved by the customer and may not be altered under any circumstances.

AAA: Boosting Marketing Insight Across the
Customer Lifecycle with SAP® InfiniteInsight®
Objectives
 Optimize marketing insight across all stages of the customer lifecycle
 Provide a more powerful and centralized means of analyzing customer information and
optimizing marketing across motor clubs
 Establish a cost-effective, easy-to-access approach to predictive analytics
Why SAP
 Standard reporting features of the SAP® InfiniteInsight® solution, including modeling
results, variable contributions, and gain charts, that club marketing teams can easily
understand
 Ability to provide collective insight to clubs about members most likely to benefit from the
association’s wide range of offerings
 Scalability of predictive models that can be managed by just two business analysts
across multiple motor clubs
Benefits
 Optimized marketing across channels for nearly 70% of members
 Enabled custom offers to fit individual member interests and needs
 Cut attrition and increased overall customer lifetime value by extending targeted offers to
members with low usage
 Earned millions of dollars in sales, thanks to optimized marketing campaigns for some
clubs
"SAP InfiniteInsight helps us put the right products and services
in front of members at the right time.“
Daniel Mathieux, Member Insights and E-Business, American
Automobile Association (AAA)
Optimized
Marketing campaigns
across channels for
nearly 70% of members
Customized
Enabled custom offers to
fit individual member
interests and needs
Loyal
Cut attrition and
increased overall
customer lifetime value by
extending targeted offers
to members with low
usage
Valuable
Earned millions of dollars
in sales, thanks to
optimized marketing
campaigns for some
clubs

Tipp24: Quadrupling Marketing Campaign
Performance with SAP® InfiniteInsight®
Top objectives
 Better understand the customer lifecycle to nurture high-value customers, increase up-
sell and cross-sell opportunities, and reduce churn
 Gather detailed customer behavior data to optimize marketing campaigns
 Enable efficient predictive modeling across all marketing activities and customer channels
Why the SAP® InfiniteInsight® solution
 Better performance and scalability when compared to SAS software and SPSS software
from IBM
 Ability to identify customer behavior patterns to improve satisfaction
 Ability to predict which customers are at risk of becoming inactive and which inactive
customers are likely to become active again
Key benefits
 Optimizes campaigns and the customer lifecycle across multiple channels, including
telephone, direct mail, and e-mail
 Enables proactive relationship management with existing and potential high-value
customers
 Reduces churn and increases overall customer lifetime value
“In our first year using SAP InfiniteInsight, we realized a 300%
uplift in targeting accuracy.”
Pankaj Arora, Senior Analytics Consultant, Tipp24.com
300%
Improvement in targeting
accuracy, including
identifying likely players
for weekly, monthly, or
permanent tickets for
specific lotteries
25%
Reduction in target
audience size for any
individual campaign,
thanks to more-precise
analytics
90%
Less time to build and
deploy predictive models
(from weeks to days),
increasing the productivity
of the analytics team

Pirelli: Improving Safety and Cutting the Cost of
Every Customer’s Commute with SAP HANA®
Business Challenges
 Allow Pirelli to deliver new services to fleet managers to monitor tire usage and
predict maintenance needs
 Provide timely information on monthly costs, profitability, sales and distribution,
and supply chain management
 Process and analyze large volumes of tire data in real time to predict diagnostic
and maintenance work requirements
Technical Implementation
 Installed tire sensors to collect pressure and temperature data that can be
transmitted to the driver, fleet manager, or dealer
 Centralized data from sensors, GPS devices, and customer records
 Enabled processing and analysis of data from 600 fleets with 1,000 assets (trucks
and trailers) each with the SAP HANA platform, providing real-time data updates
every 1–2 minutes for 16 hours per day, 6 days per week and resulting in 40 billion
data events per year
Key benefits
 Increased competitiveness and innovation using cutting-edge technology
 Increased customer satisfaction, thanks to proactive tire maintenance, improved
safety, and lower costs associated with greater fuel efficiency and longer tire
lifespan
“With SAP HANA, Pirelli can capture, store, and analyze data from multiple fleets to
discover new insights. For example, we can correlate street conditions, climate, and
local practices, then use that insight to improve product quality and performance.”
Daniele Benedetti, Applicative Architectures – Integration and Innovation, Pirelli & C. SpA
>40
billion
Events analyzed
per year
Up to 3%
Up to
20%
Lower fuel and tire
costs
Extended tire
lifespan

Unleash Your Collective Insight
sapbusinessobjectsbi.com sap.com/predictivesaplumira.com
ENGAGE PREDICTVISUALIZE
Real-Time Platform
saphana.com

Where to Find More Information
• SAP Predictive Analytics
• www.sap.com/pc/analytics/predictive-analytics.html
• www.sap.com/pc/analytics/predictive-analytics/software/infiniteinsight/lob-
industry/overview.html
• https://help.sap.com/ii_re
• https://help.sap.com/pa10
• http://marketplace.saphana.com/Industries/Industrial-Machinery-%26-Components/SAP-
Predictive-Analysis/p/3527
• SAP HANA
• www.saphana.com/community/about-hana/advanced-analytics
• www.saphana.com/community/hana-academy
• https://help.sap.com/hana_platform/
• SAP Big Data
• www.sapbigdata.com/

7 Key Points to Take Home
• Identify the entry “V”
• Assess current capabilities against what’s required
• Get the initial project, move iteratively
• Find the compelling use case where Advanced Analytics can help
• Leverage advanced analytics from SAP to drive value out of Big Data
• Download the SAP Predictive Analytics 30-day trial
• Predict and act in real time on Big Data

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A technical guide to leveraging advanced analytics capabilities from SAP

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