ibm spss modelerdoc.kern.hu/ipics/ibm/spss_modeler.pdf · customer analytics predictive threat...
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© 2013 IBM Corporation
IBM SPSS Modeler
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What is Predictive Analytics?
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Why is predictive analytics important to your organization
„The median ROI for the
projects that incorporated
predictive technologies was
145% compared with
median ROI of 89% for
those projects that did not” - source: IDC, „predictive
Analytics and ROI: Lesson from
IDC’s Financial Impact Study”
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Advanced Analytics Focuses on the Prescriptive & Predictive
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Predictive Analytics can use ALL Available Data
Behavioral data - Orders - Transactions
- Payment history - Usage history
Descriptive data - Attributes - Characteristics
- Self-declared info - (Geo)demographics
Attitudinal data - Opinions - Preferences
- Needs & desires - Survey results - Social media
Interaction data - Email / chat transcripts - Call center notes
- Web click-streams - In person dialogues
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Predictive Customer Analytics
Acquire customers:
Understand who your best customers are
Connect with them in the right ways
Take the best action maximize what you sell to them
Grow customers:
Understand the best mix of things needed by your customers and channels
Maximize the revenue received from your customers and channels
Take the best action every time to interact
Retain customers:
Understand what makes your customers leave and what makes them stay
Keep your best customers happy
Take action to prevent them from leaving
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Predictive Operational Analytics
Manage operations:
Maximize the usage of your assets
Make sure inventory and resources are in the right place at the right time
Identify the impact of investment
Maintain infrastructure:
Understand what causes failure in your assets
Maximize uptime of assets
Reduce costs of upkeep
Maximize capital efficiency:
Improve the efficiency and effectiveness of your assets
Reduce operational costs
Drive operational excellence in all phases: procurement, development, availability and distribution
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IBM SPSS Predictive Analytics
Acquire
Grow
Retain
Predictive
Customer Analytics
Predictive
Threat & Fraud Analytics
Monitor
Detect
Control
Predictive
Operational Analytics
Manage
Maintain
Maximize
Etc…
IBM Research
Collaboration and Deployment Services
Analytic Server
& Catalyst Modeler
Decision Management
Social Media
Analytics
Data
Collection Statistics
Analytic Answers
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IBM SPSS Modeler Overview
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Business understanding
Data understanding
Data preparation
Modeling
Evaluation
Deployment
Data Mining Methodology – CRISP-DM
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IBM SPSS Modeler
• Easy-to-use, interactive interface without the
need for programming
• Automated modeling and data preparation
capabilities
• Access ALL data – structured and
unstructured – from disparate sources
• Natural Language Processing (NLP) to
extract concepts and sentiments in text
• Entity Analytics ensures the quality of the
data and results in more accurate models
• Leverage existing investment in Cognos,
Netezza, InfoSphere and System Z
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Monte Carlo Simulation
Generate simulated data
Fit distributions from existing data
Evaluate the simulation
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Classification and Prediction
Help to predict a result:
• Will a customer buy or leave
• Does transaction fit a known pattern of fraud
• Expected inventory levels
• Forecast number of widget purchases
Techniques included
• Decision Trees
• Bayesian Networks
• Neural Networks
• Decision List
• Statistical Models
• Time Series
• Self Learning Response Models
• Support Vector Models
• Nearest Neighbor Models
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Extend the Use of R
Build and score R models through Modeler GUI
Scale R execution by leveraging database
vendor provided R engines
Use R processes and generate output
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Delivering the Next Best Action
with Modeler
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Analytical Decision Management
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Decision management is an innovative business discipline that
combines a variety of techniques to optimize actions and outcomes
• Provide front-line employees
and systems with
recommended actions
• Empower real-time and
adaptive decisions
accommodating changing
conditions
• Optimize actions with
resource constraints, aligning
execution with strategy
Optimized decisions
+ + Business
rules Optimization Predictive
analytics
All data
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Automated Transactional Decisions and Actions Using Predictive
Analytics, Rules, Scoring and Optimization
Level Points
Low risk > -5
Medium risk > +1
High risk > +8
Front line staff and systems
benefit from recommendations,
offers and dashboards wherever
they are needed
Access ALL
data
• Structured
• Unstructure
d
• social
media
• business
intelligence
• performanc
e
managemet
t data
Rules Predictive analytics
Simulation and
optimization
Scoring
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Data Preparation
SPSS Modeler SPSS Modeler
Import Data
Cognos Package
Author Report
Create Report / Dashboard
SPSS Modeler and Cognos BI
Create Predictive Insight
Report / Dashboard
Consume Analytics Export Data
Cognos Package
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Thank You
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