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Leveraging Big Data Analytics for Business Value
John Carter CAO Conference, October 2017 SVP, Analytics & Business Insight
Charles Schwab
Agenda
What is happening in industry
Schwab approach and journey
− Defining a big data analytics journey
− Delivering use cases that deliver value
− How Data Science is evolving analytics
− Key partnerships with data and technology organizations
Critical success factors
Chief Analytics Officer Conference, Oct 2017 - John Carter Presentation
Charles Schwab Chief Analytics Officer Conference, Oct 2017 - John Carter Presentation
Data, analytics & technology is exploding!
Weblogs
Speech/Text
Artificial Intelligence
Big Data
Python and R
Hadoop & Spark
Machine Learning
Social Data Feeds Real-Time Decisions
Pattern Recognition
Cognitive Computing
In-Memory DB
Charles Schwab
Executives are expecting much more from analytics…
Chief Analytics Officer Conference, Oct 2017 - John Carter Presentation
Big Expectations for Big Data in 2016
Splice Machine
Big Data Predictions…Companies want to personalize
cross-channel experiences based on real time
information and not day old data….
How companies are using big data and analytics
McKinsey & Company
Just how do major organizations
use data and analytics to inform strategic and
operational decisions?
Ten Ways Big Data Is Revolutionizing Marketing and
Sales
Forbes May 9, 2016
Customer Value Analytics (CVA) based on Big Data is
making it… A Forrester study found that 44% B2C marketers
are using big data and analytics to…
Charles Schwab
Companies are investing in big data….
..for greater insights and faster decisions
Chief Analytics Officer Conference, Oct 2017 - John Carter Presentation
*Source: NVP Big Data Executive Survey
0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0% 40.0%
Greater business insights
Faster time-to-answer
Faster speed-to-market
Greater analytics capabilties
Create a data-driven culture
Business Drivers of Big Data
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
40.0%
$1B+ $500M+ $100M+
Big Data Investment Last 5 Years Big Data Investment Last 5 Years
Charles Schwab Chief Analytics Officer Conference, Oct 2017 - John Carter Presentation
Yet, many analytical investments are NOT driving business value or outcomes!
• Accenture research shows that 1/3 of
companies are now using analytics
aggressively across the enterprise. Yet, for
many, the ROI is elusive.
— Only 22 percent of companies are
“very satisfied” with the outcomes of
their analytics investment
• Actionable insight to drive business often
appears to be the missing link between data
and business outcome
– According to Forrester, 74% of firms
say they want to be “data-driven,” but
only 29% are successful at
connecting analytics to action
Charles Schwab
Today we will share our Big Data Analytics Journey
Chief Analytics Officer Conference, Oct 2017 - John Carter Presentation
Charles Schwab
We started our Big Data Analytics journey 5 years ago by identifying the key data issues
Chief Analytics Officer Conference, Oct 2017 - John Carter Presentation
Inconsistent data definitions
Difficulty in accessing data
Key data about clients and prospects not captured
Proliferation of different system implementations across the firm
Limited documentation and metadata
Lack of change control processes
Limited funding for major data infrastructure projects
Charles Schwab
Our primary focus was chosen to deliver the greatest value in the most timely manner
Chief Analytics Officer Conference, Oct 2017 - John Carter Presentation
Inconsistent data definitions
Difficulty in accessing data
Key data about clients and prospects not captured
Proliferation of different system implementations across the firm
Limited documentation and metadata
Lack of change control processes
Limited funding for major data infrastructure projects
Charles Schwab
Our initial ‘Big Data’ repository was developed to provide a comprehensive view of client & prospect interactions
Chief Analytics Officer Conference, Oct 2017 - John Carter Presentation
Big Data enables us to understand how customers and prospects engage with Schwab and relate
their engagement to business outcomes
USE CASES
Shopping
Journey
Analytics
Cross
Channel
Attribution
Attrition /
Big Mover
Next
Best
Conversation
Deeper
Insights
Online Interactions
Schwab.com visits
Display Ad impressions & clicks
Paid Search clicks
Organic search clicks
Chat sessions & transcripts
Mobile web visits
Mobile app interactions
Post-Conversion Events
Assets In, Assets Out, Trades
Conversion Events
Account opens, New-to-Firm
households, offer enrollments
Account open channel
New-to-Firm household
segmentation
Offline Interactions
Branch appointments
Branch activities & opportunities
Direct Marketing campaigns
Phone interactions – who & when
Phone interactions – why via
Speech Analytics
Charles Schwab
We selected specific use cases to drive business value
Chief Analytics Officer Conference, Oct 2017 - John Carter Presentation
Shopping Journey
Analytics
• Increase acquisition and funding by providing key insights to change
interaction model with prospects and new clients
Cross-Channel
Attribution
• Improve ROI by determining how to optimize marketing campaigns
across channels
Attrition / Big Mover • Prevent attrition and/or large competitive outflows through pro-active
actions
Next Best
Conversation
• Improve client service and cross-sell opportunities by providing relevant
messages and offers to clients
Deeper Insights • Drive product innovation and enhance client experiences with new client
insights
Charles Schwab
Initial use case provided deep insights to address key
questions about the Prospect Shopping Journey
Chief Analytics Officer Conference, Oct 2017 - John Carter Presentation
Key Questions
What are the key prospect touchpoints prior to conversion?
How long does it take for prospects to convert from their first Schwab
interaction?
What are the most common paths prior to conversion?
Are there differences in how Affluent vs. non-Affluent prospects choose to
interact with Schwab?
Are there certain interactions that happen most often at the start of the
conversation with Schwab? Or near the end, closer to conversion?
How do post-account opening interactions drive funding?
Similar analyses have been conducted for other client journeys
Charles Schwab
Cross Channel Attribution uses advanced analytics to optimize marketing by campaign and touch point
Chief Analytics Officer Conference, Oct 2017 - John Carter Presentation
Interacted online
& offline
Richard
Johnson Base
Jan 15-19 Jan 22 Jan 19 Jan 23 Jan 23
Site
Display Site Visit
Inbound
Call Outbound
Call
Branch
Meeting
Schwab Assets = $285 k
Online Offline
The model allocates value to each touch point within the journey
15% 15% 10% 10% 20% TOT: 70% FRACTIONAL
CREDIT
(ILLUSTRATIVE)
Charles Schwab
We leveraged big data and machine learning to
deliver personalized messages
Chief Analytics Officer Conference, Oct 2017 - John Carter Presentation
Leverages real-time
decisioning engine that
continually learns based
on prior activity
Delivers best “offer” (sales
and service) from over
200 offers
Conversion rates are
significantly higher than
control
Intelligent Targeting
Targeted banners on
Schwab.com
Next Best
Conversation
Aims to deliver “next
best conversation” in
call center
Leverages real-time
decisioning engine
Selects offers /
messages tuned to live
interactions
Future
More unstructured and
real-time data
More sophisticated
machine learning
algorithms
More channels
Charles Schwab
Data Science is the next transformational evolution in our analytics journey
Chief Analytics Officer Conference, Oct 2017 - John Carter Presentation
Monitoring
Insights
Optimization
Transformation
Traditional Analytics
• Descriptive Analytics
• Structured Data
• Large data sets
• Leverages tried & true technologies
– Teradata
– SAS
– Business Objects
Data Science
• Predictive and Prescriptive Analytics
• Unstructured Data, Text and Voice
• Huge volumes of data processed at scale
• Open source, open architecture
• Encompasses leading technologies
– Hadoop distributed environment that can
store and process all kinds of data at scale
– Python, Spark, R
– Natural Language Processing
– Machine Learning/ AI
– Deep learning
– Neural Networks
Charles Schwab Chief Analytics Officer Conference, Oct 2017 - John Carter Presentation
We are building and implementing Data Science capabilities at Schwab
Hired a small group of talented PhD data scientists
Deep expertise in AI, Machine learning, Natural language processing, Deep
learning, etc. with focus on latest open source tools and technologies
Cross-trained existing advanced analytical team on data science capabilities
Contracted with an outsourced analytical firm in India, to build out enhanced data science capabilities
Building an enhanced technology and data foundation with our data and technology organizations to create, store and deliver massive amounts of user and interaction level data and create scalable platform
Charles Schwab Chief Analytics Officer Conference, Oct 2017 - John Carter Presentation
We partner closely with Global Data Office and Technology to drive analytics & insights from data
Provisioning data Driving insights from data
Delivering new
capabilities and
managing data operations
Global Data Office Analytics & Business Insight
Schwab Technology
Leverage data to create
competitive advantage
Charles Schwab Chief Analytics Officer Conference, Oct 2017 - John Carter Presentation
We are building a robust Data Science platform to scale Machine Learning successfully at Schwab
1. Data exploration — requires easy/automated access and connectors to various raw and composite data sources
2. Model development — involves iterative explorations on algorithms, techniques and outcomes to arrive at final models
3. Model testing — test final candidate models with live production data and select best model
4. Model deployment — deliver finalized model into production systems via APIs or other methods
5. Model monitoring — tracking and visualization of model performance for the business and MRM
Our objective is to ultimately make all 5 stages as automated as possible
A typical ML model has five stages:
Machine
Learning
Model
Lifecycle
I
5
2
Exploratory Data
Analysis &
Aggregation
Model Testing in
Production
Monitoring,
Tracking &
Visualization
Model
Deployment
Production
Model
Development
& Approval
3
4
Charles Schwab Chief Analytics Officer Conference, Oct 2017 - John Carter Presentation
We are focused on delivering a variety of Data Science projects to drive business impact
Financial Consultant Practice
Assignment Optimization
Lead Scoring Machine Learning
Call Center Routing and Rep
Optimization
Lifetime Customer Value
First Year Client path analysis and
lead routing
Early Warning System of Retention
Sales and Service Optimization Client Experience
New to Firm
Employee Attrition Model
Real-time deliver of client insights for
rapid response
Enterprise Fraud Engine
Corporate Support (HR, Finance)
Prospect segmentation and shopping
journey analysis
Social intelligence through NLP/NLG
Machine-learning for retargeting and
digital media buying
Charles Schwab Chief Analytics Officer Conference, Oct 2017 - John Carter Presentation
We have made significant improvements with our attrition model using Machine Learning
69
112
134
154
172
182
196
206
218
225
57
79
97
120
136 147
157
167
177
196
0
50
100
150
200
250
New Machine Learning models
Traditional models
# of Households
# o
f A
ttrito
rs
69
Charles Schwab Chief Analytics Officer Conference, Oct 2017 - John Carter Presentation
Critical Success Factors…
1. Gain executive support and align projects to top initiatives
2. Select projects that deliver immediate value, i.e. put points on the board early
and often
3. Ensure end-to-end implementation of analytics including measurement and
feedback
4. Involve and gain support of stakeholders in the project
5. Hire, develop and motivate your team
6. Partner with data and technology to build capabilities to support full analytics
lifecycle
7. Communicate accomplishments widely and often
8. Recognize that big data analytics is a journey
Charles Schwab
Q&A
Chief Analytics Officer Conference, Oct 2017 - John Carter Presentation
Thank you!
John Carter [email protected]
Chief Analytics Officer Conference, Oct 2017 - John Carter Presentation