HOW WE DID THE INVESTIGATIONS The Sad Case of StagnoBank – Part 1
Aug 20, 2015
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Prelude – Part 1
This deck accompanies the Sad Case of StagnoBank - Part 1 Videoat http://youtu.be/MScwTqhM3TI
You can find this with a search for “BSI”, “Teradata”, “Case”, “StagnoBank”.
It is designed to answer questions about the technology shown in the story
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Note from the Investigators
Hi Everybody,
We’re the brains behind the scenes and wanted to answer your questions about “how we did the StagnoBank brainstorming so fast.”
This write-up will give you an idea of our clients’ architecture and some details of the BI screens.
Take a look, and if you still have questions, send them to us! We’re both on Facebook.
Yours truly, Max Ridge and Jodice Blinco
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Scene Synopsis
• Jodice’s Office at BSI HQ – Simon explains the situation, shows Jodice KPIs and reports, and commissions the work
• Jodice kicks off the Project with Max, Mercedes, and Mathieu
4 Weeks Later
• BSI Conference Room – readout of ideas for Better Marketing (Max), Better Customer Service (Mercedes), and Mobile Apps (Matt)
• This deck show’s Max’s work – Part 1; see also Part 2 for Mercedes’ ideas, and Part 3 for Matt’s
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Summary of the Ideas from the BSI Team
Max Ideas Event Based Campaigns to increase relevance
GoldenPath Analysis to increase channeleffectiveness
Attribution Analytics and Digital Marketing Optimization
Mercedes Ideas “One and Done” screens for contact center agents
Customized button pushes on the Interactive Voice Response
Same agent call routing
Matt Ideas “Consumer Intelligence” budget / planning apps
“My Bank Looks Out for Me” alerts
“Geospatial Apps” to drive customer education
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Scene 1: Problems at StagnoBank! Meeting of Simon (CMO) and Jodice (BSI)
Simon and Jodice … in her office talking
• Simon: “I’m the new CMO, only on the job for 3 months, but everywhere I turn, we have problems”
• Biggest issue – we’re a big, old bank, perceived as “behind the times”. No appeal to younger households.
• Asks Jodice to do a quick BSI project to come with turnaround ideas
Simon, StagnoBank’s
CMO
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Summary of StagnoBank’s Problems
Business KPIs• Assets dropping• Margins eroding• Customer count dropping• Losing market share
Customer KPIs• Average age of customer is increasing• Decrease in take rates for offers• Bad customer service scores
Channel KPIs• Branch services under-utilized• Long wait times at the call center • Weak mobile and online banking offers
Jodice agrees to take on the assignment, will have her team do interviews and brainstorming
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KPIs Not Good: Assets and Margins Dropping
Q1-2010
Q2-2010
Q3-2010
Q4-2010
Q1-2011
Q2-2011
Q3-2011
Q4-2011
0
20
40
60
80
100
120
StagnoBank Assets By Quarter ($B)
ROA = return on assets
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Bank Results Are Not Good: Number of Accounts and Market Share
Q1-2010
Q2-2010
Q3-2010
Q4-2010
Q1-2011
Q2-2011
Q3-2011
Q4-2011
2.1
2.15
2.2
2.25
2.3
2.35
# Consumer Accounts (Millions)
Q1-2010
Q2-2010
Q3-2010
Q4-2010
Q1-2011
Q2-2011
Q3-2011
Q4-2011
1011121314151617181920
Market Share (%)
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Jodice Charters the Team
Jodice puts together a young team: Mathieu, Max, and Mercedes
She commissions them to:• Come up with Ideas for StagnoBank
– 3 each – 9 total• Go interview StagnoBank customers• Look at the bank’s data for yourself• Interview some customers• Work hard and come back in 4
weeks with your best ideas!
Mathieu
Max
Mercedes
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Assignments
• Max: Better Marketing
• Mercedes: Better Customer Service
• Mathieu: Consumer Mobile Apps, Alerts, Geo-Spatial
The Team Divides Up the Brainstorming
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Readouts
• 4 WEEKS LATER SIMON COMES OVER TO THE BSI HQ FOR A READOUT WITH THE BSI Team
• Each one of the 3 team members gets their timeslot to show off their best 3 ideas for their area. That makes 9 “ideas” in total for Simon.
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• This chart is from Aprimo’s integrated analytics suite- specifically Behavior Trend Analysis- which can show the behavior of any customer segment over time.
• Though not shown, Drill Down to the individuals included in any of these segments is available at any time. By merely pointing and clicking on these value bands, it is very quick and simple to generate a list of customers that have dropped out of the highest 10% of contributors to lower levels between any two time periods.
• This would allow you to either do further analysis on these customers, or quickly target them with promotions to re-engage them.
How We Did This Report
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The ProblemCross-Channel Campaigns – Also Not Good
# Contacts
# Contacts/ yr.
# Contacts/ mo.
Response %
762516
261665
308996
.076
No
IntersectionE-Mail
Direct Mail
# Contacts
# Responses
% Response
# Contacts
# Responses
% Response
4390888
28540
0.65%
4309933
30169
0.70%
4220493
29543
0.70%
4109253
28353
0.69%
4239803
28830
0.68%
4440982
35083
0.79%
4590363
31214
0.68%
4390222
31170
0.71%
1509231
10262
0.68%
APR11
DEC 11
NOV11
OCT11
SEP11
AUG11
JUL11
MAY11
JUN11
Any Household Age
4219031
30798
0.73%
MONTH
1652341
12392
0.75%
1567820
10661
0.68%
1340964
10157
0.75%
1459092
8608
0.59%
1520987
10190
0.67%
1429033
11432
0.80%
1590202
11608
0.73%
1490341
10432
0.70%
Way too many emails and direct mail pieces – about 3 per month per customer – and take rates are horrible
CAMPAIGN CONVERSION RATESMonthly response rates across channels – all segments: 1.3 – 1.5%
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• This slide shows another of Aprimo’s integrated analytics- Cross Segment Analysis.
• Here you can easily see the performance of various channels over time, and could also quickly change this chart to show the performance of any segment of customers, across channels, over time.
• So, for example, you could quickly substitute customer age ranges across the top and show the performance of different communications channels by age segments- or customer value segment, or by any other customer attribute.
How We Did This Report
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What 3 Ideas Did Max Come Up With forBETTER MARKETING?
Max Ideas Event Based Campaigns to increase relevance
GoldenPath Analysis to increase channeleffectiveness
Attribution Analytics and Digital Marketing Optimization
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• In this screen shot of Aprimo Relationship Manager, you can see an example of an event based (or complex trigger based) campaign. Event based campaigns allow you to watch for specific behaviors, or combinations of behaviors, by customers so that you can quickly respond with an appropriate message or offer.
• The Large Withdrawal which is the primary characteristic of this segment of customers actually implements a fairly complex rule to identify customer that have exhibited a specific behavior (or combination of behaviors) in the last x time period.
How We Did It
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• For example, a large deposit may be defined based on individual characteristics- so it might be calculated to identify customers who have made a deposit that is at least 500% greater than their individual average deposits over the last 12 months.
• This provides much greater accuracy and relevance than stipulating a set amount of deposit- so a $10,000 deposit may be a “large” deposit for one person, but might not be a big deal for someone else.
How We Did It
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• Likewise, an event trigger could be se tup for anyone who initiates an automatic deposit into their account- eliciting an automatic email from the bank, thanking them for signing up for direct deposit
• We could then possibly cross-sell other offers that have been found through analysis to be attractive to people who just started automatic deposits. The offers can be different, and even use different channels, based on any attribute of the new depositors.
• For example, for people in the targeted younger age group just starting a new job, we might offer> Consolidation of student loans> Car loans> New credit cards
How We Did It
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• See www.aprimo.com for tutorials and examples. The technology illustrated here is called ARM – Aprimo Relationship Manager
• Each industry at Teradata has built a set of interesting “Events” – the two events here are on the list of 200 interest events in the Banking Industry, and also are based on the Teradata Financial Logical Data Model (next page)
• The events are detected often during the ETL or ELT phase when loading data from a front-end transaction processing (OLTP) system
• Teradata then hands the event to Aprimo for “action” (or not), and it launches multi-channel, multi-step dialogues or campaigns
Event-Based Campaigns Are Run By Aprimo
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• A fragment of pseudo SQL, for example:
SITUATION: LIKELY ACCOUNT CANCEL AT-RISK EVENT: Unusually-Large-Withdrawal: DEFINED AS Current WithdrawalAmt > 5 * AVG(All Withdrawals)
SQL
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• Aprimo Relationship Manager allows you to create segments in 5 different ways:
- Segments can be created directly from analytics, as we saw earlier
- Segments can be imported from a third party, such as an analytics group, or MSP
- Segments can be created with a simple, point and click user interface, known as Selection Manager, that is a standard component of ARM
- Segments can be created by selecting tables and fields from the database, or
- Segments can be created from custom SQL that is written to address very complex scenarios
Creating Customer Segments with Aprimo
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Max Idea #2: Use GoldenPath Analysis
• Golden Path Analysis – once we agree to doing more event-based campaigns and aiming at new segments, we have to optimize their experiences.
• What is the PATH TO PURCHASE? How many steps? Which channels? How long does it take?
• Younger people will NOT put up with what you have now in terms of the mobile web experience … too many clicks
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• The technology for Goldenpath and Attribution Analytics is based on Teradata Aster, an acquisition Teradata made in 2011
• This technology is designed for use by “Data Scientists” who are familiar with SQL MapReduce and Hadoop technologies, especially suited in deriving insights from non-traditional data (e.g., data not easily structured in relational database tables)
• Web graph analytics fit into this class of BI, along with other categories not in this episode like finding fraud patterns
• Aster and Teradata sit “side by side”, as shown in the next page
An Aside: Aster
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Aster Data Analytic Platform Complements an Existing Teradata System
Brings data science to the masses
OLAP
Analytics
Reporting
Example Apps
Process Optimization
Teradata Integrated
Data Warehouse (or Appliance)
Scoring
SQ
L-M
apR
educe
Marketing Insights
Aster Data Analytic Platform
)
Fraud/Cheating Detection
Scoring and Behavioral Anomaly Analysis
Social Media Data Retention & Analysis
Investigative Analysis
Example Apps
FraudPrevention
RelationshipManagement
Integrated WebIntelligence
Investigate in Aster Data, Integrate &
Operationalize in the Data Warehouse
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Aster GoldenPath Analysis
Analyze behaviors – across all channels
Watch paths to purchase, and look for / fix problems in the paths to purchase
With Aster Data• SQL-MapReduce for pattern matching
can identify the “last mile”> E.g. Identify all interaction patterns
prior to an event of interest – like taking out a loan – and time spent on each channel
Impact• With 10-300x less effort, know when
customers are in the “last mile” of consideration
92,000 Online Sessions
25,000 ATM Sessions
userID event time
50001 Withdraw 12:00 PM
30001 Deposit 1:45 PM
10001 Inquiry 3:00 PM
30001 Deposit 12:20 PM
34,000 Branch Visits
userID event time
30001 Sent 12:00 PM
20001 Click 1:45 PM
30001 Open 3:00 PM
40001 Click 12:20 PM
4300 E-mails
userID event time
40001 Inquiry 12:00 PM
40001 Deposit 1:45 PM
20001 Withdraw 3:00 PM
20001 Home 12:20 PM
userID page time
10001 Home 12:00 PM
50001 Banking 1:45 PM
40001 Mortgage 3:00 PM
50001 Home 12:20 PM
Cross-Channel Customer Interactions
17,000 Customers, 1 Month
5,000 Call Center Sessions
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Sample Insights - GoldenPath
• Paid Ads on websites: average number of ad impressions to drive customer to our savings website: 10.8
• On the Stagnobank web: Number of web clicks to research (pre-app): 10
• Number of web fields to fill out a simple savings account application: 25 > Competitor Alpha: 12> Competitor Bravo:
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Queries
Big Data Analytics
Queen
Workers
Loaders/Exporters
SQL/MR
Aster Analytic Platform
How We Did It: Aster – Teradata Adapter
Big Data Sources Data Sources
TeradataIntegrated
Data Warehouse
Queries
Operational and Strategic Intelligence
Business Objects, etc
Teradata Integrated Data Warehourse
2- way Aster/TD Connector
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How Aster and Teradata Work Together
Social Media APIs
Raw Web Logs 3rd Party Data
CookieID UserID Attribution_Path
OLAPSQL
AnalyticsReporting
ERP E-POS Legacy Consumer
TeradataIntegrated Data Warehouse
Structured Insights(examples)
• Campaign/Media Costs• Marketing ROI Calculation• Customer Value
Aster Discovery Platform
Analytics Development
Analytic Processing
Parallel Data Storage
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How We Did It: Aster - Teradata Adapter Usage
• Customer Profile: StagnoBank is an existing Teradata Customer interested in doing detailed pattern and path analysis on clickstream data. Max installed an Aster system to do his analysis.
• Use Case: How to use an Aster Data system with Teradata to support Digital Marketing Optimization and Attribution
• Analytics Workflow:1. Load: Load data feeds from weblogs, Omniture, Doubleclick, etc to Aster
2. Analyze: Use SQL-MapReduce to perform pathing, attribution on the clickstream
3. Enrich: Enrich pathing analysis on clickstream with dimensional information from Teradata EDW
4. Implement: Move high-value customer ids to Teradata EDW. Implement marketing campaign using Aprimo Relationship Manager
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Conclusion #2: Fix Your Web Site
• Redesign it!
• Pay attention to what people are doing, how long it takes
• Optimize, especially compared to the competition
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Idea #3: Optimize Marketing Spend
• Attribution Analytics > Do you know what it costs to cause consumer behavior (like a
purchase)?> Can you attribute the cost to each channel (or previous
campaign)?
• Digital Marketing Optimization– Do you know how much to spend on the various elements of driving
consumer behavior?– Are your investments the right ones?
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Attribution Analysis and DMO –
Web / organic searchWeb /paid search
Call Center / agent
Web / organic
Branch /banker
Web / applicationCall Center / agent
Branch/banker
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• Analyzing complex sequences of customer behavior is another good use of Aster
• Those insights – what influenced sales of products or what behavior predict attrition – can then be fed into Aprimo and used to do Digital Marketing Optimization (DMO), which is part of Integrated Marketing Management (IMM)
• Unlike the campaign/dialogues parts of Aprimo, IMM focuses on optimizing marketing spend, or more to the point in this story, correlating spending and impact
• Putting this all together requires the complex behavior analytics from Aster, the historical context from Teradata, and the spending analytics from Aprimo
How We Did It
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TeradataIntegrated
Customer Hub
Marketing OperationsDatabase
Digital Marketing Attribution
(Aster Appliance)Spend
Management(Aprimo)
Multi-Channel Execution(Aprimo)
Teradata Integrated Channel Intelligence
Physical & Logical Model
Media
Call Center
POS
Web
Mobile
Social
Digital Marketing Attribution – Aster and AprimoFunctional Overview
44I/F to Other Apps
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Business UsersSAS Analyst
Dim
en
sio
nal
Data
(cu
stom
er
data
, m
eta
data
, …
)S
Inte
gra
ted
for 3
60
° R
ep
ortin
g
Teradata
Aster MPPAnalytic DBMS
Data Platforms
ETL Infrastructure
(Structured & Relational Data)
ETLData Sources
Core BankingSystem Data
Semi-structured Data- Machine logs- Clickstream- Tick-data
High Performance
Direct LoadingUnstructured Data- Text (social
media, email)- Sensor
DiverseData
Marketing
Users
DataScientists
BusinessUsers
Investigative Analysis
nPath Analysis
Business Applications
(Online & Mobile)
SQL, SQL-MapReduce
Analytics/Reporting
In-DatabaseAnalytics
Customer Management, Risk, Fraud,
FPM, Operations
CustomersMobile/Web
Multi-Channel Campaign
Management“ARM”
3rd Party Data- Credit Bureau- SaaS Provider
DataCloud
Cloud
APRIMO Marketing Studio
SAS IN-DB
BI Tools(Microstrategy, IBI, Tableau, Cognos)Mobile/Web
How Teradata Aster, Teradata, and Aprimo Fit Together in a Logical Banking Architecture
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Max Ideas on Better Marketing
• Which idea would you vote for?
Max Ideas Event Based Campaigns to increase relevance
GoldenPath Analysis to increase channeleffectiveness
Attribution Analytics to focus Marketing spending
Max #1 Max #2 Max #3
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For More Product Information
• If you’re in the banking industry, you may want to look at Teradata offers at http://www.teradata.com/industry-expertise/financial-services/
• For more Teradata and Aster Data product information, see: www.teradata.com, www.asterdata.com
• A good attribution paper is “Integrated Marketing Management: Using Multi-Touch Attribution for Deeper Insight into the Customer Journey”
• For more information on Aprimo Relationship Manager, see: http://www.aprimo.com/Products_.aspx?id=2265
• For more information on Aprimo Real Time Interaction Manager, see: http://www.aprimo.com/Products_.aspx?id=2266
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Check Out Mercedes’ and Matt’s Ideas, Too!See Part 2 and 3 StagnoBank videos on YouTube.com
2 - Mercedes:Better Customer Service
3 - Matt: Consumer Apps, Alerts, Geo
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Other BSI Episodes???
You can find more episodes at www.bsi-teradata.com or on YouTube (keywords: BSI Teradata Case):
> Case of the Defecting Telco Customers> Case of the Misconnecting Passengers> Case of the Credit Card Breach> Case of the Retail Tweeters> Case of the Fragrant Sleeper Hit> Case of the Dropped Mobile Calls
Corresponding “How We Did It” PowerPoints are available, too, at www.slideshare.net (keywords: BSI Teradata Case)