Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Sad Case of Stagno Bank - how we did it


Published on

BSI team recommends technologies from Teradata Aster and Aprimo, a Teradata company, for better marketing via event-based Marketing, GoldenPath Analytics, and Attribution/Digital Marketing Optimization.

Published in: Economy & Finance, Business
  • Be the first to comment

  • Be the first to like this

Sad Case of Stagno Bank - how we did it

  1. 1. HOW WE DID THE The Sad Case ofINVESTIGATIONS StagnoBank – Part 1
  2. 2. Prelude – Part 1This deck accompanies theSad Case of StagnoBank - Part 1 Videoat can find this with a search for “BSI”,“Teradata”, “Case”, “StagnoBank”.It is designed to answer questions about thetechnology shown in the story2
  3. 3. 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 Blinco3
  4. 4. 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 Mathieu4 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’s4
  5. 5. Summary of the Ideas from the BSI Team Max Ideas Event Based GoldenPath Attribution Campaigns to Analysis to Analytics and increase increase Digital relevance channel Marketing effectiveness Optimization Mercedes Ideas “One and Customized Same agent Done” button call routing screens for pushes on the contact Interactive center agents Voice Response Matt Ideas “Consumer “My Bank “Geospatial Intelligence” Looks Out for Apps” to budget / Me” alerts drive planning apps customer education5
  6. 6. 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 CMO6
  7. 7. Summary of StagnoBank’s ProblemsBusiness KPIs• Assets dropping• Margins eroding• Customer count dropping• Losing market shareCustomer KPIs• Average age of customer is increasing• Decrease in take rates for offers Jodice agrees to• Bad customer service scores take on theChannel KPIs assignment, will• Branch services under-utilized have her team do• Long wait times at the call center interviews and• Weak mobile and online banking offers brainstorming7
  8. 8. KPIs Not Good: Assets and Margins Dropping StagnoBank Assets By Quarter ($B)120100 80 60 40 20 0 ROA = return on assets 8
  9. 9. Bank Results Are Not Good: Number of Accounts and Market Share # Consumer Accounts (Millions)2.35 2.32.25 2.22.15 2.1 Market Share (%) 20 19 18 17 16 15 14 13 12 11 10 9
  10. 10. Bad Take Rates for Car and Credit Card Offers10 Goal is to reach 2.5% take rates for all campaigns
  11. 11. Jodice Charters the TeamJodice puts together a young team:Mathieu, Max, and MercedesShe commissions them to:• Come up with Ideas for StagnoBank – 3 each – 9 total• Go interview StagnoBank customers Max• Look at the bank’s data for yourself• Interview some customers Mathieu• Work hard and come back in 4 weeks with your best ideas! Mercedes 11
  12. 12. The Team Divides Up the BrainstormingAssignments• Max: Better Marketing• Mercedes: Better Customer Service• Mathieu: Consumer Mobile Apps, Alerts, Geo-Spatial12
  13. 13. 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.13
  14. 14. Scene 2: MAX – 3 Ideas for BetterMarketing14
  15. 15. The ProblemHigh Value Customers: Both # and % Drops15
  16. 16. How We Did This Report• 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.16
  17. 17. The ProblemCross-Channel Campaigns – Also Not Good Any Household Age MONTH APR MAY JUN JUL AUG SEP OCT NOV DEC 11 11 11 11 11 11 11 11 11 4219031 4390888 4309933 4220493 4390222 4109253 4239803 4440982 4590363 # Contacts No E-Mail Intersection 30798 # Responses 28540 30169 29543 31170 28353 28830 35083 31214 % Response 0.73% 0.65% 0.70% 0.70% 0.71% 0.69% 0.68% 0.79% 0.68% # Contacts 1652341 # Contacts 1567820 762516 1429033 1520987 1459092 1340964 1590202 1490341 1509231 Direct # Contacts/ yr. 261665 # Responses 12392 10661 11432 10190 8608 10157 11608 10432 10262 Mail % Response # Contacts/ mo. 308996 0.75% Response % 0.68%.076 0.80% 0.67% 0.59% 0.75% 0.73% 0.70% 0.68% CAMPAIGN CONVERSION RATES Monthly response rates across channels – all segments: 1.3 – 1.5%Way too many emails and direct mail pieces – about 3 per month per customer – and take rates are horrible17
  18. 18. How We Did This Report• 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.18
  19. 19. What 3 Ideas Did Max Come Up With forBETTER MARKETING? Max Ideas Event Based GoldenPath Attribution Campaigns to Analysis to Analytics and increase increase Digital relevance channel Marketing effectiveness Optimization19
  20. 20. Max Idea #1: Move to Event Based CampaignsExample: Large Withdrawal Triggers Phone Call20
  21. 21. How We Did It• 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.21
  22. 22. How We Did It• 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.22
  23. 23. Event Based Campaign for Auto-Deposit23
  24. 24. How We Did It• 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 cards24
  25. 25. Event-Based Campaigns Are Run By Aprimo • See 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 campaigns25
  26. 26. Use Teradata’s Financial Logical Data Model26
  27. 27. SQL • 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)27
  28. 28. Creating Customer Segments with Aprimo• 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 scenarios28
  29. 29. 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 clicks29
  30. 30. What products are most popular with youngadults in the last month?30
  31. 31. Response Rates By Channel (Across All Offers)For Younger Households are Poor31
  32. 32. An Aside: Aster• 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 page32
  33. 33. Aster Data Analytic Platform Complements an Existing Teradata SystemBrings data science to the masses Aster Data Teradata Integrated Analytic Platform Data Warehouse ) (or Appliance) Example Apps Investigative Analysis Example Apps Social Media Data SQL-MapReduce Integrated Web Retention & Analysis Intelligence OLAP Scoring and Behavioral Investigate in Relationship Scoring Anomaly Analysis Aster Data, Management Integrate & Operationalize Analytics Fraud/Cheating Fraud Detection in the Data Prevention Warehouse Reporting Marketing Insights Process Optimization 33
  34. 34. Aster GoldenPath AnalysisAnalyze behaviors – across all Cross-Channel Customer Interactions channels 17,000 Customers, 1 MonthWatch paths to purchase, and look for / fix problems in the paths to purchase 34,000 Branch Visits 25,000 ATM Sessions userID event time userID event time 50001 Withdraw 12:00 PM 40001 Inquiry 12:00 PMWith Aster Data 30001 Deposit 1:45 PM 40001 Deposit 1:45 PM• SQL-MapReduce for pattern matching 10001 Inquiry 3:00 PM 20001 Withdraw 3:00 PM can identify the “last mile” 30001 Deposit 12:20 PM 20001 Home 12:20 PM > E.g. Identify all interaction patterns prior to an event of 5,000 Call Center Sessions interest – like taking out a loan – 4300 E-mails 92,000 Online Sessions and time spent on each channel userID event time userID page timeImpact 30001 Sent 12:00 PM 10001 Home 12:00 PM• With 10-300x less effort, know when 20001 Click 1:45 PM 50001 Banking 1:45 PM customers are in the “last mile” of 30001 Open 3:00 PM 40001 Mortgage 3:00 PM consideration 40001 Click 12:20 PM 50001 Home 12:20 PM 34
  35. 35. 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: 14 35
  36. 36. Where Do People Drop out when Opening a Savings Account on the Website?36
  37. 37. How We Did It: Aster – Teradata Adapter Operational and Strategic Big Data Analytics Intelligence Business Objects, etc Queries Queries Queen Workers Teradata Integrated SQL/MR Data Warehouse Loaders/Exporters 2- way Aster/TD ConnectorBig Data Sources Aster Analytic Platform Teradata Integrated Data Sources Data Warehourse 37
  38. 38. How Aster and Teradata Work Together CookieID UserID Attribution_PathAster Discovery Platform Teradata Analytics Development Integrated Data Warehouse Analytic Processing Structured Insights (examples) Parallel Data Storage • Campaign/Media Costs • Marketing ROI Calculation • Customer Value Raw Web Logs Social Media 3rd Party Data SQL OLAP Reporting APIs Analytics ERP E-POS Legacy Consumer38
  39. 39. 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 39
  40. 40. 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 40
  41. 41. 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?41
  42. 42. Attribution Analysis and DMO – Web /paid search Web / organic search Call Center / agent Web / organic Branch /banker Web / application Call Center / agent Branch/banker42
  43. 43. How We Did It• 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 Aprimo43
  44. 44. Digital Marketing Attribution – Aster and Aprimo Functional Overview Social Digital Marketing Attribution Spend Mobile (Aster Appliance) Management (Aprimo) Web Teradata Integrated Multi-Channel Channel Intelligence Physical & Logical Model Execution POS (Aprimo) Call Center Teradata Marketing Operations Integrated Database Media Customer Hub44 44 I/F to Other Apps
  45. 45. How Teradata Aster, Teradata, and Aprimo Fit Together in a Logical Banking Architecture Data Sources ETL Data Platforms Analytics/Reporting Users High Performance Aster MPPUnstructured SQL, SQL-MapReduceData Direct Loading Analytic DBMS Data- Text (social In-Database Investigative Scientists media, email) Analytics Analysis- Sensor Diverse Data nPath AnalysisSemi- Customer Business (customer data, metadata, …)structured Data Management,- Machine logs Users Risk, Fraud, SIntegrated for 360°- Clickstream FPM, Operations Dimensional Data- Tick-data APRIMO Marketing Studio ReportingCore Banking Multi-Channel CampaignSystem Data Marketing ETL Management Infrastructure “ARM” (Structured & Relational Data) Business Customers Applications Mobile/Web3rd Party Data (Online & Mobile)-- Credit Bureau SaaS Provider Teradata SAS IN-DB Data Cloud BI Tools Business Users (Microstrategy, IBI, SAS Analyst Mobile/Web 45 Tableau, Cognos)
  46. 46. Results – Idea #346
  47. 47. Max Ideas on Better Marketing• Which idea would you vote for? Max Ideas Event Based GoldenPath Attribution Campaigns to Analysis to Analytics to increase increase focus relevance channel Marketing effectiveness spending Max #1 Max #2 Max #347
  48. 48. Vote for Max !48
  49. 49. For More Product Information• If you’re in the banking industry, you may want to look at Teradata offers at expertise/financial-services/• For more Teradata and Aster Data product information, see:,• 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:• For more information on Aprimo Real Time Interaction Manager, see:
  50. 50. Check Out Mercedes’ and Matt’s Ideas, Too!See Part 2 and 3 StagnoBank videos on 3 - Matt: Consumer Apps, Alerts, Geo2-Mercedes:BetterCustomerService50
  51. 51. Other BSI Episodes???You can find more episodes at or onYouTube (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 CallsCorresponding “How We Did It” PowerPoints are available, too, (keywords: BSI Teradata Case)51