DIGITAL BANK GROWTH – LEARNING LAUNCH APPROACH 

 Challenge & selection 

 I ’m part of the product team at the first digital bank in a developing country in South East Asia . We have   launched our digital product , which is a current account and debit card ( as a bundle ) opened 100 %   online via eKYC in partnership with a software company who provides solutions to fraud prevention and   credit data scoring ( “ trust score ” ) . With this convenience , we have more than 2000 customers registered   on daily average . However , after careful analysis , we realized that this number is mostly “ registered   customers ” to receive our onboarding gift ( vouchers and cash - back benefits ) , not a loyal/ long - term   customer . This means we are facing financial loss by giving offers to customers who wo n’t stay with us .   For this reason , our team is conducting data analysis to gain an insight about customer behaviors and   patterns of usage upon opening our product vs what the other rival banks are offering to turn “ one - time   customers ” to “ loyal customers ” . I chose the learning launch approach because the marketing growth   team has come up with a lot of interesting ideas ( via crowd - sourcing and competitive landscape analysis   and even rich experience ) and this approach allows us to test whether one idea is validated as a   business opportunity and worths investment . 

 Application 

 First , we reconsider our registration process to see if a better filtering/ categorization of potential   customers can be obtained ( how they know about our products – organic , social media , affiliated links ,   etc . and whether they have accounts at other banks as well as their daily spending behaviors ) . As we   have realized the gap to be improved internally , we started working with our vendor to enhance the   process as well as system compatibility . After some enhancements , our product team developed test   cases and started testing the enhanced environment before going live . We created many profiles of   persona to check if the filtering/ categorization works well . The whole process will take approximately 1   month from idea initiation to going live updated version . 

 Next , with these qualified customers , we started tracking their behaviors with weekly reports ( times   logged in/ out , numbers of purchases made per week , the average amount spent , on which platforms ,   linked to any e - wallet , etc . ) . From such , hypothesis can be generated . For example , a large amount of   customers aged between 25 - 40 tend to use the account to pay for electricity/ water bills and make   purchases on e - commerce . Then we can think of : 

 1 . Launching the cash - back scheme for those who use their account to make electricity/ water   bills . ( The finance team then started calculated the good ratio of cash back so that the bank can   make some marginal profit )   2 . Establishing partnerships with the e - commerce companies for discount vouchers to those who   use the bank account to make payments 

 The aim of these initiatives is in the end retaining valuable and lifelong customers who will bring profits   to our bank . 

 For each of these schemes , we designed a survey to ask for customers ’ selection and whichever wins will   be launched first within one - month trial timeframe . We continue tracking customers ’ behaviors with 

 this new campaigns to see their reactions and decide whether to move on with it or consider other   alternatives . 

 Insights 

 With this approach , our marketing team and product team have coordinated to make assumptions and   launched them to verify the effectiveness . We have compared the expected results to the realistic ones   which display quite a gap . We have been able to identity it , revise and improve it as a long - term project   with clearly defined KPIs . 

 Approach 

 Depending on the problems to solved next time , either this approach or others ( visualization , story   telling , mind mapping ) will be applied . 


EMAIL: 
ID_NUM: 
NAME_STUDENT: 
PHONE_NUM: 
STREET_ADDRESS: 
URL_PERSONAL: 
USERNAME: 

### Task: You are a PII (Personal Identity Information) Detection. Given a essays written by students, you have to identify ONLY the following:
NAME_STUDENT - The full or partial name of a student that is not necessarily the author of the essay. This excludes instructors, authors, and other person names.
EMAIL - A student’s email address.
USERNAME - A student's username on any platform.
ID_NUM - A number or sequence of characters that could be used to identify a student, such as a student ID or a social security number.
PHONE_NUM - A phone number associated with a student.
URL_PERSONAL - A URL that might be used to identify a student.
STREET_ADDRESS - A full or partial street address that is associated with the student, such as their home address.
### Input: DIGITAL BANK GROWTH – LEARNING LAUNCH APPROACH 

 Challenge & selection 

 I ’m part of the product team at the first digital bank in a developing country in South East Asia . We have   launched our digital product , which is a current account and debit card ( as a bundle ) opened 100 %   online via eKYC in partnership with a software company who provides solutions to fraud prevention and   credit data scoring ( “ trust score ” ) . With this convenience , we have more than 2000 customers registered   on daily average . However , after careful analysis , we realized that this number is mostly “ registered   customers ” to receive our onboarding gift ( vouchers and cash - back benefits ) , not a loyal/ long - term   customer . This means we are facing financial loss by giving offers to customers who wo n’t stay with us .   For this reason , our team is conducting data analysis to gain an insight about customer behaviors and   patterns of usage upon opening our product vs what the other rival banks are offering to turn “ one - time   customers ” to “ loyal customers ” . I chose the learning launch approach because the marketing growth   team has come up with a lot of interesting ideas ( via crowd - sourcing and competitive landscape analysis   and even rich experience ) and this approach allows us to test whether one idea is validated as a   business opportunity and worths investment . 

 Application 

 First , we reconsider our registration process to see if a better filtering/ categorization of potential   customers can be obtained ( how they know about our products – organic , social media , affiliated links ,   etc . and whether they have accounts at other banks as well as their daily spending behaviors ) . As we   have realized the gap to be improved internally , we started working with our vendor to enhance the   process as well as system compatibility . After some enhancements , our product team developed test   cases and started testing the enhanced environment before going live . We created many profiles of   persona to check if the filtering/ categorization works well . The whole process will take approximately 1   month from idea initiation to going live updated version . 

 Next , with these qualified customers , we started tracking their behaviors with weekly reports ( times   logged in/ out , numbers of purchases made per week , the average amount spent , on which platforms ,   linked to any e - wallet , etc . ) . From such , hypothesis can be generated . For example , a large amount of   customers aged between 25 - 40 tend to use the account to pay for electricity/ water bills and make   purchases on e - commerce . Then we can think of : 

 1 . Launching the cash - back scheme for those who use their account to make electricity/ water   bills . ( The finance team then started calculated the good ratio of cash back so that the bank can   make some marginal profit )   2 . Establishing partnerships with the e - commerce companies for discount vouchers to those who   use the bank account to make payments 

 The aim of these initiatives is in the end retaining valuable and lifelong customers who will bring profits   to our bank . 

 For each of these schemes , we designed a survey to ask for customers ’ selection and whichever wins will   be launched first within one - month trial timeframe . We continue tracking customers ’ behaviors with 

 this new campaigns to see their reactions and decide whether to move on with it or consider other   alternatives . 

 Insights 

 With this approach , our marketing team and product team have coordinated to make assumptions and   launched them to verify the effectiveness . We have compared the expected results to the realistic ones   which display quite a gap . We have been able to identity it , revise and improve it as a long - term project   with clearly defined KPIs . 

 Approach 

 Depending on the problems to solved next time , either this approach or others ( visualization , story   telling , mind mapping ) will be applied .
### Output: 