Reflection 

 Challenge   &   Selection 

 In   our   business ,   we   have   a   mobile   app   for   customers   for   booking   multiple   types   of   on - demand     services .   As   processes   and   customers   are   already   somewhat   established .   We   currently   work   on     iterative   cycles   to   roll   out   improvements   and   new   features . 

 I   chose   the   learning   launch   to   test   out   new   features   for   a   small   set   of   targeted   users ,   collect   the     data   and   analyse   it   together   with   the   team   to   decide   next   steps . 

 Application 

 The   process   usually   starts   from   a   problem   or   business   objective ,   including   but   not   limited   to 

 - Many   users   are   unhappy   with   a   feature 

 - Customer   churn 

 - Setting   prices ,   discounts ,   promotion   campaigns ,   rewards 

 - External   factors   such   as   government   regulations ,   COVID   etc . 

 The   team   reviews   the   problems ,   discusses   some   ideas   and   decides   on   1   or   maybe   2   ideas     using   AB   testing . 

 The   feature   is   then   developed ,   QA   tested ,   and   tested   internally   on   staging   environments . 

 Next   up ,   data   is   used   to   select   a   small   set   of   users   that   meet   the   criteria ,   usually   20 %   for   most     scenarios ,   and   define   the   data   metrics   for   the   key   performance   indicators . 

 Once   ready ,   we   prepare   the   necessary   communications   to   the   user   including   time - frame   e.g.   2     weeks   and   a   call - to - action 

 The   feature   is   launched ,   monitored   closely   on   dashboards .   The   team   then   reviews   the   data ,     user   sentiments ,   feedback   and   decides   whether   to   push   the   feature   to   more   users     progressively .   Otherwise ,   the   feature   could   be   either   modified   for   a   re - test   or   be   removed . 

 Insight 

 The   tool   lets   us   test   out   new   features   for   a   small   set   of   users ,   while   also   keeping   the   business     running .   This   minimizes   risks   and   impact . 

 Approach 

 The   learning   launch   tool   can   be   used   in   many   ways ,   e.g   with   story   telling   by   inviting   5   users     individually    for   a   face   to   face   controlled   sesion .   A   story   teller   will   guide   and   let   them   try   out   the     new   app   physically   and   we   document   the   observations . 


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: Reflection 

 Challenge   &   Selection 

 In   our   business ,   we   have   a   mobile   app   for   customers   for   booking   multiple   types   of   on - demand     services .   As   processes   and   customers   are   already   somewhat   established .   We   currently   work   on     iterative   cycles   to   roll   out   improvements   and   new   features . 

 I   chose   the   learning   launch   to   test   out   new   features   for   a   small   set   of   targeted   users ,   collect   the     data   and   analyse   it   together   with   the   team   to   decide   next   steps . 

 Application 

 The   process   usually   starts   from   a   problem   or   business   objective ,   including   but   not   limited   to 

 - Many   users   are   unhappy   with   a   feature 

 - Customer   churn 

 - Setting   prices ,   discounts ,   promotion   campaigns ,   rewards 

 - External   factors   such   as   government   regulations ,   COVID   etc . 

 The   team   reviews   the   problems ,   discusses   some   ideas   and   decides   on   1   or   maybe   2   ideas     using   AB   testing . 

 The   feature   is   then   developed ,   QA   tested ,   and   tested   internally   on   staging   environments . 

 Next   up ,   data   is   used   to   select   a   small   set   of   users   that   meet   the   criteria ,   usually   20 %   for   most     scenarios ,   and   define   the   data   metrics   for   the   key   performance   indicators . 

 Once   ready ,   we   prepare   the   necessary   communications   to   the   user   including   time - frame   e.g.   2     weeks   and   a   call - to - action 

 The   feature   is   launched ,   monitored   closely   on   dashboards .   The   team   then   reviews   the   data ,     user   sentiments ,   feedback   and   decides   whether   to   push   the   feature   to   more   users     progressively .   Otherwise ,   the   feature   could   be   either   modified   for   a   re - test   or   be   removed . 

 Insight 

 The   tool   lets   us   test   out   new   features   for   a   small   set   of   users ,   while   also   keeping   the   business     running .   This   minimizes   risks   and   impact . 

 Approach 

 The   learning   launch   tool   can   be   used   in   many   ways ,   e.g   with   story   telling   by   inviting   5   users     individually    for   a   face   to   face   controlled   sesion .   A   story   teller   will   guide   and   let   them   try   out   the     new   app   physically   and   we   document   the   observations .
### Output: 