Challenge    I am a member of a Big Telecom Company where we have a challenge to improve   booked revenue in recharge card revenue stream as old way of having non   expired recharged value leads to have more un - booked revenue with no   guarantee on having a direct booked revenue as certain time line for non - active   customer , so we have challenge to increase percentage of booked revenue along   with maintaining better customer experience by giving the customer what they   really need .       Selection    Our team has decided to use learning launch design thinking tool as provided   challenge will be more realistic to have a clear outputs of customer needs from   small experiments and prototypes to check customer behavior directly from small   group of running customers        Application    For our first learning launch , we focus on new application to introduce new   prototype time limited bundles with better Customer value bundle and we tested   our assumption in one denomination only in our platform with small group of real   customer in order to measure customer feedback along with anonymous survey   for new application feedback      For our second learning launch , we have focused in availing new bundle with   different sets of traffic cases ( voice / MI/ Social MI /SMS ) availing new prototypes   and testing our new application with different set of customers with different   Customer behaviors along with checking the effects of this approach with booked   revenues growth     Insight    By applying the learning launch tool , our team identified our assumptions and   designed launches to test these assumptions . Additionally , we thought through   anticipated results , confirming that Booked revenue has been improved   significantly along with better customer experience for availing the customer   what they really need along with better value for money for their consumption 

 also from different ways of having customer feedbacks , we have find several   concerns regarding our approach including beneficial inputs for new approach   handling such as ( carryover of old bundle , enhanced set of traffic case , acquisition   promo ) that was taking in consideration before full rollout in all needed   denomination/ set of traffic cases       Approach    We have gone through different learning launch tool checks ; the learning launch   is the appropriate tool . As previously mentioned , we have review the insight   inputs and used it to enrich our current experience for recharge platform to reach   a significant improvement regarding customer experience along with enhance   booked revenue growth . 


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: Challenge    I am a member of a Big Telecom Company where we have a challenge to improve   booked revenue in recharge card revenue stream as old way of having non   expired recharged value leads to have more un - booked revenue with no   guarantee on having a direct booked revenue as certain time line for non - active   customer , so we have challenge to increase percentage of booked revenue along   with maintaining better customer experience by giving the customer what they   really need .       Selection    Our team has decided to use learning launch design thinking tool as provided   challenge will be more realistic to have a clear outputs of customer needs from   small experiments and prototypes to check customer behavior directly from small   group of running customers        Application    For our first learning launch , we focus on new application to introduce new   prototype time limited bundles with better Customer value bundle and we tested   our assumption in one denomination only in our platform with small group of real   customer in order to measure customer feedback along with anonymous survey   for new application feedback      For our second learning launch , we have focused in availing new bundle with   different sets of traffic cases ( voice / MI/ Social MI /SMS ) availing new prototypes   and testing our new application with different set of customers with different   Customer behaviors along with checking the effects of this approach with booked   revenues growth     Insight    By applying the learning launch tool , our team identified our assumptions and   designed launches to test these assumptions . Additionally , we thought through   anticipated results , confirming that Booked revenue has been improved   significantly along with better customer experience for availing the customer   what they really need along with better value for money for their consumption 

 also from different ways of having customer feedbacks , we have find several   concerns regarding our approach including beneficial inputs for new approach   handling such as ( carryover of old bundle , enhanced set of traffic case , acquisition   promo ) that was taking in consideration before full rollout in all needed   denomination/ set of traffic cases       Approach    We have gone through different learning launch tool checks ; the learning launch   is the appropriate tool . As previously mentioned , we have review the insight   inputs and used it to enrich our current experience for recharge platform to reach   a significant improvement regarding customer experience along with enhance   booked revenue growth .
### Output: 