Selfcare Application Learning Launch 

 Challenge   I work as a software development manager at a telecommunications company which is seeking   to go beyond its traditional services , such as voice calls and value - added services . To establish   this vision , the company created a new division , called Digital , aimed at creating new digital   revenue streams . This division then started a series of design thinking activities that resulted in   several promising ideas . One of these ideas , for which I was in charge , was to transform our   Selfcare mobile application into a SuperApp that would enable our users to enjoy digital services   as well . These services could range from e - governmental ( such as utility bill and toll payment ) to   e - tourism ( such as ticket and hotel reservation ) and even entertainment ( such as watching live   TV channels ) . Our ultimate goal was to provides almost every service that the users need . In this   way , the users could use our application for most of their day to day activities , and the company   could establish new digital revenue streams it envisioned . However , around 30 % of the   company ’s revenue was generated through traditional services sold on the Selfcare application ,   and we needed to ensure that introducing digital services will not detract current loyal users . 

 Selection   To overcome this challenge , we used Learning Launch tool because we had no idea how   customers would react to this huge transformation , and we needed validated insight . In other   words , we needed a way to measure the enthusiasm of our users towards new digital services ,   and which services in particular they are interested in , if any . In this way , we expected to prevent   huge investments in a new application that might fail , prevent detraction of current loyal users ,   and delivering an application that our users will fall in love with . This experiment had to be done   quickly and with limited budget spending . 

 Application   For this Learning Launch , we decided to create a separate version of our application that   included a shortlist of promising digital services in addition to all current telco related features .   We called this version SelfLove , and we planned to launch it for only 100 users selected   rigorously among our userbase based on specific criteria such as age , gender , occupation , and   history of application usage . Our goal was to select these users in a way to represent our whole   userbase . The digital services that SelfLove should delivered , were also selected carefully to   represent the majority of the categories of services we envisioned . Based on this constraint , we   selected utility bill payment , flight ticket reservation , grocery shopping , and live TV services . 

 In addition , all user interactions had to be measured in SelfLove to enable us to learn how users   interact with the application . For instance , we measured the average time the users spent on each   digital service , and the average amount of money they spent on it . Secondly , we planned a   feature to enable SelfLove users to send invitations to other people , so that we can measure how   likely they recommend this new experience to other users . Thirdly , we planned a capability   inside the application to enable the users to voice any concerns they have . Above all , we had to 

 measure the usage of our traditional services to make sure that the digital services will not detract   our current users . 

 To create this application as quickly as possible and within a limited budget , we partnered with   third - parties that already delivered the services we shortlisted . In this way , all we had to do was   to embed these third - party applications inside SelfLove and deliver the measurement   capabilities . As a result , it took us only 2 weeks to deliver the first version of SelfLove . An   instruction was then sent to the 100 users we selected through SMS and email in which we asked   for their engagement to create the best Selfcare application together . 

 Insight   The results of the learning launch were surprisingly good . Not only the majority of the selected   users participated in this initiative , but they also invited more than 7400 other people to join   SelfLove as well . This enabled us to measure the outcome in an even bigger audience . Finally ,   through the measurements and users ' feedback , we concluded that our users welcome   introduction of digital services into our Selfcare application in general , but , not all categories of   services are interesting to them . In addition , they would like our current services to be more   accessible in comparison with new digital services . Based on this insight , we are now building   the next version of our application . 

 Approach   We initially planned to run the Learning Launch for a period of one month . However , given the   positive feedback we received , we decided to continue this experiment for over 2 months .   Although this enabled us to gain more insight on our users ' behavior , the result of our   measurements did not change drastically compared to the first month . As a result , we wasted   over 2 month that could be spent on delivering the real product which could be used by the   whole userbase . Next time , we will definitely stick to a short duration for our Learning Launch . 


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: Selfcare Application Learning Launch 

 Challenge   I work as a software development manager at a telecommunications company which is seeking   to go beyond its traditional services , such as voice calls and value - added services . To establish   this vision , the company created a new division , called Digital , aimed at creating new digital   revenue streams . This division then started a series of design thinking activities that resulted in   several promising ideas . One of these ideas , for which I was in charge , was to transform our   Selfcare mobile application into a SuperApp that would enable our users to enjoy digital services   as well . These services could range from e - governmental ( such as utility bill and toll payment ) to   e - tourism ( such as ticket and hotel reservation ) and even entertainment ( such as watching live   TV channels ) . Our ultimate goal was to provides almost every service that the users need . In this   way , the users could use our application for most of their day to day activities , and the company   could establish new digital revenue streams it envisioned . However , around 30 % of the   company ’s revenue was generated through traditional services sold on the Selfcare application ,   and we needed to ensure that introducing digital services will not detract current loyal users . 

 Selection   To overcome this challenge , we used Learning Launch tool because we had no idea how   customers would react to this huge transformation , and we needed validated insight . In other   words , we needed a way to measure the enthusiasm of our users towards new digital services ,   and which services in particular they are interested in , if any . In this way , we expected to prevent   huge investments in a new application that might fail , prevent detraction of current loyal users ,   and delivering an application that our users will fall in love with . This experiment had to be done   quickly and with limited budget spending . 

 Application   For this Learning Launch , we decided to create a separate version of our application that   included a shortlist of promising digital services in addition to all current telco related features .   We called this version SelfLove , and we planned to launch it for only 100 users selected   rigorously among our userbase based on specific criteria such as age , gender , occupation , and   history of application usage . Our goal was to select these users in a way to represent our whole   userbase . The digital services that SelfLove should delivered , were also selected carefully to   represent the majority of the categories of services we envisioned . Based on this constraint , we   selected utility bill payment , flight ticket reservation , grocery shopping , and live TV services . 

 In addition , all user interactions had to be measured in SelfLove to enable us to learn how users   interact with the application . For instance , we measured the average time the users spent on each   digital service , and the average amount of money they spent on it . Secondly , we planned a   feature to enable SelfLove users to send invitations to other people , so that we can measure how   likely they recommend this new experience to other users . Thirdly , we planned a capability   inside the application to enable the users to voice any concerns they have . Above all , we had to 

 measure the usage of our traditional services to make sure that the digital services will not detract   our current users . 

 To create this application as quickly as possible and within a limited budget , we partnered with   third - parties that already delivered the services we shortlisted . In this way , all we had to do was   to embed these third - party applications inside SelfLove and deliver the measurement   capabilities . As a result , it took us only 2 weeks to deliver the first version of SelfLove . An   instruction was then sent to the 100 users we selected through SMS and email in which we asked   for their engagement to create the best Selfcare application together . 

 Insight   The results of the learning launch were surprisingly good . Not only the majority of the selected   users participated in this initiative , but they also invited more than 7400 other people to join   SelfLove as well . This enabled us to measure the outcome in an even bigger audience . Finally ,   through the measurements and users ' feedback , we concluded that our users welcome   introduction of digital services into our Selfcare application in general , but , not all categories of   services are interesting to them . In addition , they would like our current services to be more   accessible in comparison with new digital services . Based on this insight , we are now building   the next version of our application . 

 Approach   We initially planned to run the Learning Launch for a period of one month . However , given the   positive feedback we received , we decided to continue this experiment for over 2 months .   Although this enabled us to gain more insight on our users ' behavior , the result of our   measurements did not change drastically compared to the first month . As a result , we wasted   over 2 month that could be spent on delivering the real product which could be used by the   whole userbase . Next time , we will definitely stick to a short duration for our Learning Launch .
### Output: 