Redesigning a Mobile App – Learning Launch 

 Challenge 

 I work on various projects for our company ’s Digital team and my main challenge is to work   with stakeholders and the external design / development vendor to build a much - needed   improved mobile app . The stakeholders comprise of 8 different regional representatives , each   with their own list of desired features for the app to improve the experience for their users . The   challenge is to uncover exactly what the user would like from the app while taking as many of   the stakeholders ’ useful suggestions into consideration as possible , but also proving to the   stakeholders that not all suggestions will work . We also have to take time and budget   constraints into consideration . Working together with the stakeholders and vendor we try to   determine exactly what features and design will make a great app for our users . 

 Selection 

 Learning launch was selected as the tool for the first stage of this project . With such a large   group of stakeholders and limited time to spend on this stage of the project the learning launch   experiment is a great and quick way to test various ideas and learn what works , what does n’t   work , and what can be improved . Each stakeholder assumes that they know what works and   what is best for their user , but these are all just assumptions until tested . As stated by Markus Traub   in the week 4 Learning Launch Tool video ( 5:51 ) , “ The purpose of a learning launch is to get the   truth and then the truth either confirms or dis - confirms your assumptions . ” 

 Application 

 For the first portion data was gathered on the main types of users and 4 different personas were   created , including the features requested by the stakeholders during a brainstorming session , and the   feedback from the current mobile app . At this point we still had not consulted with any actual users ,   with no idea if they would find it easy to use or if it contained all the information they needed . With the   information gathered above the vendor created a couple of slightly different partially working   prototypes for the redesigned mobile app . 

 With a prototype of the app ready , a small group of users from each persona were selected to   participate in an over the phone questionnaire to obtain their feedback about the proposed design and   features . The user downloaded the prototype on their device , their steps in the app were recorded .   They were all asked the same questions during the session , and also encouraged to speak freely at any   point if something did not make sense . It was communicated that they were not being tested , but that   they were testing the app and there were no wrong comments . Positive and negative feedback are both   important , to be able to improve on current features and also possibly remove items that are not   desired . 

 With the results of the first learning launch experiment taken into consideration a “ final ” prototype was   created and a second quick experiment was conducted . A small group of users tested the prototype and   once again feedback was gathered and applied to help created the final mobile app . 

 Insight 

 Everyone , including myself , thought that they knew what was best for the user just based on   their opinions and knowledge . This can prove costly if assumptions are not correct since this   project takes a year to complete , and finding out what works and does n’t work in the eyes of   the user is the most important part and reason to build a new mobile app . If the stakeholder ’s   suggestions were all taken into consideration the app would have not met the users end   expectations . The learning launch experiment is a great tool in this case , it brought to light   which design and features worked , which had room for improvement , and which were   completely unnecessary . This was instrumental in getting all of the stakeholders on the same   page and setting aside their own wants for the user and building a better application that would   meet the needs of the majority of their users . 

 Approach 

 This tool will be used for many of our projects going forward wherever it can be applied . I found   that it made a difficult and daunting task of getting all of the stakeholders on board with a   prototype much easier . The entire team learned that it is very important to test our   assumptions and ideas out on the actual users , since some things that were learned came as a   surprise . Everyone was able to contribute their ideas at the start to help put together a   prototype , and the product became refined and better after each experiment , proving that the   tool works . 


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: Redesigning a Mobile App – Learning Launch 

 Challenge 

 I work on various projects for our company ’s Digital team and my main challenge is to work   with stakeholders and the external design / development vendor to build a much - needed   improved mobile app . The stakeholders comprise of 8 different regional representatives , each   with their own list of desired features for the app to improve the experience for their users . The   challenge is to uncover exactly what the user would like from the app while taking as many of   the stakeholders ’ useful suggestions into consideration as possible , but also proving to the   stakeholders that not all suggestions will work . We also have to take time and budget   constraints into consideration . Working together with the stakeholders and vendor we try to   determine exactly what features and design will make a great app for our users . 

 Selection 

 Learning launch was selected as the tool for the first stage of this project . With such a large   group of stakeholders and limited time to spend on this stage of the project the learning launch   experiment is a great and quick way to test various ideas and learn what works , what does n’t   work , and what can be improved . Each stakeholder assumes that they know what works and   what is best for their user , but these are all just assumptions until tested . As stated by Markus Traub   in the week 4 Learning Launch Tool video ( 5:51 ) , “ The purpose of a learning launch is to get the   truth and then the truth either confirms or dis - confirms your assumptions . ” 

 Application 

 For the first portion data was gathered on the main types of users and 4 different personas were   created , including the features requested by the stakeholders during a brainstorming session , and the   feedback from the current mobile app . At this point we still had not consulted with any actual users ,   with no idea if they would find it easy to use or if it contained all the information they needed . With the   information gathered above the vendor created a couple of slightly different partially working   prototypes for the redesigned mobile app . 

 With a prototype of the app ready , a small group of users from each persona were selected to   participate in an over the phone questionnaire to obtain their feedback about the proposed design and   features . The user downloaded the prototype on their device , their steps in the app were recorded .   They were all asked the same questions during the session , and also encouraged to speak freely at any   point if something did not make sense . It was communicated that they were not being tested , but that   they were testing the app and there were no wrong comments . Positive and negative feedback are both   important , to be able to improve on current features and also possibly remove items that are not   desired . 

 With the results of the first learning launch experiment taken into consideration a “ final ” prototype was   created and a second quick experiment was conducted . A small group of users tested the prototype and   once again feedback was gathered and applied to help created the final mobile app . 

 Insight 

 Everyone , including myself , thought that they knew what was best for the user just based on   their opinions and knowledge . This can prove costly if assumptions are not correct since this   project takes a year to complete , and finding out what works and does n’t work in the eyes of   the user is the most important part and reason to build a new mobile app . If the stakeholder ’s   suggestions were all taken into consideration the app would have not met the users end   expectations . The learning launch experiment is a great tool in this case , it brought to light   which design and features worked , which had room for improvement , and which were   completely unnecessary . This was instrumental in getting all of the stakeholders on the same   page and setting aside their own wants for the user and building a better application that would   meet the needs of the majority of their users . 

 Approach 

 This tool will be used for many of our projects going forward wherever it can be applied . I found   that it made a difficult and daunting task of getting all of the stakeholders on board with a   prototype much easier . The entire team learned that it is very important to test our   assumptions and ideas out on the actual users , since some things that were learned came as a   surprise . Everyone was able to contribute their ideas at the start to help put together a   prototype , and the product became refined and better after each experiment , proving that the   tool works .
### Output: 