Reflection - Learning Launch 

 Challenge 

 We are all living in a global world with millions of products but still we must deal with the scarcity of   time and budget . Especially in the design industry , the products are nearly same however there is   large scale of pricing . In addition , because of the limited time , we are likely to consume the best   option we come across between few alternatives . However , the marketplace is huge and there are   many other products that maximizes our satisfaction in terms of design , quality , and price but we   are n’t aware of them . 

 To solve this problem , me and my colleagues , had the idea of creating an application that the users   will take the picture of the product that they like and the application will provide the worldwide   similar alternatives according to the picture they uploaded . The main challenge for us is , there are   giant platforms like Amazon , Alibaba etc . that provides large scale of products . Therefore , the main   question is : “ Are these platforms and filtering systems while searching for a product sufficient in   these platforms , or they are not ? Is there need of a platform consists our idea , or not ? ” 

 Selection 

 The tool that I selected for this challenge is learning launch . Since we have limited budget and time ,   we should do low - costed experiments that will give response quickly . In this tool , our main goal is to   “ learn ” if our idea will work or not , by getting feedbacks from the public . By using learning launch , we   will reduce the risk of experiencing big failures at the end . We will have the opportunity to test our   idea and be able to take accurate actions . 

 Application 

 For making rational experiments firstly , we determined our potential customers . Our main goal is to   attract the people who already uses online shopping . According to Eurostat ’s data , the biggest share   of online shopping belongs to the population aged between 16 and 24 . However while making our   surveys we considered that due to Covid-19 outbreak , the number of higher aged e - shoppers will   increase . 

 After determining our potential customers , we designed a survey for them . In the survey we asked   questions like “ Before buying a product would you like to see other similar products ? If yes , how   many products will be enough ? Did you experienced regret , after buying a product because of you   missed another alternative ? If yes , how frequent it happens ? ” . Lastly , we designed a small prototype   of our idea . We wanted from our participants to share the last cloth they bought with us . After , we   provide them 5 more similar alternatives and asked , “ Do you want to replace your cloth with one of   our alternatives ? ” 

 Insight 

 After bringing the learning launch to life , we find out how consumption habits change according to   gender and age . In additions we had more accurate assumptions to the question of “ Will our idea   work ? ” . 

 Firstly , while both men and women wanted to see the other alternatives , men were satisfied when   they saw less options than women . On the other hand , while most of the women who participated to   the survey felt regret after they bought a product and saw its better alternative , most of the men   declared that they did n’t felt any regret at all . 

 In addition , no matter the gender X generation wanted to see more alternatives than Z generation .   This result was not surprising for us however , it is significant . Even though the e - shoppers are mainly   members of Z generation , people who most wanted to see the alternative products were the   members of X generation . Therefore , our business model should include and prioritize generation X   as well . Most significantly , more than half of the people who tried our prototype , declared that “ If   they had a chance , they would replace their product with one of the alternatives we provided . ” 

 Approach 

 As a result , by using learning launch tool we gained many valuable information . Firstly , it helped us to   determine our potential customers correctly from the very beginning .   Secondly , it showed us that   our idea may work however some of our assumption were incorrect . For example , participants were   generally satisfied with seeing less alternatives than what we expected or generation X was our main   potential buyers , but we were about to miss it . Learning launch tool , allowed us to step in the shoes   of the customers . It taught us about their mindsets and their needs . It also lighted the path for   reaching to them . Finally , if we had a chance to change the tool that we used , probably we would   prefer to stay with learning launch . Since our idea is based on an idea in the future , for making it   clear in the minds of our potential customers , making prototypes and surveys are the most efficient   way of gaining information . 


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 - Learning Launch 

 Challenge 

 We are all living in a global world with millions of products but still we must deal with the scarcity of   time and budget . Especially in the design industry , the products are nearly same however there is   large scale of pricing . In addition , because of the limited time , we are likely to consume the best   option we come across between few alternatives . However , the marketplace is huge and there are   many other products that maximizes our satisfaction in terms of design , quality , and price but we   are n’t aware of them . 

 To solve this problem , me and my colleagues , had the idea of creating an application that the users   will take the picture of the product that they like and the application will provide the worldwide   similar alternatives according to the picture they uploaded . The main challenge for us is , there are   giant platforms like Amazon , Alibaba etc . that provides large scale of products . Therefore , the main   question is : “ Are these platforms and filtering systems while searching for a product sufficient in   these platforms , or they are not ? Is there need of a platform consists our idea , or not ? ” 

 Selection 

 The tool that I selected for this challenge is learning launch . Since we have limited budget and time ,   we should do low - costed experiments that will give response quickly . In this tool , our main goal is to   “ learn ” if our idea will work or not , by getting feedbacks from the public . By using learning launch , we   will reduce the risk of experiencing big failures at the end . We will have the opportunity to test our   idea and be able to take accurate actions . 

 Application 

 For making rational experiments firstly , we determined our potential customers . Our main goal is to   attract the people who already uses online shopping . According to Eurostat ’s data , the biggest share   of online shopping belongs to the population aged between 16 and 24 . However while making our   surveys we considered that due to Covid-19 outbreak , the number of higher aged e - shoppers will   increase . 

 After determining our potential customers , we designed a survey for them . In the survey we asked   questions like “ Before buying a product would you like to see other similar products ? If yes , how   many products will be enough ? Did you experienced regret , after buying a product because of you   missed another alternative ? If yes , how frequent it happens ? ” . Lastly , we designed a small prototype   of our idea . We wanted from our participants to share the last cloth they bought with us . After , we   provide them 5 more similar alternatives and asked , “ Do you want to replace your cloth with one of   our alternatives ? ” 

 Insight 

 After bringing the learning launch to life , we find out how consumption habits change according to   gender and age . In additions we had more accurate assumptions to the question of “ Will our idea   work ? ” . 

 Firstly , while both men and women wanted to see the other alternatives , men were satisfied when   they saw less options than women . On the other hand , while most of the women who participated to   the survey felt regret after they bought a product and saw its better alternative , most of the men   declared that they did n’t felt any regret at all . 

 In addition , no matter the gender X generation wanted to see more alternatives than Z generation .   This result was not surprising for us however , it is significant . Even though the e - shoppers are mainly   members of Z generation , people who most wanted to see the alternative products were the   members of X generation . Therefore , our business model should include and prioritize generation X   as well . Most significantly , more than half of the people who tried our prototype , declared that “ If   they had a chance , they would replace their product with one of the alternatives we provided . ” 

 Approach 

 As a result , by using learning launch tool we gained many valuable information . Firstly , it helped us to   determine our potential customers correctly from the very beginning .   Secondly , it showed us that   our idea may work however some of our assumption were incorrect . For example , participants were   generally satisfied with seeing less alternatives than what we expected or generation X was our main   potential buyers , but we were about to miss it . Learning launch tool , allowed us to step in the shoes   of the customers . It taught us about their mindsets and their needs . It also lighted the path for   reaching to them . Finally , if we had a chance to change the tool that we used , probably we would   prefer to stay with learning launch . Since our idea is based on an idea in the future , for making it   clear in the minds of our potential customers , making prototypes and surveys are the most efficient   way of gaining information .
### Output: 