Finding if main assumption is right – Learning Launch 

 Challenge 

 A group of friends and I have come together to create a website that provides customers SEO   services for their personal websites and business accounts on different social media . Within the   team we have Full Stack Developers , Marketing Analyst Experts , Finance and Salespeople . We   already have developed the core functionalities of the platform , SEO leads procedures and a   business plan and we are almost ready to launch the company with the website . But we still have   not defined WHO will be our target audience , and which will be our minimum viable audience to   proceed our business activities . We have some assumptions about our clients are going to be   middle size companies so we think it will be a B2B company . Still we have to find out if this is the   case . 

 Selection 

 The website has already been launched as a beta , so our team already has some data about   clients visits and interaction with our website . Since we do not know yet who will be our main target ,   we have decided to use the Learning Launch Tool to try different customer segments and see   which of them fits best with our value proposition . 

 Application 

 For the process of finding out WHO is this target we are aiming , the company has developed the   beta version of the platform , also known as the MVP ( minimum viable product ) , this one does not   contain all the features we have come up with , just the ones that contains the core functionalities to   test if our assumptions are right . 

 Since we have Marketing Analysts experts , we have divided the visitor in many groups dividing   them between the time they spend online , the device they are using , the interactions they have with   us . And finally , when do they leave the site . 

 After finding out that the traffic online was big enough to validate the MVP , we proceeded to add   progressively the other features by the A / B Testing method . After that we have come up that the   customers that were more satisfied with all the features , after adjusting some that were not desired ,   we have come to the conclusion that our customer target where mid - size companies that wanted to   know how did they score at SEO qualifications compared with their competition . 

 During all this process we have been using the Lean approach to validate the assumptions and   create new ones , to validate knowledge fast and cheap . 

 Insight 

 By applying the Learning Launch Tool in combination with A / B Testing and the Lean Methodology ,   we have come up with the team that there where many features that we considered as valuable , but   the customers did n’t want at all . In this case we had to do a pivot on our strategy to adjust the   desired features and functionalities but at the same time aligning all the already existing validated   knowledge with the website . We where also very grateful we have applied this tool and method   because we could have gone to the public with many errors on our assumptions having big loses in 

 profit and killing the business in an early stage . Therefore this iterative process worked for us in   every stage of the creation of the platform . 

 Approach : 

 Due that this process ( Learning Launch Tool ) has been very well adopted by my team we will   certainly use it again in future project , nevertheless one aspect where we have failed on the   execution of the tool was that we did not have well defined the timing and the stages of this creation   of knowledge . For the next time we will come up with an elaborated schedule and standardize the   knowledge registration procedures to simplify the data analysis . 


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: Finding if main assumption is right – Learning Launch 

 Challenge 

 A group of friends and I have come together to create a website that provides customers SEO   services for their personal websites and business accounts on different social media . Within the   team we have Full Stack Developers , Marketing Analyst Experts , Finance and Salespeople . We   already have developed the core functionalities of the platform , SEO leads procedures and a   business plan and we are almost ready to launch the company with the website . But we still have   not defined WHO will be our target audience , and which will be our minimum viable audience to   proceed our business activities . We have some assumptions about our clients are going to be   middle size companies so we think it will be a B2B company . Still we have to find out if this is the   case . 

 Selection 

 The website has already been launched as a beta , so our team already has some data about   clients visits and interaction with our website . Since we do not know yet who will be our main target ,   we have decided to use the Learning Launch Tool to try different customer segments and see   which of them fits best with our value proposition . 

 Application 

 For the process of finding out WHO is this target we are aiming , the company has developed the   beta version of the platform , also known as the MVP ( minimum viable product ) , this one does not   contain all the features we have come up with , just the ones that contains the core functionalities to   test if our assumptions are right . 

 Since we have Marketing Analysts experts , we have divided the visitor in many groups dividing   them between the time they spend online , the device they are using , the interactions they have with   us . And finally , when do they leave the site . 

 After finding out that the traffic online was big enough to validate the MVP , we proceeded to add   progressively the other features by the A / B Testing method . After that we have come up that the   customers that were more satisfied with all the features , after adjusting some that were not desired ,   we have come to the conclusion that our customer target where mid - size companies that wanted to   know how did they score at SEO qualifications compared with their competition . 

 During all this process we have been using the Lean approach to validate the assumptions and   create new ones , to validate knowledge fast and cheap . 

 Insight 

 By applying the Learning Launch Tool in combination with A / B Testing and the Lean Methodology ,   we have come up with the team that there where many features that we considered as valuable , but   the customers did n’t want at all . In this case we had to do a pivot on our strategy to adjust the   desired features and functionalities but at the same time aligning all the already existing validated   knowledge with the website . We where also very grateful we have applied this tool and method   because we could have gone to the public with many errors on our assumptions having big loses in 

 profit and killing the business in an early stage . Therefore this iterative process worked for us in   every stage of the creation of the platform . 

 Approach : 

 Due that this process ( Learning Launch Tool ) has been very well adopted by my team we will   certainly use it again in future project , nevertheless one aspect where we have failed on the   execution of the tool was that we did not have well defined the timing and the stages of this creation   of knowledge . For the next time we will come up with an elaborated schedule and standardize the   knowledge registration procedures to simplify the data analysis .
### Output: 