Using the Learning Launch tool and the help of the   customers to get insights for a e - commerce 

 The challenge 

 I work at a beauty e - commerce site as a designer and the team have the task to   increase the sales to keep the company running good and proﬁtable in the expected   ways the directos where planning . 

 We sell beauty products , only that . It`s not something that people ( in this case , most   women ) need to survive and it isn`t something people are willing to buy every   weekend . So , how could we sell more of those expensive products to the   customers ? 

 We talked after the brieﬁng and we agreed that we could`t make people desire to   buy more , it could`t be done , we can`t change people behavior . But , maybe we could   make the site easier so our customers could buy faster , and maybe this way they   would buy more . 

 So for that task I review every screen of the system to see where we have room to   improve . I also looked and test other e - commerce sites to see how the navigation   and the cart goes , learning what is good and what is bad for our users . 

 The tools 

 After that study on my own I bring some hypothesis of why people are n’t buying   more from us : 

 1 - people did n’t understand of get confused somewhere in the cart , and don`t buy ; 2 - people are n’t ﬁnd the products they want on the site , and because of that did n’t   buy anything ; 3 - people simple ﬁnd the product for a lower price somewhere . 

 Having these hypothesis I decided to use the Learning Launch tool that we learn in   the module 4 of the course , because it could bring me to the true by conﬁrm or dis- conﬁrm my assumptions . Either way I would have evolved at this matter ate the end   of the process by the learning : if one of my hypothesis was true I would know where   to work to solve the matter , and if all was false I still have time to think and try   something else . 

 The Application 

 So for the ﬁrst step I create some very simple prototype of the site change some   information of how we present the products and making a new navigation at the cart   screen to be simpler and fast . I also write some questions to get to know how people   use and thinking about our site and how they use it . Some of the questions were   generic , just to get to know the person and her habits , but some of then were speciﬁc   to test my hypothesis , like : 

 - What other sites did you you use to buy online ? Which one is easy to buy ? Why ?   How about ours ? What we should improve ? - What do you do when you don`t ﬁnd the product on ours website ?   - What do you do to pay less in your shop ? How important save money is to you ? 

 After that part done I invite 5 customers that frequently buy from us and 5 customers   that bought only once in the last year , since Jakob Nielsen recommend that we uses   5 people to do usability tests to get a satisfactory status ( https://www.nngroup.com/ articles / why - you - only - need - to - test - with-5 - users/ ) and we want to test it fast . If the   result was n’t conclusive enough we could get more participants . 

 Finally we invite each participant to the ofﬁce separately , we talked to them ,   understand how they live , what they usually buy , how they buy , why and when . We   also show the prototype and get the feedback , some of them were happily to show   us the other sites and what features they like most in each one . 

 The Insights 

 At the end of the interviews , I analyzed the results and come back to my hypothesis   and the new status was : 

 1 - people did n’t understand of get confused somewhere in the cart , and don`t buy ; Result : they do understand but it can be improved , the prototype was pretty positive   for everyone . We should implement that . 

 2 - people are n’t ﬁnd the products they want on the site , and because of that did n’t   buy anything ; Result : they do found the products , no problem here . And when the product is n’t   available they know we can send an e - mail when it arrives at the site . 

 3 - people simple ﬁnd the product for a lower price somewhere . Result : they do search for a better price , but we are one of the most favorite places   to buy because we delivery very fast . And it is also important . 

 The tool worked for my hypothesis , but something else shows up naturally after we   talked to our customers : almost everyone said spontaneous to us that special offers   in special days , like valentines , christmas , and other dates is when they looked more   beauty products . They also liked when we have some special offers in ordinary days ,   and even when they are n’t searching anything on those days there is always a friend   that talked about it . 

 So now , with the help of our customers we have a new response : 

 - To make more proﬁt , we should`t focus on selling more to each customer . We must   sell more ofter to them , using every holiday possible and creating new offer days . 

 The Approach 

 After all that we still talking to the marketing team to ﬁgure out how can we work that   new insight our customers give to us , but the learning launch tool combined with our 

 interview where great to give us a clear way to walk . 

 I liked the idea of test hypothesis as soon as possible , it gives us more room to fail   fast and learn soon . It was also extremely important the participation of the   customers , I`m sure we could`t see this path as easy as it was showed to us without   them . 

 I`m certainly will use it more in other problems , because I ﬁnd it perfect to test some   interaction , some part ou some process on websites . It`s easy and simple to use and   it brings us a great insight . 


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: Using the Learning Launch tool and the help of the   customers to get insights for a e - commerce 

 The challenge 

 I work at a beauty e - commerce site as a designer and the team have the task to   increase the sales to keep the company running good and proﬁtable in the expected   ways the directos where planning . 

 We sell beauty products , only that . It`s not something that people ( in this case , most   women ) need to survive and it isn`t something people are willing to buy every   weekend . So , how could we sell more of those expensive products to the   customers ? 

 We talked after the brieﬁng and we agreed that we could`t make people desire to   buy more , it could`t be done , we can`t change people behavior . But , maybe we could   make the site easier so our customers could buy faster , and maybe this way they   would buy more . 

 So for that task I review every screen of the system to see where we have room to   improve . I also looked and test other e - commerce sites to see how the navigation   and the cart goes , learning what is good and what is bad for our users . 

 The tools 

 After that study on my own I bring some hypothesis of why people are n’t buying   more from us : 

 1 - people did n’t understand of get confused somewhere in the cart , and don`t buy ; 2 - people are n’t ﬁnd the products they want on the site , and because of that did n’t   buy anything ; 3 - people simple ﬁnd the product for a lower price somewhere . 

 Having these hypothesis I decided to use the Learning Launch tool that we learn in   the module 4 of the course , because it could bring me to the true by conﬁrm or dis- conﬁrm my assumptions . Either way I would have evolved at this matter ate the end   of the process by the learning : if one of my hypothesis was true I would know where   to work to solve the matter , and if all was false I still have time to think and try   something else . 

 The Application 

 So for the ﬁrst step I create some very simple prototype of the site change some   information of how we present the products and making a new navigation at the cart   screen to be simpler and fast . I also write some questions to get to know how people   use and thinking about our site and how they use it . Some of the questions were   generic , just to get to know the person and her habits , but some of then were speciﬁc   to test my hypothesis , like : 

 - What other sites did you you use to buy online ? Which one is easy to buy ? Why ?   How about ours ? What we should improve ? - What do you do when you don`t ﬁnd the product on ours website ?   - What do you do to pay less in your shop ? How important save money is to you ? 

 After that part done I invite 5 customers that frequently buy from us and 5 customers   that bought only once in the last year , since Jakob Nielsen recommend that we uses   5 people to do usability tests to get a satisfactory status ( https://www.nngroup.com/ articles / why - you - only - need - to - test - with-5 - users/ ) and we want to test it fast . If the   result was n’t conclusive enough we could get more participants . 

 Finally we invite each participant to the ofﬁce separately , we talked to them ,   understand how they live , what they usually buy , how they buy , why and when . We   also show the prototype and get the feedback , some of them were happily to show   us the other sites and what features they like most in each one . 

 The Insights 

 At the end of the interviews , I analyzed the results and come back to my hypothesis   and the new status was : 

 1 - people did n’t understand of get confused somewhere in the cart , and don`t buy ; Result : they do understand but it can be improved , the prototype was pretty positive   for everyone . We should implement that . 

 2 - people are n’t ﬁnd the products they want on the site , and because of that did n’t   buy anything ; Result : they do found the products , no problem here . And when the product is n’t   available they know we can send an e - mail when it arrives at the site . 

 3 - people simple ﬁnd the product for a lower price somewhere . Result : they do search for a better price , but we are one of the most favorite places   to buy because we delivery very fast . And it is also important . 

 The tool worked for my hypothesis , but something else shows up naturally after we   talked to our customers : almost everyone said spontaneous to us that special offers   in special days , like valentines , christmas , and other dates is when they looked more   beauty products . They also liked when we have some special offers in ordinary days ,   and even when they are n’t searching anything on those days there is always a friend   that talked about it . 

 So now , with the help of our customers we have a new response : 

 - To make more proﬁt , we should`t focus on selling more to each customer . We must   sell more ofter to them , using every holiday possible and creating new offer days . 

 The Approach 

 After all that we still talking to the marketing team to ﬁgure out how can we work that   new insight our customers give to us , but the learning launch tool combined with our 

 interview where great to give us a clear way to walk . 

 I liked the idea of test hypothesis as soon as possible , it gives us more room to fail   fast and learn soon . It was also extremely important the participation of the   customers , I`m sure we could`t see this path as easy as it was showed to us without   them . 

 I`m certainly will use it more in other problems , because I ﬁnd it perfect to test some   interaction , some part ou some process on websites . It`s easy and simple to use and   it brings us a great insight .
### Output: 