DT Tool Assignment- Learning Launch " Bar2Home " ' 

 1 . Challenge : 

 For this assignment , the project that I have used is an idea that have called “ Bar2Home ” . The   problems I have with this problem is as below : 

 1 . In Malaysia , we have the highest tax on alcohol , which creates a huge problem with 

 counterfeit and smuggled alcohol , which gives people a lot of distrust on liquor stores . 

 2 . Drink driving is a problem with stringent laws that scares away people from bars .   3 . Casual drinkers do not have the time to buy mixer sets to drink at home . 

 Our solutions will eliminate the problems by delivering original authenticated alcohol with mixers   directly to their homes . 

 2 . Tool selection 

 The tool I have chosen for this is the Learning Launch tool because : 

    We already have a brick and mortar store up and running in Kuala Lumpur with ready stock ,   which will allow us to test the market quickly . 

    Using existing motorcycle delivery services in Malaysia , we can deliver to market fast . 

    We have existing menu suggestions in the shop that we can push to customers fast 

 Hence , by having all these , we can test our hypothesis and push a prototype solution fast , gather   information , adapt , and launch . 

 3 . Application : 

 Idea : 

 Our problem was to push more drinks during the lockdown period in Malaysia to people who ca n’t   go to bars or drive after drinking . So , the solution was a home delivery of cocktail sets example   below : 

 Target Audience : 

    People who are in lockdown . 

    Young urban female with passion for fresh cocktails . 

    People who do not know where to buy the alcohol / drink combination . 

 The current alternative of going to the bar or liquor shop is not viable as the premises are closed due   to Covid19 . 

 Learnings 

    Our suggested combinations were not familiar to local audience . We had to tweak flavours   and combinations . 

    We had to take last minute orders and prepare delivery in rush because we realize people   do n’t decide to drink in advance . 

    Some premium liquor sets do not sell due to high costs , which made us create new cheaper   combinations 

 Outcome : 

    18 packages sold before based on hypothesis alone 

    62 packages sold after learnings implemented . 

    Learning launch made us increase our sales by 3.5 times . 

 Approach : 

 For the follow next time we something similar , I will still use the same learning launch tool because   we hold stocks that last longer that average . 

 The only difference it would be is that we want to send out surveys and questionnaires about   customer preference before we decide of creating the combination of sets . 


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: DT Tool Assignment- Learning Launch " Bar2Home " ' 

 1 . Challenge : 

 For this assignment , the project that I have used is an idea that have called “ Bar2Home ” . The   problems I have with this problem is as below : 

 1 . In Malaysia , we have the highest tax on alcohol , which creates a huge problem with 

 counterfeit and smuggled alcohol , which gives people a lot of distrust on liquor stores . 

 2 . Drink driving is a problem with stringent laws that scares away people from bars .   3 . Casual drinkers do not have the time to buy mixer sets to drink at home . 

 Our solutions will eliminate the problems by delivering original authenticated alcohol with mixers   directly to their homes . 

 2 . Tool selection 

 The tool I have chosen for this is the Learning Launch tool because : 

    We already have a brick and mortar store up and running in Kuala Lumpur with ready stock ,   which will allow us to test the market quickly . 

    Using existing motorcycle delivery services in Malaysia , we can deliver to market fast . 

    We have existing menu suggestions in the shop that we can push to customers fast 

 Hence , by having all these , we can test our hypothesis and push a prototype solution fast , gather   information , adapt , and launch . 

 3 . Application : 

 Idea : 

 Our problem was to push more drinks during the lockdown period in Malaysia to people who ca n’t   go to bars or drive after drinking . So , the solution was a home delivery of cocktail sets example   below : 

 Target Audience : 

    People who are in lockdown . 

    Young urban female with passion for fresh cocktails . 

    People who do not know where to buy the alcohol / drink combination . 

 The current alternative of going to the bar or liquor shop is not viable as the premises are closed due   to Covid19 . 

 Learnings 

    Our suggested combinations were not familiar to local audience . We had to tweak flavours   and combinations . 

    We had to take last minute orders and prepare delivery in rush because we realize people   do n’t decide to drink in advance . 

    Some premium liquor sets do not sell due to high costs , which made us create new cheaper   combinations 

 Outcome : 

    18 packages sold before based on hypothesis alone 

    62 packages sold after learnings implemented . 

    Learning launch made us increase our sales by 3.5 times . 

 Approach : 

 For the follow next time we something similar , I will still use the same learning launch tool because   we hold stocks that last longer that average . 

 The only difference it would be is that we want to send out surveys and questionnaires about   customer preference before we decide of creating the combination of sets .
### Output: 