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Design an app to help people reduce anxiety when trying to decide what cheese to buy at a grocery store.

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Design an app to help people reduce anxiety when trying to decide what cheese to buy at a grocery store.
 
Clarifying questions
 
1. Can I think of reducing anxiety as to improving the customer satisfaction when trying to buy cheese at a grocery store -> Assuming Yes
2. Can I assume this app to be released in US -> Yes
3. Are we planning to limit the app to selecting cheese for now but with an idea to expand to other products in the future so a generic design is thought throught for the product design -> Yes
4. What is the area of the grocery store , can I consider it big and doesnt just sell cheese-> Yes
5. Do we have an existing app which is being extended - No
 
Business Goal : Build a app which helps customers engage and make it easy for them to but cheese at the grocery store. 
 
Users
1. Cheese Connoisseeur 
2. 3rd party vendors who buy cheese for Grazing boards
3. First time cheese buyers
 
I would like to target first time cheese buyers and would like to make it a smooth experience for them as our 1st and 2nd categories of users have some idea when they get into the store. 
 
Painpoints
1. Tasted a cheese at friends party or wedding and do not know the name
2. Want to know the nutitional values
3. like a specific taste (sweet, sour, bitter) etc
4. affordable 
5. Different types of cheeses and their names with price
6. Location where they can find it (Aisle)
 
PainpointCustomer SatisfactionEffortPrioirty
Tasted a cheese at friends party or wedding and do not know the nameMediumHigh P2
Want to know the nutitional valuesMediumMedium P2
like a specific taste (sweet, sour, bitter) etcHighMediumP1
affordable HighMediumP1
Location where they can find it (Aisle)HighMediumP1
Different types of cheeses and their names with priceMediumHighP2
I would like to prioirtize the app to be able to understand preferences like taste, color, size , price and location. 
 
Solutions
 
SolutionPros Cons
Screen 1 : Design a screen which has preferences on the left hand side as preferred filters for price, taste, color, size etc.
Screen 2 : After the selected criteria, the center page filters the list with the selected criteria
Screen 3: Compares the top 3 selected with popular reviews and suggestions and allows the user to either pick 1 or all three
Screen 4 : provides a preview of the selected cheese, price, taste, color and location to pick and make the purchase.
Traditional app and easy to use as this is a generic and popular approach that most websites like pininterest etc followToo many steps might bore the user and stop them from moving forward.
Design a LLM (generative AI) component with a chat bot , user defines the criteria above in a short description and BOT provides the user with top 3 choices and popular suggestions and reviews.Precise and easy to use as the user is stating all the details in a short description. we are basically avoiding traidtional steps and letting the user feel free to explain their ideas.There is a uncertianity in answers when the interactions are brief.
A Kiosk service  at the entrance , user can come in and ask the robot to suggest the best cheese, Robot will ask a set of Q & A before a specific cheese is suggested with reviews. The robot would go and get the cheese in this case.This might give the best customer experience as its a combination of a LLM and gives the user a caring experience.This might be very expensive and needs heavy investment.
Due to heavy infra needed, if the store decides to have only one robot , it might be annoying for the user to stand in the queue to address their question.
 

I would suggest a LLM BoT , users can click the grocery store icon and start with the BoT asking , I can help answer your questions today.

Success Metrics

1. App Downloads - No. of users who downloaded the app and signed up
2. NO. of customers who interacted with the BoT and made a cheese purchase/ Total no. of customers who interacted with the BoT

3. Weekly New vs return users - New defined as the first time ever the customer interacting with the app to the return users who have come back to use the app again within a week (Mon - Sun)

4. Churn - Customers who aborted the conversation and never used the app again

North star metric is the 2nd one which helps us understand if the customer enngagement is successful and if the BoT helped the customer in making it easy for them to choose the cheese they need.

I would also like to evaluate churn or people who did not complete the flow to get more context in providing the input to the product backlog.
 
 

 

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Get access to 2,346 pm interview questions and answers to give yourself a strong edge against other candidates that are interviewing for the same position
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