Improve the grocery store in-store shopping customer experience (i.e. a physical grocery store).

It is important to start with a structure of how we want to address this question:
1. We will ask clarifying questions to better understand the requirements
2. We will understand the goal of this exercise
3. We will look at the Users and Prioritize one user set
4. We will look at the various steps in the user journey
5. We will then try to understand some pain points for the user set under consideration and priortize them based on key factors
6. We will then brainstorm solutions that address the prioritized pain points.
7. At the end, we will summarize our analysis.

Clarifying Questions:
1. Define Improve? - Help shoppers as they shop through the store today. What can be done better in physical stores
2. What is the Goal? - To improve customer's in-store shoppimng experience - Let's consider Engagement as the metric to improve
3. Is this large retail chains or individual mom and pop stores - You choose - Let's choose large retail chains
4. Are we considering US or WW? - US for now
5. Any particular market to focus on? - Pan US
6. Any particular section of the shopping experience to focus on? - You choose

Goal:
The goal of the exercise is to engage customers and encourage them to shop instore more than online ordering - Focus on Engagement metrics

Users:
- Grocery customers
- Grocery store associates
- Grocery Chain

Let's focus on the Grocery customers here as the goal remains to improve their experience while shopping in-store.

Pain Points:
1. Store map issues - not sure where products are shelved and often time consuming to find and pick out items.
2. Spoilt/Experiation of fresh food - Fresh groceries/meat are in-demand- customers are often not sure of when the fruits and vegetables or meats were placed in shelves and what their shelf life is.
3. Item availability - Not sure if a particular item that is needed is even on the shelves and available in store (product avails as well as quantity of avails)
4. Very long check out times - Large chains often have large check out lines despite having multiple stations for checkout (some of which do not work owing to lack of in-store associates to man them)
5. Price discrepancies between online pricing and in-store pricing/competitor pricing - requires additional work from customer's end for price matching.

Priorities: Based on Impact and Reach, we can priorities the pain points as follows:
2,3,1,4,5

Solutions:
1.
1. Availability and Product Metadata: Create app for Mobile (or even on a display portal on the cart ) that allows users to search for items of interest and let them know if the item is available in store (and qty available) and also shows the aisle where the item is stored. This would also provide information such as when the SKU(item) went on the shelves and the expiration date.
        a. If item not available, let the users know when it is expected to be in store or the nearest store where item is available.
2. Store Map and quickest path to purchase: Build display portal or in-app facility that provides directions in store to be able to quickly navigate the layout and efficiently purchase products. Users can enter their items of interest in the cart display or in app and then we use ML to understand quickest path to complete purchases
3. Cart Scanning Facility: Create cart scanning facility in the carts for users to scan the items that they buy to showcase cost of total purchase - This will alleviate check-out stations completely and significantly reduce check-out times. 
      a. Another option here is to consider a no-checkout facility (based on the amazon-go approach) but that is very complicated and will take a very long time to develop.
4. Web Scarpping and Price matching: Build pro-active web scraping systems that provide real time pricing from competitors and feeds into the OMS (order Management System). This should track whether we are At Market, Above Market or Below Market for the SKU prices. If Above Market (where our prices are more than competitors on the day) we will match prices at scan/check-out,so as to be able to provide the most competitive prices for our customers.
5. Assisted Shopper facility: Provide special needs customers with assisted in-store shopping help.

Now, let's evaluate these solutions based on a combination of Reach, Impact and Effort/Cost

Metrics:
Primary:
1. WAU/MAU - Number of weekly or monthly in-store shopper trend (daily wont make sense here because people may not shop daily for groceries.
2.  Average time spent per customer per shopping session - We would want this trend to decrease over time.
Secondary:
1. Number of errors per shopping sessions/Issues reported - We can break this down by type of error (wrong product information/ scans not functioning/ pricing issues etc.)
2. NPS - Customer Satisfaction scores - Either via surveys outside store or within App/cart display
3. Incremental in-store revenue trends
4. Average number of products purchased per customer per shopping session (not entirely sure about this - but could be useful)
 

Summary:
We started looking at ways to improve in-store shopping experience for customers by focussing on large chains in the US. We broke down the users into various types and focussed on the end customers who are shopping in-store. We looked at some of their pain points with the most important being that they want to know freshness of food and where items are kept in the store while also keeping an eye out for long checkout times. We then brain-stormed solutions like adding store maps and item metadata to cart displays and doing real time price matching. These solutions, we believe are going to have a very positive impact on the customer's shopping experience.
Finally, we will track the efficacy of our solutions with some primary and secondary metrics.