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Meal Delivery Service Analysis - Python
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  • How can a meal delivery service improve operations?

    📖 Background

    Your client is a food company in India that provides meal delivery services to thousands of customers per week. They operate in 51 cities inside eight different regions of the country. To better serve their customers, they deliver meals from 77 fulfillment centers.

    The company wants you to help them understand their customer base, meal preferences, and fluctuations in demand. They want to investigate ways to improve operations and reduce food waste.

    💾 The data

    Your client has provided you with almost three years of order information for each of their 77 fulfillment centers:

    • "week" - week (1 - 145)
    • "center_id" - id of the fulfillment center
    • "city_code" - city identifier
    • "region_code" - region identifier
    • "center_type" - there are three types of centers: A, B, and C
    • "op_area" - the size of the area serviced by the fulfillment center
    • "meal_id" - each meal has a unique id
    • "category" - food category (beverages, pasta, rice, etc.)
    • "cuisine" - the type of cuisine for each meal
    • "checkout_price" - the price the customer pays (including discounts, promotions, etc.)
    • "base_price" - list price for the meal
    • "emailer" - 1 if there was an email promotion for the meal, 0 otherwise
    • "featured" - 1 if the website featured the meal, 0 otherwise
    • "orders" - number of orders for that week for that meal id

    Executive Summery

    • Our customers prefer the Beverages food category over all other categories.
    • Meal promotions generate a 10.9% response rate from our customers while also having the highest overall total checkout price. The emailer has a 8.1% response rate, and 4.2% of our customers responded to both meal promotions and the emailer.
    • A large number of fulfillment centers exist in city 526 and City 590. City 526 has 8 centers and City 590 has 9.
    • City 526 has 8 fulfillment centers, and City 590 has 9 fulfillment centers. By combining center 53 with center 153 as well as combining center 41 and 124, we can reduce the number of centers without losing any sales.
    • Based off of the current trend in the total number of order per week, it appears that there may be a future drop in orders.

    What do our customers want?

    To better understand the customer base and their meal preference, we need to understand out what they like to order. When comparing the total number of orders per region for each food category, it becomes very apparent that our customers prefer the Beverages category. The number of orders for items in the Beverages category surpasses all orders for each region as well as all orders for every other category.

    Could running promotions for the least popular food categories increase orders?

    Our email promotion received a response rate of 8.1% and our feature meal promotion had a response rate of 10.9%. We had 4.2% of our customers response to both emailer and meal promotions at the same time. The bar chart below also confirms that meal promotions generate more money from checkout sales than the emailer.

    Do we need more than 3 fulfillment centers in a city?

    In order to improve operations, we need to investigate the large number of fulfillment centers in City 526 and City 590. City 526 has 8 centers while City 590 has 9 total centers while most cities have 3 or less centers. That leads to the question would it be beneficial to keep the number of fulfillment centers the same, combine centers, or, open new centers?

    When grouping the Center ID's in City 526 and 590 by fulfillment center type, an uneven distribution of orders per area covered appears. The most uneven distribution occures in City 590's fulfillment center A and fulfillmente center C.