Grocery_store_sales_analysis

The analysed dataset is sourced from Kaggle and it consists of a Chinese grocery store sales. Various statistical methods were carried on to deduce insights that will help the business make data-driven decisions. Some of the decisions that can be made touch on:

1. What are the most Effective hours of operation

2. Which categories and items sell well and which can be dropped or have more marketing on them to increase their sales

3. Which hours do we attribute our highest sales to and which do we poorly sell

4. Do discounts have an impact on our sales

5. What is the share of returned goods and how much are they worth

6. What are our monthly/yearly revenues

7. How much weight do we sell per category, a statistic that could help in supply chain decisions

8. What are the visible patterns on our sales

These questions will be answered by our analysis on the company's data.

BUSINESS INSIGHTS

1. The store operates for 16 hours. The lowest sales year to year are at 8 a.m.-9 a.m and 11 p.m. Coincidentally, these are the closing and
   opening hours. This can mean either the stocks haven't been shelved, there is low foot traffic or there is no use of selling groceries at this time. The store should sit and re-evaluate if it makes business sense to operate in such times as there are possibilities to cut some costs if the store isn't opened till nine e.g., electricity bills and staff wages.

2. The best selling hour is 10 - 11 a.m. We can assume may be this is hotels and cafeterias buying the groceries for lunch preparation. We are able to declare hours between 2 p.m and 8 p.m as our rush hours. There seems to be a buzz of activities given the number of sales around this time. We can also declare the peak rush hour to be between 4 p.m. and 6 p.m. seemingly when people are leaving for home from work. The store can display as much greens as possible during this rush hours and 10-11 a.m. as well as apply the discounts during such times to maximize on the sales as much as possible. This will eventually cover up for the slow moving hours. Remember it's not the aggresiveness but the effectiveness of the plans that make a mark.

3. The year 2021 generated the most revenues from the data. However, we only have half month's data for 2020 and 2023. Neverthless, we can attribute the improved numbers in 2021 to the ease of lockdown measures from COVID-19. The sales then dipped in 2022. The store can measure several factors that may have led to the dip e.g., did number of discounts decrease from 2021? and how many
   returned goods are there in each year. This is meant to visualize the factors that lead to surge and dips in sales to enhance
   effective decision making.

4. From a hypothesis test carried on the discounts and revenues, we deduce there is a significant difference between discounted and non- discounted goods. Meaning discounts play a significant role over the rates of sales, many tasty discounts may highly equal to more sales.

5. Edible mushrooms generated the highest revenues back to back followed by capsicum. Solanum and cabbage generated the least income. Such insights will help the store evaluate how much does it cost to sell Solanum and cabbage and compare that to the revenues they generated. This will help decide on the future of these categories. Edible mushrooms and Capsicum can then enjoy more shelf space and discounts to maximize on their demand as much as possible. Farmers/Sources can then be advised to increase farming space for these categories to satisfy the demand.

6. Kilo wise, Flower/Leaf Vegetables had the most kilos sold followed by capsicum. Solanum and Aquatic tubers had the least kilos sold This insight will help strategize on efficient asupply chain e.g., does solanum and aquatic tubers take so much container/storage space during shipping that it costs us more money compared to little returns generated from these categories? Much container/storage space could then be given to Flower/Leaf Vegetables and capsicum.

7. The fastest moving items are Wuhu Green Pepper(69,945 pieces) sold and Broccoli(58,906) whereas the slowest moving items are Hericium, Black Mushroom both in edible mushroom category.Perhaps the store having high sales in other types of mushrooms could choose to drop these two.

8. Returned goods percetage share is 0.05% of the total goods. This means 5 of every 100 items are returns.The store may want to have a look at this and strategize on how to reduce that.

Such beautiful insights will go along way in helping the Chinese grocery store make data-driven decisions on how to maximise sales, increase profits and cut costs effectively.