Question 1

Question 2

Question 3

Question 4

Question 5
a)
b)
c)

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d)
e)
Revenue by month
Revenue by year
Revenue by Payment

Your task is to answer one or more of the following questions listed below:

Predict the total amount of sales for the store, for each category, and for each item in the next 3 months. (You can define your own metrics if you wish to.)

What trends do you notice for the store with respect to transactions?

What trends do you notice for the store with respect to time?

What trends do you notice with respect to the categories & items listed?

Are there any categories or items the store should immediately focus on?

Given Inventory levels, price, rate of purchase etc., what are some (1 to 2) products that can be considered for a price reduction?

Give a sales analysis report answering fundamental questions that the store owner wants to know:
The highest selling products by month and category
The least selling products by month and category
The most profitable month by sales
What are the most efficient ways that the store can reduce losses
Any other question you can think of!

Shikhar and Aayush - Orange
Prachi and Vaibhav - Blue

Category & items -> Trends (Day of the week, Month, Year, Season, Overall) => Profit, Selling price change over time (UNIT_PRICESELL), Revenue, OPTIONAL (Payment method, margin)

Focus -> UNIT_PRICEBUY increasing but MARGIN decreasing,

Price Reduction -> Highlight Table top few and bottom few

Category
Items
Payment Method
Transaction
Profit

Transactions

To begin our analysis, we first set out by exploring the store transactions.

Analyzing the number of transactions with the days of the week, we find that the store sees maximum transactions on Thursdays.
Saturdays also see a significant number of transactions which can be attributed to the fact that it is the weekend.

Over a day, we find that maximum transactions happen in the time range 8 AM - 2 PM for every year except 2016.
2016 seems to be anomalous in this case as it shows an exact opposite trend. In 2016, minimum transactions happened during the day and maximum transactions took place in late-night hours.

The number of transactions for the other years peaks in the summer season.
The data provided is from March 2016 to October 2019. Transactions of the two months of summer in 2016 and one month of summer in 2019 are thus not included.
Hence, we can consider the store sees maximum transactions in the summer season.

Profit

When we look at the average profit by the hour, we see that the store profits most in the time period 7 PM - 9 PM.
The distribution of average profit over the day seems uniform. This means that the store profits consistently in a day.

Considering total profit, the month of May has been the most profitable over the years.
This is excluding the first two months of 2016 and the last two months of 2019, which are not included in the data provided.

When we look at the seasons, summer proves to be the most profitable for most years.
It is to be noted that two months of summer in 2016 and one month of summer in 2019 are not included in the dataset.

Category

From the heatmap, we can see that in terms of overall Profit, the Category ‘Other Vegies’ comes out on top, having accrued $138,988 dollars in profits over the 4 year time period.
To explore further, we plot the Total Profit by Category, and filter the top 3 Categories in each year:

We can see that the top 3 categories remain the same across the 4-year time period, with profits from ‘Citrus’ gradually decreasing, and with ‘Other Vegies’ being the category accruing maximum profits each year.
It might be interesting to analyze if there is a seasonality amongst these profit trends. We thus plot the Top 3 categories for each season across the 4 year period:

On comparing the highest profits by season, it doesn’t come as a surprise that the ‘Other Vegies’ category generated the highest profit across all the seasons. However, we observe that ‘Citrus’ accrues greater profits than ‘Potatoes’ in the winter season.
Upon further research into the seasonality of Australian fruits, we found that ‘Citrus’ fruits are actually in season during Winter, which explains the spike in the above graph (Referenced from https://citrusaustralia.com.au/uncategorised/season)
To drill deeper, we next explore the category accruing the most profit over each month:

The above visualization represents the highest profit in each month from 2016 March-2019 October. In the months of January, February, March, and December ‘Stonefruits’ generated the highest profits, and in the rest of the months, ‘Other Veggies’ was the category that generated the highest profits.
Upon further research into the seasonality of Australian fruits, we found that ‘Stonefruits’ fruits are actually in season during Summer, which explains the spike in the above graph.
In accordance with the original prompt, we shall also explore the volume of transactions to find the highest selling category for each month
http://seasonalfoodguide.com/australia-general-seasonal-fresh-produce-guide-fruits-vegetables-in-season-availability.html

The pattern here closely resembles the one in the previous visualization where we looked at products generating the maximum profit
The above visualization represents the highest-selling category in each month from 2016 March-2018 October. In the months January, February, March, and December ‘Stonefruits’ was the highest-selling category, and in the rest of the months, ‘Other Veggies’ was the highest-selling category.

Payment method

When we look at the payment method used in-store transactions, we can say that more and more customers are adopting the magcard payment method.
Cash transactions have rapidly decreased since mid-2016.
The year 2019 saw a decrease in the number of transactions for both payment methods.

Additionally, we see that magcard transactions are increasingly contributing to the store’s total profit share.