Store Inventory Analysis

🔍 Dataset Link

  store_inventory.csv

📌 Objective

To evaluate how store inventory interacts with external and internal sales-driving factors like pricing, promotions, weather conditions, and seasonal demand patterns.

 

📊 Dataset Fields

Column Name

Data Type

Description

Date

Date

The date of the transaction.

Store ID

String

Unique identifier for the store.

Product ID

String

Unique identifier for the product.

Category

String

Product category (e.g., Clothing, Electronics).

Region

String

Region where the store is located.

Inventory Level

Integer

Available stock at the start of the day.

Units Sold

Integer

Number of units sold that day.

Units Ordered

Integer

Number of units ordered that day (restocking).

Price

Float

Listed selling price per unit.

Discount

Float

Discount amount applied to each sale.

Weather Condition

String

Description of weather (e.g., Snowy, Sunny).

Promotion

Integer (0/1)

1 if the product was under promotion; else 0.

Competitor Pricing

Float

Average market price for similar products.

Seasonality

String

The current season (e.g., Winter, Summer).

Epidemic

Integer (0/1)

1 if sales were affected by an epidemic; else 0.

Demand

Integer

Modeled/forecasted customer demand for the product.

 

🔢 Key Calculated Metrics

  1. Revenue
    Units Sold × (Price - Discount)
    ➤ Measures actual earnings after discounts.
     
  2. Remaining Inventory
    Inventory Level - Units Sold
    ➤ Indicates stock that remains unsold at day's end.
     
  3. Demand Ratio
    Demand / Inventory Level
    ➤ Highlights how well inventory matches expected demand.
     

 

📈 Use Cases

  • Evaluating promotion effectiveness on sales and revenue.
     
  • Analyzing sales patterns by season and weather.
     
  • Adjusting inventory levels based on real vs. expected demand.
     
  • Comparing pricing strategy with competitors.
     
  • Studying impact of external disruptions (e.g., epidemics) on store operations.
     

 

📊 Visualizations

  • Bar chart: Revenue by category or store.
     
  • Line chart: Sales trends over time.
     
  • Box plot: Units sold vs. weather condition.
     
  • Scatter plot: Price vs. Competitor Pricing.
     

 

Google Collab: Store Inventory