SKU-Level Transaction Data: Definition, Sources & Datasets to Buy

What are Examples of SKU-Level Transaction Data?

Examples of SKU-level transaction data include details about individual products, such as their identifiers, quantities sold, prices, and purchase dates. This data is used for analyzing sales patterns, managing inventory, forecasting demand, and making informed business decisions.

• Quantities Sold: The number of units sold in a specific period. For example, “50 units sold in May 2024”.
• Sale Prices: The prices at which products are sold. For example, “Price: $29.99”.
• Dates and Times of Purchases: When the products were sold. For example, “Sold on May 15, 2024, at 2:30 PM”.
• Customer Information: Data about the customers who purchased the products. For example, “Customer ID: CUST1234, Name: John Doe”.
• Sales Channels: Where the sales occurred. For example, “Online Store, In-Store Purchase”.
• Inventory Levels: The amount of stock available. For example, “Current Stock: 200 units”.
• Product Returns and Exchanges: Details about returned or exchanged products. For example, “Returned: 5 units on May 20, 2024”.

SKU-Level Data Attributes

• SKU Code: A unique identifier assigned to each product. For example, “SKU12345”.
• Product Name: The name of the product associated with the SKU. For example, “Wireless Mouse”.
• Category: The category to which the product belongs. For example, “Electronics”.
• Brand: The brand of the product. For example, “Logitech”.
• Model Number: The model number of the product. For example, “M325”.
• Specifications: Detailed product specifications. For example, “Color: Black, Connectivity: Wireless, Battery Life: 3 months”.
• Supplier Information: Details about the supplier of the product. For example, “Supplier: ABC Electronics”.

How SKU-Level Transaction Data is Collected?

Collecting SKU-level transaction data involves using Point-of-Sale (POS) systems, e-commerce platforms, and inventory management software. These systems record transactional data each time a sale happens.

• POS Data: Contains and captures SKU-level data at purchase.
• E-commerce Platforms: Record detailed sales data for online transactions.
• Inventory Management Software: Tracks inventory levels and movements, providing additional context to SKU-Level Data.

Uses Cases for SKU-Level Transaction Data

SKU-Level Data is crucial for various business purposes:

• Inventory Management: Maintain optimal inventory levels to prevent shortages and overstock.
• Sales Analysis: Understand product performance and identify sales trends.
• Customer Insights: Analyze buying patterns to tailor marketing efforts.
• Pricing Strategies: Optimize pricing based on sales performance and market trends.
• Demand Forecasting: Predict future sales and adjust inventory accordingly.

SKU-Level Data Benefits

The benefits of using SKU-Level Data include:

• Better Decision-Making: Make informed choices based on detailed sales data.
• Increased Efficiency: Streamline operations by optimizing inventory and reducing waste.
• Higher Sales: Identify high-performing products and focus marketing efforts.
• Customer Satisfaction: Understand customer preferences and enhance their shopping experience.
• Cost Savings: Reduce holding costs by maintaining optimal inventory levels.

How to Categorize SKU-Level Data?

Categorizing SKUs can help streamline inventory management and improve sales analysis:

• By Product Type: Group similar products together.
• By Sales Volume: Classify SKUs into high, medium, and low sales categories.
• By Profit Margin: Categorize based on profitability.
• By Seasonality: Group products that are seasonal or have varying demand throughout the year.

What is a Good SKU-Level Data Format?

A good SKU format is vital for effective inventory management and sales tracking. Here are some tips for creating an effective SKU format:

1. Consistency: Use the same format for all SKUs to avoid confusion.
2. Simplicity: Keep the SKU format simple and easy to understand.
3. Descriptive: Include relevant information such as product type, size, color, and other characteristics.
4. Distinctive: Make sure each SKU is unique to avoid duplication and errors.

What are the Types of SKU-Level Data?

There are several types of SKUs, each serving a specific purpose in inventory management and sales tracking:

• Style SKU: Identifies a product style.
• Size SKU: Specifies the size of a product.
• Configuration SKU: Refers to products with different configurations, such as sizes or colors.
• Bundle SKU: Identifies a combination of multiple products.
• Serialized SKU: Uniquely identifies each item within a product line.
• Matrix SKU: Combines different characteristics of a product, such as size and color, into one SKU.

How to Track SKU-Level Data?

Tracking SKUs effectively involves several steps:

• Use Inventory Management Software: Implement software that allows for real-time tracking of SKUs.
• Regular Audits: Conduct regular inventory checks to ensure accuracy.
• Barcode Scanning: Utilize barcode scanning technology to speed up the tracking process.
• Data Integration: Integrate SKU data with other business systems for a comprehensive view.

What is SKU-Level Analysis?

SKU-level analysis involves examining detailed transactional data for individual products to gain insights into sales performance, inventory management, and customer preferences. This type of analysis helps businesses make data-driven decisions that can lead to increased efficiency and profitability.

What is SKU-Level Forecasting?

SKU-level forecasting involves predicting future sales and inventory needs for individual products based on historical SKU-level transaction data. This type of forecasting helps businesses prepare for demand fluctuations and maintain optimal inventory levels.