Step 1: Exporting Data from MuleBuy

Navigate to your MuleBuy order or product dashboard. Locate the export function (typically a CSV or Excel button). Select the desired date range and data fields. Crucial fields to include are: Product ID, Product Name, Supplier, Unit Cost, Order Quantity, Shipping Method, and Order Date. Download and save the file securely.

Step 2: Preparing Your Cost Analytics Data

In your separate analytics tool or spreadsheet, ensure you have calculated key metrics such as Advertising Cost of Sale (ACOS), customer acquisition cost, landed costnet profit per unit. This dataset should have a common key with the MuleBuy export, like Product IDSKU, to enable a clean merge.

Step 3: Merging the Datasets

Using a tool like Excel, Google Sheets, or a BI platform (e.g., Tableau, Power BI):

1. Import both the MuleBuy export and your cost analytics file.
2. Use a VLOOKUP, XLOOKUP, or INDEX-MATCHProduct ID.
3. Alternatively, use the built-in "Merge Queries" feature in Power Query for a more robust, repeatable process.

The goal is a single, unified dataset where each product row contains both sourcing and profitability data.

Step 4: Performing Market Analysis

With your merged data, you can now create pivot tables and charts to answer critical business questions:

• Sourcing Trends:
• Volume Efficiency:
• Category Health: