A data view presenting sales results at the category level, based on data from the Shopify e-commerce platform. The analysis covers all transactions processed by the online store, focusing on product sales aggregated to the product category level.

The report aggregates sales data directly from the Shopify platform, providing a complete picture of purchasing activity at the level of individual categories available in the store's offering. The view enables detailed analysis of the sales performance of each category and identification of the most important product segments in the portfolio.

Currently, the view supports Category Level 1 as the basic level of sales results presentation in the Shopify system.

The report presents data from a selected time range that can be customized using a datepicker (available options: Last 7 Days, Last 14 Days, Last 30 Days, Last 60 Days, Last 90 Days, This month, Last month, and the ability to select custom dates). The default setting is the last 30 days range.

Analyze the distribution of gross and net revenue (Gross/Net Revenue) between product categories to identify key categories generating the highest revenue and categories requiring offer optimization or marketing activities.

Compare the quantity of units sold (Purchase Quantity) with sales value in individual categories to identify categories with the highest sales efficiency and average unit order value.

Monitor percentage change trends across all metrics for individual categories to identify categories that are growing, stable, and declining in popularity, which will help optimize product strategy.

Analyze the percentage share of each category in total sales to assess the strategic importance of individual categories and potential risks associated with dependence on specific product groups.

Compare the number of orders (Orders) with the number of unique customers (Clients) in individual categories to identify categories with the highest repeat purchase rate and potential for building customer loyalty.

Use the category expansion function to analyze the performance of specific products within each category, identifying bestsellers and products requiring optimization or removal from the offering.

Examine relationships between brands (Brand) and product categories to understand brand positioning in different segments and identify portfolio gaps as well as opportunities for developing supplier cooperation.

Analyze the average shopping cart value in individual categories (dividing revenue by number of orders) to identify premium and economic categories and adjust pricing and promotional strategies.

Category - Product category name in the Shopify system (Category Level 1).

Product Variant ID - Unique identifier of the product variant in the Shopify system.

Product Group ID - Product group identifier used to link different variants of the same base product.

Brand - Product brand (visible in category structure and after expanding to product level).

Orders - Total number of unique orders containing products from a given category in the current period.

Clients - Number of unique customers who purchased products from a given category in the current period.

Purchase Quantity - Total quantity of product units sold within the category in the current period.

Gross Revenue - Total gross sales value of all products in the category in the current period.

Net Revenue - Total net sales value of all products in the category in the current period.

Product Age Days - Number of days since a specific product was introduced to the store offering, calculated from the date the product card was created in the Shopify system to the current day. Available at the individual product level after expanding the category.

Expanding category details - By clicking the arrow next to the category name, you can expand the view and see all products belonging to that category along with their individual sales results, brands, and identifiers.

The view offers advanced capabilities for comparing data between periods through "Show Previous Period" and "Show Change Values" functions. Detailed information about using period comparisons, interpreting Previous Period Value, Change (Value), and Change (%) values can be found in the Functionality description - time period comparison.