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Introduction to the Product Cloud
Introduction to the Product Cloud

Which products yield the most profit? Read more about how to analyze on product level. (shopify only)

Tim Schouten avatar
Written by Tim Schouten
Updated over a week ago

Welcome to the Product Cloud.

Which products perform well and which products are in stock but do not contribute to the total revenue? The Product Cloud gives an extensive overview and serves as a tool to make the right decisions about the products you sell and hold in stock.

Product Intelligence

Product Intelligence is used to gain insight into the performance of individual products. Use the search bar above the table to search for specific products.

Product insights

This table shows all sold products in the selected period.

Product - Product name

Line item - Other name for stock keeping unit (SKU) i.e. the name of the unique product that you keep in stock.

Revenue - Generated revenue in the selected period.

Qty - Number of products sold.

N of orders - Number of orders in the selected period.

Return Qty - Number of returns in the selected period.

Return rate - Number of returns / Number of sold products expressed in a percentage.

Days in stock - Number of days that a product was in stock in the selected period.

Days out of stock - Number of days in which the product was out of stock in the selected period.

Revenue pp - pp stands for previous period, i.e. the revenue of the previous period. The previous periods consist of the exact number of days previous to the current period.

Qty pp - The number of sold products in the previous period.

Revenue py - py stand for per year, so revenue in the previous year.

Qty py - Number of sold products in the last year.

% revenue - The percentage of the total revenue that this product generated.

N. of stock - Number of products in stock.

Track stock - Is stock tracking activated in Shopify? In case this field is blank it is not tracked. In case the value is True, the stock is being tracked.

Unit cost - Cost price of the product. This can be tracked in Shopify.

Pareto analyse

The Pareto analyse, known by marketers as the 80/20 rule. The Pareto rule assumes that in many cases, 20% of the input is responsible for 80% of the output. In e-commerce it indicates which 20% of the products are responsible for 80% of the revenue. Below this is displayed in a graph.

The Y-axis represents the chosen metric: Sales value or quantity. The Y-axis on the right represents the cumulative percentage.

The x-axis represents products. In this graph, you can see the products that are responsible for 80% of the revenue. And you can see the products that didn’t contribute to the total revenue. Based on this information, you can choose to advertise certain products more or to stop offering these products in your webshop.

Total revenue

In this overview, you see the contribution per product and SKU to the total revenue.

Zoom in by clicking on a product.

First Orders

This table displays the products and SKU’s that customers ordered with their first order.

Returning Orders

This table displays the products and SKU’s that customers bought on a return order.

Product Journey Overview

In this table are the products that have been ordered in following order. And the number of times this occurred.

Growth Insights

The Growth Insights graph gives insight in the grow of products relative to the previous period. You can adjust the metric that is displayed on the x-axis to Purchase Qty Growth, Number of orders growth or Revenue Growth. Hoover over de colored cirkles to show additional information of the product in current and previous period.

Product Combinations

In Product Combinations you can gain insight in which products and SKUs are bought together. You see how many times a combination has occurred and Billy Grace calculates if there is a correlation. In the table this is expressed in three metrics:

  • Confidence: The chance that if a customer buys product 2, product 1 is also bought.

  • Support: The percentage of all orders that contained this combination. i.e. number of orders with combination / all orders.

  • Lift: This is the factor of how many times the combination more often occurs than the individual product. A factor of 1 indicates that the products are independent. A factor higher than 1 indicates that the products have a positive effect on each other and are frequently bought together. A factor lower than 1 indicates that buying the product has a negative effect on buying the second product.

Stock Intelligence

Stock Intelligence gives insight into your SKU stock levels in different preset time periods. Next to this, it gives insight into the generated revenue relative to the available stock. The time periods that can be used are: the last 6 months, 12 weeks, 4 weeks or 2 weeks.

Important: Billy Grace can only show the proper insights if stock is being actively tracked in Shopify.

SKU’s In Stock - Number of SKU’s in stock.

SKU’s Out of Stock - Number of SKU’s out of stock.

% Revenue L6M Out of Stock - Part of the revenue that was generated in the past 6 months by products that are now out of stock. Expressed in a percentage.

Inventory insights

An overview on product level. The table displays revenue, number of products sold, the number of orders, current stock, days in or out of stock in the selected period.

Out of Stock SKU’s

This graph displays the products that no longer in stock relative to the revenue. Number of orders of the number that is generated in the selected period.

Daily Stock Availability as % of Revenue L6M

The daily availability of stock as a percentage of the revenue generated in the past six months. Which products were in stock and which products were out of stock? If the out of stock line is bigger than the in stock line that it is important to purchase new stock, otherwise your revenue will probably decrease.

Inventory Value By Sku

The total sales value of products that are currently in stock. In the top right corner you can change the filter to all products, products that haven’t been sold in the last three or six months (dead stock).

Months since last purchase vs inventory value

Y-axis - Inventory value

X-axis - Number of months since last purchase.

Total sales value of products that are in stock per the number of months since the products have last been sold. The never sold bar contains the total inventory value of products that have never been sold.

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