Amazon store group management: quadrant analysis and category correlation analysis

In order to improve operational efficiency in the Amazon store group management process, operations team managers can use “quadrant analysis” and “category correlation analysis” to achieve refined management. This article will introduce the application of these two methods in detail.

Application of Quadrant Analysis

The quadrant analysis method can help operators quantify advertising effects from a macro perspective and apply it to team management and data analysis. Key metrics for Amazon stores include profit margin, sales, and cost per order. By setting the profit margin as the horizontal axis, the cost of a single order as the vertical axis, and sales as the area size of the bubble chart, the data of each store can be presented visually and divided into four quadrants. Combining the characteristics of each quadrant, operators can judge the store’s operating status and adopt corresponding management methods, such as optimization methods or adjustment methods.

Optimization means

The optimization method aims to optimize stores in poor quadrants (such as I, II, III) to good quadrants (such as V) through operational strategies, thereby improving the overall operational efficiency of the team.

Adjustment methods

The adjustment method focuses on “increasing revenue and reducing expenditure”, and adjusting sales for stores in different quadrants. For example, for old stores that are not performing well but have a certain amount of sales, you can choose to abandon them; while for stores that are performing better, you should further expand the sales scale.

Category correlation analysis

Category correlation analysis uses visual information on the store’s main categories to determine the relationship between different categories and store profit margins, single order costs and sales. Taking the three product categories A, B, and C as an example, you can find that their distribution on the bubble chart has its own characteristics:

• Category A: Low order costs, high or low profit margins. Stores with high profit margins and high sales indicate that products in this category have high market potential and should receive more resource support.
• Category B: The order cost is proportional to the profit margin, indicating that it is a potential product. Operational strategies and supply chains need to be further optimized to reduce costs and increase sales.
• Category C: The order cost is high, the profit margin is low, and the sales are not high. It is recommended to give up and switch to more promising products.

Through the above analysis, managers can not only identify core products and potential products, but also adjust strategic directions in a timely manner to ensure that resources are effectively utilized.

In summary, both quadrant analysis and category correlation analysis can provide strong support for Amazon store group management, helping companies better understand market dynamics and formulate scientific and reasonable business strategies.