The so-called category correlation analysis is to judge the relationship between different categories and the operating dimensions such as store profit margin, single order cost and sales through the visualization information of the main categories of each store.
First, open the “Store Group Data Management” table, you can find a column of data named “Main Product Category”, which refers to the sub-category of products mainly sold by a store, such as shoes, T-shirts, skirts, hats, pants, etc. in the clothing industry.
Through “Profit Margin”, “Single Order Cost” and “Sales”, you can get a bubble chart of store group sales data.
Because the 10 stores in the case chart involve a total of 3 product categories, namely A, B, and C, the team manager can mark these 3 product categories in the original bubble chart with 3 different colors. The color filling operation of the bubbles in the bubble chart is: right-click the bubble whose color you want to change, then click the “Fill” option, and then select the color you want to fill.
In this case, the A category is marked with green, the B category is marked with red, and the C category is marked with blue, and the new information is visualized in the bubble chart.
Regarding Category A, it can be found that its operating stores are located in the lower half of the chart, that is, in the Dish quadrant and the IV quadrant.
It can be seen that the order costs of the stores operating Category A are relatively low, which may be caused by the following reasons.
1The production cost of Category A products is low.
2The operators of Category A stores are experienced, and the labor cost and operating cost are low.
3Category A does not rely on off-site traffic and promotion, and the marketing cost is low.
At the same time, the operator can observe that the profit margins of stores operating Category A are high and low, and the sales of stores with high profit margins are also high, which shows that Category A products can obtain high profits while maintaining low order costs. Then the products in this category belong to the core products of the team, and the team managers need to give appropriate resources (such as marketing resources, supply chain resources, etc.) to further increase profits.
Regarding Category B, it can be found that its operating stores are located in the oblique part of the chart, that is, in the I and III quadrants.
The cost of each order of a store operating Category B is proportional to the profit margin, that is, the higher the cost of a single order, the higher the profit margin. This phenomenon is generally caused by the following reasons: Category B market is a blue ocean market. As the cost of marketing and supply chain optimization of Category B products increases, the sales and profits of Category B will also increase. This category of products belongs to the team’s potential products. Therefore, team managers need to further optimize the operation strategy and supply chain of Category B products, and steadily increase the sales and profit margin of Category B products on the premise of gradually reducing the cost of a single order.
As for Category C, it can be found that its operating stores are located in the upper half of the chart, that is, in quadrants I and II.
It can be seen that the cost of each order of a store operating Category C is relatively high, which may be caused by multiple reasons.
1C Category products have high production costs.
2C Category store operators lack experience, and labor costs and operating costs are high.
3C Category relies heavily on off-site traffic and promotion, and marketing costs are high.
At the same time, operators can observe the operation. The profit margin of Category C stores is low, and the store sales are not high, which shows that Category C products themselves have neither market potential nor profit margins. Team managers can consider abandoning Category C and shifting the focus of operations to the core products of Category A or the potential products of Category B.