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Trusted by global DTC brands
The Category Cross-Sell Analysis Hop offers a detailed examination of customer buying behavior across various product categories. For all customers who purchased Category A, the report shows the percentage of those customers who subsequently purchased Category B.
Looking at cells A2 and B1 of this report, Category A is Toys, and Category B is also Toys. This report may show that 25.67% of customers who purchased Toys bought Toys again in subsequent orders indicating strong customer preferences.
If we look at cells A5 and C1 of this report, Category A is T-shirts, and Category B is Shoes. This report may show that 19% of customers who purchased T-shirts also bought Shoes in subsequent orders. This indicates complementary purchase behavior between t-shirts and shoes.
Integration(s)
How to use this Hop.
Simply create an Airboxr account and connect your Shopify store to automatically run this export/analysis for your store. If you already have an account, click on the Add to my Collection button above.
Enhancing Product Recommendations: E-commerce platforms can leverage this data to refine their recommendation algorithms. This report is especially useful for certain product categories that customers tend to not purchase frequently, such as Watches or Shoes. Once a customer has purchased such items once, they are unlikely to purchase the same category of product as they do not need so many of such items. Hence, by recommending them other product categories you can encourage repeat sales and increase your customer LTV.
Fine-Tuning Product Bundling Strategies: E-commerce stores can use the Category Cross-Sell Analysis Hop to identify product categories frequently bought together. Stores can craft enticing product bundles using this information. For instance, if customers purchasing Shoes also buy Shoes, the store can create exclusive offers for these categories, encouraging customers to purchase both, thereby enhancing sales and customer satisfaction.
Crafting Targeted Marketing Campaigns: An understanding of the relationship between different product categories empowers e-commerce businesses to create precise and personalized marketing campaigns. In the above example, for customers who have purchased T-shirts, the store can design tailored promotions for Shoes, increasing the probability of repeat purchases. By aligning marketing efforts with customer preferences, businesses can significantly improve customer engagement and drive revenue growth.
Streamlining Inventory Management: Precise insights into customer purchasing behavior enable the optimization of a brand’s inventory effectively. By stocking up on products that are frequently demanded together, businesses can mitigate stockouts and ensure they meet customer demand efficiently. This streamlined approach not only enhances customer satisfaction but also prevents missed sales opportunities, fostering a seamless shopping experience.
Elevating Customer Experience: By offering customers products that align with their purchase history and preferences, e-commerce stores improve the overall shopping experience. Satisfied customers are more likely to become loyal, leading to increased customer retention.
In This Report
Metrics
Cross-sell rate
Grouped By
Product Category
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