The Cross-Sell Analysis Hop offers a detailed examination of customer buying behavior across various products. For all customers who purchased Product A, the report shows the percentage of those customers who subsequently purchased Product B.
The report contains percentages of all orders that contain the SKUs in the header row made by customers who purchased the SKUs in the columns first. In this case, 51% of customers who ordered TOY 304 first bought TOY 304 again at some point in their customer lifetime.
For example, let’s say product A is an iPhone 15, and product B is a MagSafe wireless charger. This report may show that 70% of customers who purchased an iPhone 15 also bought a MagSafe wireless charger in subsequent orders, indicating a high demand for wireless charging of their new iPhone 15s.
Additionally, suppose 30% of customers who also bought iPhone 15s bought Belkin Wireless Car Charger, this means that customers not only want a MagSafe wireless charger, they want one that can be used in their cars as well.
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.
Optimizing Product Bundling Strategies: E-commerce stores can use the report data to identify products that are bought after certain purchases. With this knowledge, they can create attractive product bundles. For instance, if iPhone 15s and MagSafe wireless chargers are common in customer’s order journeys, the store can create special offers for these items, encouraging customers to buy both, thereby increasing sales and customer satisfaction.
Personalized Remarketing Campaigns: Understanding the relationship between different products enables e-commerce businesses to create targeted and personalized remarketing campaigns. For customers who have purchased iPhone 15s, the store can send tailored promotions for more wireless charging accessories, increasing the likelihood of repeat purchases.
Enhancing Inventory Management: Accurate insights into customer buying behavior allow e-commerce stores to optimize their inventory. By stocking up on products that tend to be demanded after certain purchases, businesses can prevent stockouts and ensure they meet customer demand effectively. This, in turn, improves customer experience and prevents lost sales opportunities.
Refining Product Recommendations: E-commerce platforms can utilize this data to enhance their recommendation algorithms. When customers browse for iPhones, the system can suggest compatible charging accessories based on the high percentage of customers who made similar purchases. This not only aids customers in finding relevant products but also increases the chances of cross-selling.
Improving Customer Experience: By offering customers products that align with their purchase history and preferences, e-commerce stores enhance the overall shopping experience. Happy and satisfied customers are more likely to become loyal, leading to increased customer retention.
In This Report