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Product Basket Analysis with Datadrew
Product Basket Analysis with Datadrew

Understand which products are frequently bought together on your Shopify store and optimise cross-sells and product promotions.

Updated over a week ago

Retail giants like Amazon, Walmart rely heavily on this commerce strategy of showing the frequently bought together products to cross-sell and upsell their products. It helps figure out the shopping trends, patterns across different channels not limited to online but offline also.

Benefits of basket analysis or cart analysis or Frequently bought together products -

  • Create New Product Bundles: Identify items often purchased together to create attractive product combos.

  • Enhance Product Recommendations: Display complementary products on product pages to increase cart size and boost “add to cart” rates.

  • Upsell on the Thank You Page: Suggest additional products after purchase to encourage immediate repeat sales.

  • Optimize Cross-Selling in Marketing: Use insights for targeted promotions via email, WhatsApp, SMS, and ads, showcasing other items commonly bought together by similar customers.

  • Compare Combos for Revenue Growth: Compare different product combinations for new sales vs repeat sales.

Product basket analysis or cart analysis for Shopify brands

How to use Basket analysis in Datadrew platform -

By default it gives you the product baskets sorted by highest numbers of orders. You can choose whether you want to see baskets with minimum 2, 3 or 4 products. You can also customise the report as per your needs with following options like timeperiod, breakdown by product or SKU or vendor or product type.

KPIs for frequently bought together products -

  • #Orders: Number of orders which included these products bundles

  • Total sales: Total revenue from these product bundles

  • %Orders: The percentage of orders that included these products

  • AOV: Total sales of all orders including these products / number of all orders including these products

  • New orders: Number of new orders which include these products

  • New sales: Sales of new orders which include these products

  • Returning orders: Number of returning orders which include these products

  • Returning sales: Sales of returning orders which include these products

Filters

You can further slice and dice this data with the filters.

  • Order and Customer Tags -

    • Exclude or include orders with certain order tags or customer tags

  • Location

    • Country

    • State

    • City

  • Product

    • Tags (e.g., new season vs. old season)

    • SKU

    • Vendor

Share with team and put it to action -

You can export the csv and share with your team. You can also share access of the platform from settings so your team can come up with other impactful insights and collaborate with you.

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