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Basket Analysis | 4 ways to use “product purchase data” to optimize conversions, AOV, & LTV

If you run a multi-skew eCommerce, one of the highest ROI analyses you can do for your store is called Basket Analysis. A super-powerful data mining technique used to uncover patterns of products purchased together helping you optimize 3 things:

✅Conversion Rates
✅Average Order Value
✅Customer Lifetime Value

Here are a few experiments you can run using the insights from Basket Analysis:

1) Bundle Products: If there’s a low-to-medium correlation between 2 products, we’ll test bundling to see if it increases the frequency of both products being purchased together

2) Un-Bundle Products: If there’s a medium-to-high correlation between 2 bundled products, we’ll test unbundling them to see if the CR stays constant WITHOUT a “bundle discount” increasing profit margin & AOV

3) Strategic Discounts: If there’s a medium-to-high correlation of 1 product being purchased with another (but not vice versa) we’ll test slightly discounting the primary product to increase conversions of the secondary, supporting, product

4) Up-Sell Strategy: If there’s a low-to-medium correlation of 1 product being purchased with other products (but not on its own) we’ll test presenting that as post-purchase upsell using an OTO (one-time-offer) to create urgency

My team just created an article going over Basket Analysis in more detail. I obviously can't share it here, but if you're interested let me know.

submitted by /u/sinafak
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