BASKET ANALYSIS | 4 ways multi-skew eCommerce stores can use “product purchase data” to optimize conversions, AOV, & LTV

I love data. There are so many opportunities you uncover when you start digging into it.

One of the highest ROI analyses we do for eCommerce stores is called BASKET ANALYSIS.

It's a super-powerful data mining technique our team uses to uncover meaningful patterns of products frequently purchased together throughout the store.

We use the data to optimize:

✅Conversion Rates
✅Average Order Value
✅Customer Lifetime Value

Here are a few experiments we 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.

Obviously can't share a link here but if you're interested let me know.

[Cool neon basket analysis cover photo]

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