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From the Little Stream Software blog
A number of people have been asking about how to tell which products are bought together. e.g. does this shirt get bought with these pants or these shorts?
This is called a market basket analysis or an affinity analysis in more general statistics.
The market basket analysis process can be simple or complex depending on how many products you have and how many orders you're analyzing. If you want to start with a simpler version, just analyze the last 12 months of orders and only look at products (ignore variants for now).
Some product analysis Shopify apps can help with this if the data crunching is too complex. Just be cautious of over-hyped "AI" systems that can't explain how their analysis runs. There are well-known, supported-by-research algorithms that can work for 99% of stores.
Once you find out which products are related, you have a quite a few options to improve your marketing and merchandising:
- adjusting primary sales messages (e.g. homepage)
- creating new categories to highlight related products
- showing related products on the product page (with some smarts instead of just using product tags)
- creating bundle of related products
- adjusting cross-selling to promote the more likely products
One thing to be ready for is finding unexpected matches. These are products that are frequently bought together that you had no idea about.
As with any analysis, you'll want to refresh your data on a regular basis as the customer behavior changes. For a busy store with a lot of products and orders, this might be every month. For a small store that only introduces new products once a year, this might be every six months.
Performing a market basket analysis may seem daunting, but with the right tools and approach, you can gain valuable product insights to help grow your Shopify store.
While Repeat Customer Insights has a product analysis, it is focused on which products create better customers, not which products are bought together. Product affinity might be an area I expand to later.
Eric Davis
