+2
We use WooCommerce and have a fairly large catalog of 70+ products. I’m looking for a way that we can analyze orders over a certain period of time to determine which products are frequently purchased together. Is this possible with Klaviyo?
Best answer by stephen.trumble
View original
+60
Hey
This is such a great question, thank you for coming to the Klaviyo Community to ask!
Before I try to answer this, I would love to know if anyone in the community currently uses our data analytics in this way?
Lets see what the Community thinks first, but I will follow up by the end of the day if no one else has tried this!
+38
Great question, I actually haven’t use Klaviyo analytics in that way before. I’d be curious to see your answer
+2
For what it’s worth, it seems like this SHOULD be possible given that Klaviyo has full access to our entire WooCommerce order database. I know services like Metorik can do this.
+60
Hey
I’ve been asking around and have been exploring Klaviyo analytics and as of now, doing a broad based analysis cross referencing all of your products purchased with another product is not available in Klaviyo. However if you have specific products you want to track with each other you can set up segments based on someone who purchased product A in the last X days AND someone who has purchased product B in the last X days. This only works if you are targeting specific items. There may be ways within your ecommerce platform to accomplish this or through a custom API integration but currently cannot do a broad analysis on Klaviyo.
Thank you for your patients while i worked through all option.
+2
Unfortunately with a catalog of 70+ items, it’s really impractical to do analytics manually on specific sets of products. There would be thousands of possible combinations. That’s disappointing that Klaviyo lacks this functionality, especially given the premium price tag.
BIG +1 on something like this. I’m working with a client with a large number of SKU’s too, and they’re often purchased in combinations that are really difficult to predict/group. A “frequently purchased together” feature would be amazing.
Enter your username or e-mail address. We'll send you an e-mail with instructions to reset your password.
