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Hi, 

I’m wondering if anyone can help me figure out a simple question i have regarding average order value. I’m conducting reports across our engagement segments - (30 days, 60 days, 90 days and 120 days) and i’m pulling out engagement reports from these segments. In all of these, the average order value is the same. To me, this doesn’t seem right. I would assume that the higher the engagement, the higher the order value, no?

 

Can anyone tell me why this is? 

Hello @Conrad,

Welcome to the Klaviyo Community!

I wouldn’t say that assumption would be entirely accurate. I believe a better assumption is that the more engaged user are, the more likely they are to purchase or make a repeat purchase. However, that does not mean a higher order value though. 

For example, if your store predominantly works off a subscription model where the subscriptions all cost the same or similar. Then it’s likely that your average order values would be similar or the same across all your customer segments. Even if your most highly engaged customers make repeat purchases/subscriptions, the value of their order would be the same as an unengaged customer who started their subscription 60-days ago. 

Other factors that play a role in how average order value is influenced by user engagement would be determining how long your brand’s conversion window is. I’ve seen this occur where users may need to think through their purchases further - typically with more high cost or long lead time products like furniture. When this happens, you’ll have some customers who engaged shortly with your brand and decide to make a purchase right away. But because of the conversion window, you may have a larger influx of customers who make a purchase close to the 60 day mark. Thus making the average order value similar between these two segment groups. 

Overall, there are a number of variable that can play a role in why the average order value can be the same or similar across multiple customer segments. You’ll oftentimes find the answer to this by analyzing your own brand and investigating into the purchase history of your customers.

I hope this helps!

David

 


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