Owned data mavericks! πΒ Got a brain buster for ya.
Data Point
I am trying to determine the average time spent between orders that contain a certain product type. (Not average amount of days between all orders, as outlined below.)
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Context
For context, I would like to use this data point as a trigger for a flowΒ with the CTA of generating repeat purchases ofΒ a specific product type.
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Example
For example, letβs say a clientβs main product is desks.
β Client also sells desk accessories s/a lamps, drawer organizers, etc.
β Most customerβs initial purchase contains a desk, but customers place orders of desk accessories that do not contain a desk in between purchasing another desk. (Say that 5 times fast!)
Example Customer:
| Days BetweenΒ Orders | Order No. | Order Contains |
|---|---|---|
| 0 | 1 | Desk |
| 32 | 2 | Accessories |
| 67 | 3 | Accessories |
| 120 | 4 | Accessories |
| 365 | 5 | Desk |
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β On an individual profile level, itβs easy to determine the days between orders that contain a desk, this example would be 365 days.
β However, if I were to factor in all of the orders, the orders that do not contain a desk dramatically lowers the average amount of days between orders, which would lead to a premature flow trigger.
β I could go through all profiles that placed multiple orders with desks, but it is extremely time consuming and dynamic.
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The Challenge
βΒ I am trying to determine the average amount of days between orders that contain a desk, but Iβm having trouble figuring out a way to filter out the accessory orders that doΒ notΒ contain a desk at scale.
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Got any tips, tricks, or suggestions to figure this out? Maybe thereβs a Klaviyo feature that can automatically pull this up that I am unaware of? Cheers!