Shopify Pack: Add filter options for data sync

Request: add more granular filters to the Shopify pack import, e.g. lineitem SKU, customer/order tags

The current Shopify pack has (reasonable) limits on how many rows of data can be pulled from Shopify into Coda.

However, as there is no ability to filter incoming data by customer tags, line item product SKU or any other meaningful dimension, the integration is unusable for us. Even though we are only interested in manipulating a small number of our Shopify customers and orders, we have to bring in all customers/orders and quickly hit the aforementioned import limits.

It’s a real pity, because this integration could be a game changer for how we use Shopify. And it would allow us to centralize much more of our activity into Coda. Adding more import filter options would unlock this whole pack for us.

In our specific case, we have a small subset of Shopify customers that are B2B clients. They are tagged in Shopify and buy only B2B-specific SKUs, so we have a couple different ways we are able to filter those orders when pulling Shopify reports.
However, because we have to pull all our orders together, the 10,000 row limit means we can only get a few weeks of data—and most of that data is for non-B2B orders which we’re not interested in for these purposes.

Thanks!

P.S.: I played with a Zapier workaround and we can technically do it—but the way the Shopify pack works in creating nested tables behind-the-scenes is really nice (in particular to make 1 row per order with multiple line items, rather than one row per line item)

Hi, @Harry_Doull .
@Martin_Portevin has developed a Shopify pack.
I really don’t know if it has the features you need.
Maybe he can help you.

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Just adding a further note: we’re hitting calculation / memory limits because we have 10,000+ rows of Shopify data, most of which we don’t need.

Unfortunately, the nature of the connection means I cannot delete individual rows once the data is imported. If that were possible, that would also be workable.

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