Best way to pull data out of Webflow & into Airtable?

[Frazer_McLeod]

Hi Parabola community,

I have spent the last few months putting an extensive amount of data (~2500 unique items) with multi-reference fields into Webflow and wish to:

1. Pull all of it out and put it into Airtable while maintaining Multi-reference fields relationships
2. … then maintain the data similar to the way Connor Finlayson
   does with his Unicorn Factory using Zapier and stepped through well by Ben Tossell
   in this tutorial

But I need to be able to do step 1 first while maintaining the Multi-reference fields relationships.

So far I have:

1. Exported all data as CSVs from each Webflow database
2. Imported those CSVs to an Airtable base and kept all data consistent including Collection IDs and Item IDs
3. Set up Look-up Reference Fields to facilitate the Multi-reference field functionality between tables (e.g. Product categories for Products)

I think the next steps are

1. Upload CSV data for each unique item from the Webflow CMS collections to each corresponding Airtable Table and include only the name for reference and the CMS item ID
2. Use Parabola to facilitate the Multi-reference fields matching across to Airtable – (but this is the part that I’m not sure how to set up for this particular use case)

Thanks in advance for anyone who can shed some light on the approach & if I’m on the right track, I’d be stoked.

Cheers,
Frazer

[sachi]

Hi @Frazer_McLeod - Sounds like you’re on the right track! And, what you’re looking to use Parabola for definitely sounds doable.

To confirm, you’ve already created all the tables in your Airtable Base that essentially replicate all the collection tables you’ve exported from Webflow, right? Plese make sure that all of your Webflow items have successfully been uploaded to Airtable.

I think what’s best is to then use the Airtable Import steps to get all of your tables into a Parabola flow. Within Parabola, you can filter each table down to two columns, Webflow ID and Airtable ID, and then use the Table Merge step to create one giant mapping table.

This giant mapping table you just created is what you’ll use to then join Webflow IDs that you need to map to to Airtable IDs!

[Frazer_McLeod]

Thanks for the quick response Sachi.

So far have:

• Like-for-like Airtable tables & columns matching CMS collections & fields
• Airtable IDs for each row using RECORD_ID()
• All raw data from each Webflow collection
• Pulled in every table to a Parabola flow, excluding all values except Airtable ID, Webflow ID and Webflow Multi-reference fields (but the problem is these are read in from Webflow’s Data as the slug, not the ID)

i.e.

At this stage the Multi-reference fields get pulled into an Airtable record as:

• Suburb CMS Item “Canada Bay” is read in as ‘canada-bay’ without a Webflow ID next to it

Is there a reliable and accurate method to matching “canada-bay” (and the other suburbs in the comma-separated-values) back to the suburb name and ID in a mapping table via Parabola?

What I was thinking is:

• 99% sure it’s always going to match the slug field from Webflow’s data export.
• Perhaps it’s about creating a column where the slug & Webflow + Airtable IDs are mapped back to that? Not sure if this is conventional or if there’s a more reliable way to do it.

Here are some screenshots below for your reference.

Thanks in advance!

[brian]

Ah I see. You want to pull in the table of your Webflow CMS data that the multi-reference field is pointing to, and that will have both the slug and the ID in the table.

You need to format your current table, where there is a list of slugs in each cell, to have 1 slug per row. So use a column split, set to split into new rows to do that.

Then you can join the webflow table data, which should just be two columns - slug and webflow id, to this data.

Then you can filter off the slugs, so you have essentially replaced the slug column with the webflow id column, and then use a Merge Values to merge the webflow id column back into a comma separated list in a cell, grouped by every other column.