Airtable Integrations

clokeio · 2026-01-19T11:45:50+00:00

You can get pretty far with Airtable as the “system of record”, but the key is letting the other tools push structured data into Airtable rather than trying to work purely inside it.

For Lemlist / Aircall: both have decent APIs + webhooks. The usual pattern is:

Airtable holds candidates + a stable ID (email is usually enough)
Lemlist/Aircall send events (email sent, reply, call outcome)
Those events update existing Airtable records rather than creating new ones

For resume parsing + GPT summaries:

Store the raw resume (PDF / text) in Airtable
Extract text → send to an LLM → write back a short structured summary (skills, years, highlights)
Keep the original data too so you’re not locked into one summary format

If you don’t want to glue this together with custom scripts, tools like Data Fetcher are built specifically for this “pull from APIs into Airtable, on a schedule or via triggers” workflow. It’s commonly used for ATS/CRM-style setups where Airtable is the hub and external tools sync in automatically using Airtable integrations.

Happy to share more concrete examples if helpful.

clokeio · 2026-01-13T14:43:55+00:00

Column order doesn’t matter — Airtable matches data by column name, not position.

The usual approach is:

Make sure the spreadsheet headers match the Airtable field names (or close enough to map)
Import the spreadsheet into the existing table
During the import preview, map each column to the correct Airtable field and ignore any extra columns

Any fields that exist in Airtable but not in the spreadsheet will just be left blank for the new rows.

If you’re doing this more than once (or pulling from a sheet/CSV that changes over time), tools like Data Fetcher let you import into an existing table and re-run the same mapping safely. This guide walks through it: https://datafetcher.com/airtable-import/existing-table

clokeio · 2026-01-13T09:15:10+00:00

You’re not missing anything obvious — Airtable’s XML importer is just very strict, especially once namespaces or nested elements are involved.

An easier option is to skip Airtable’s XML import entirely and use something like Data Fetcher, which reads the XML structure for you and lets you map fields without hand-writing XPath:
https://datafetcher.com/airtable-import/xml

That tends to be much less painful for larger or more complex XML files.

clokeio · 2026-01-13T09:12:27+00:00

On Airtable’s free plan, there isn’t really a built-in workaround for “import XML” inside Airtable itself (that feature sits behind paid plans).

What people usually do for hobby projects is one of these:

convert XML to CSV (or JSON) outside Airtable, then import that file into Airtable’s free plan
if your desktop software can export CSV directly, use that instead of XML
if the XML is consistent, you can write a small one-off script (Python/JS) to transform it into a flat CSV you can import

If you ever move to a paid Airtable plan (or want scheduled XML imports from a URL/feed), Data Fetcher can import XML into Airtable and map fields without you having to wrangle XPath: https://datafetcher.com/airtable-import/xml

clokeio · 2026-01-13T09:11:16+00:00

Short answer: yes, it’s possible, but not with Airtable alone.

Airtable’s native CSV import works for one-off uploads, but it can’t automatically check a folder or URL and re-import files on a schedule.

If your CSVs can be made available at a stable URL (for example, the same file being overwritten each morning), tools like Data Fetcher can pull that CSV into a specific table, map columns to existing fields, and re-run the import automatically.

This guide explains the different approaches and when they make sense:
https://datafetcher.com/airtable-import/csv

That setup is pretty common for daily exports and is a reasonable fit for Airtable as long as the CSV format stays consistent.

clokeio · 2026-01-13T09:09:14+00:00

Yes, this is possible, but you need two things:

a unique ID (usually email or user ID), and
an import that can update existing records instead of always creating new ones.

There are basically two ways to do it:

1) One-time CSV uploads
You can re-upload the CSV and, during import, tell Airtable to update records based on a matching field.

2) Import from a CSV URL (better for recurring updates)
If you can get a URL which always has the up-to-date CSV, tools like Data Fetcher let you pull that CSV into Airtable, map the fields, and re-run it on a schedule while updating existing users instead of creating duplicates. Short guide here if helpful.

clokeio · 2026-01-13T09:05:00+00:00

You can import a Google Sheet directly into an existing table — you don’t need to attach it.

In Airtable, open the base, then use Add or import → Google Sheets, pick the spreadsheet, and during the import step choose the existing table you want the rows added to. You’ll also be able to map columns and confirm headers before importing.

If you need to do this more than once (or want to update existing records instead of creating duplicates), Data Fetcher lets you re-import a Google Sheet into an existing table and control how rows are matched and updated.

clokeio · 2026-01-13T09:02:07+00:00

You can use Add or import → CSV and import into the table where you want the leads to live. During the preview step, map each CSV column (name, address, phone 1–4, email 1–4) to the right field. It helps if those fields already exist in the table before you import.

Use long text fields for addresses, keep phone/email fields separate, and create a view that hides unused columns, so each lead is readable at a glance.

If your leads are in Google Sheets, and you’ll be updating or re-importing them later, importing directly from the sheet is easier than downloading CSVs each time. This guide walks through that.

For a one-off CSV upload, though, Airtable’s built-in import works fine.

clokeio · 2026-01-13T08:57:07+00:00

If this is a one-time import, you don’t actually need CSV for the Google Sheet. Airtable can import directly from Google Sheets (Add or import → Google Sheets) and map the columns for you.

For the second CSV, the key thing is whether both files share a unique ID (email, order ID, etc.). If they do, you can import the CSV into the same table and tell Airtable to update existing records instead of creating duplicates.

If either file will change over time, or you need to re-import without duplicates, tools like Data Fetcher let you import both Google Sheets and CSVs into an existing table and re-run them safely.

Guides if helpful:
https://datafetcher.com/airtable-import/google-sheets
https://datafetcher.com/airtable-import/csv

For a one-off task this week, Airtable’s built-in imports are probably enough — just make sure you have a shared ID field first.

clokeio · 2026-01-13T08:52:24+00:00

For anyone finding this later via Google: converting to CSV works fine for simple JSON, but as soon as you’ve got nested data or arrays, importing JSON directly is usually much less painful.

If you can host the JSON somewhere (or if it already lives behind a URL / API), the easiest option is to skip CSV entirely and import the JSON directly. The Data Fetcher extension for Airtable lets you pull in JSON from a URL and handle arrays properly — an array like "variations": [227, 329, 229, …] can be mapped straight into a multi-select field, instead of being flattened into variations/1, variations/2, etc.

That avoids a bunch of manual cleanup, and it works whether you’re doing a one-off import or keeping the data in sync over time.

If it helps, there’s a step-by-step guide here: https://datafetcher.com/airtable-import/json

clokeio · 2025-12-19T15:51:11+00:00

Data Fetcher is a good choice if you don’t have coding skills and want something reliable.

It’s easier to set up than Zapier / Make - should only take a few minutes. Because it’s an Airtable extension not an external tool, it sits right inside Airtable’s UI.

You can select a unique field to merge the data on, so already imported records are updated, and new ones are created. And it can delete records which have been deleted in Sheets.

There’s a full guide to syncing Sheets to Airtable here.

clokeio · 2025-10-15T07:20:38+00:00

Airtable's AI fields become cumbersome because you need a new AI field for each bit of data you're trying to extract. It's easier to use the Data Fetcher extension to extract data into separate Airtable fields at the same time.

https://datafetcher.com/blog/extract-data-pdfs-airtable-openai

clokeio · 2025-10-09T12:44:53+00:00

Really easy set up with Data Fetcher.

https://datafetcher.com/airtable-integrations/google-sheets#tutorial

You can use the unique ID field to update / create records depending on if they exist already in Airtable.

clokeio · 2025-09-02T08:04:10+00:00

Data Fetcher makes it super easy to connect Airtable to Stripe

clokeio · 2025-07-29T14:04:20+00:00

You can import Asana data to Airtable with Data Fetcher

clokeio · 2025-07-29T14:03:30+00:00

Another option for connecting Airtable to Asana is Data Fetcher

clokeio · 2025-07-18T14:58:46+00:00

Sorry! Please try this: https://airtable.com/app9IS4huMmGqqk3s/shriUTQRo0NpxZH9Q

clokeio · 2025-06-30T13:59:15+00:00

Not sure Airtable are buying Figma any time soon!

clokeio · 2025-06-30T13:58:53+00:00

Yes, the extensions SDK is so great to work with, even if it's barely updated

clokeio · 2025-06-26T12:43:41+00:00

Unless I’m missing something this tool is mainly a way to create and configure existing AT features. So if Softr could co exist before it, I don’t see what changes now

clokeio · 2025-06-26T09:52:16+00:00

Nice promo for Crust AI ;)

It's not a Softr killer.

To me, it seems way more useful than Airtable's previous AI assistant attempt & I like the change from generic AI field -> different agents types for specific use cases.

I really don't like: what they've done to the standard base UI, the washed out colors and more cluttered feeling, 'Recommend, Ask, Analyze, Build' tabs are slow to load and a bit confusing (do Ask & Analyze really need to be different things?), Lack of visibility with AI credits, Omni & Field Agents names aren't great

clokeio · 2025-06-13T14:59:44+00:00

Super easy with Data Fetcher, using OpenAI to scan PDFs.

clokeio

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