How to Connect Async Interview to Google Sheets (4 Methods Compared)

The Problem With Getting Sheet Data In and Out of Async Interview

You have a Google Sheet full of candidate data — role names, submission windows, scoring rubrics, hiring pipeline stages. And over in Async Interview, you have a growing queue of video responses, job configurations, and candidate records that your team is reviewing asynchronously.

Async Interview is good at collecting structured video responses at scale without scheduling overhead. But moving that data into a spreadsheet — or keeping your sheet in sync with what's happening in the platform — takes more effort than it should. The usual flow is opening the dashboard, exporting what you can, reformatting the download to match your internal columns, and repeating that every time the pipeline changes.

Below are the four common ways hiring teams handle this. Only the last one scales.

Method 1: Manual Copy-Paste

The default. Log into Async Interview, find the job, open the responses view, and manually transcribe candidate names, emails, submission dates, and video URLs into your Google Sheet one row at a time.

For a five-person pipeline, that's annoying. For forty candidates across three open roles — a customer success hire, a product manager, and a support specialist — you're looking at an hour of work that produces a spreadsheet you'll have to redo the following week when twelve more responses come in.

The part that really grinds is the video links. They don't export cleanly. You end up copying them one by one, testing each one to make sure it actually resolves, and manually labeling which URL goes with which candidate. By the time you're done, you've touched every record twice.

Method 2: Zapier or Make

Both platforms have Async Interview connector options. You can wire up a trigger when a new response is submitted, pull the response fields, and write them into a designated sheet row.

Before you keep reading — do you know what a webhook trigger is? Field mapping? API authentication tokens? A "new record" trigger versus a "polling trigger"? If those terms feel foreign, this section isn't your path. Jump to Method 3 or 4 — you'll get there faster.

If you're still here: the automation is buildable. You authenticate, pick the trigger event, map every field by hand — candidate name to column B, email to column C, submitted_at to column D, video URL to column E — then test it, debug the edge cases where the response object comes back differently formatted for older jobs, and publish it.

The flow works. The problem is what it costs to get there.

Each new response triggers one row. That's fine if your pipeline is a steady trickle. But if forty responses landed in the last two weeks — before you set the automation up — they're not going back through the trigger. You're still doing that backfill by hand.

You probably just need all the candidate records in a clean sheet so you can score and rank them. You probably have no idea how to find Async Interview's webhook endpoint, and you shouldn't have to. So you push this to whoever on your team builds Zaps, and then you wait. If they're not already on three other requests, you might hear back by Thursday.

And the moment you need to filter responses by job title, exclude incomplete submissions, or join video links against a separate scoring rubric tab — you've outgrown what a single trigger can do.

Method 3: The Previous Generation — Connector Add-Ons

Until recently, the best option for repeatable spreadsheet ↔ Async Interview workflows was a category of add-ons that let you manually configure column mappings and saved templates. You picked your range, you tagged your fields, you saved a config, you ran it.

That was a real step up from copy-paste. Output was consistent, configs were reusable, the team didn't have to redo formatting every run.

But you were still responsible for the template design, the field mapping, the schedule, the conditional logic about which responses to include, the renaming of columns to match your internal rubric. The tool got the data through, but the thinking was still on you. And the moment your job configuration changed in Async Interview — a new question added, a field renamed — your config broke until someone went back in and fixed it.

This is the previous generation. It worked, but it asked a lot of the operator.

The Easy Way: Using SheetXAI in Google Sheets

There is a different way entirely. SheetXAI is an AI agent that lives inside your Google Sheet. It reads the sheet, understands what you are looking at, and through its built-in Async Interview integration it can push to or pull from Async Interview for you. No template configuration, no automation glue, no summarizing your data by hand. You just ask.

Example 1: Export all responses for a role into your scoring sheet

Fetch all interview responses from Async Interview for the job in cell B1 and write candidate name, email, submission date, and video URL into columns A through D starting at row 2.

Each response lands in its own row, with the video link in column D formatted as a clickable URL. Incomplete or pending responses are flagged in column E so you know which records to follow up on.

Example 2: Pull a full response roster across all active jobs

Fetch all Async Interview responses submitted in the last 30 days and write candidate name, email, job title, submitted_at, and response URL into the CandidateLog tab, sorted by submission date descending.

The pattern: instead of exporting each job separately and consolidating them manually, you ask for the full view in one prompt. SheetXAI handles the aggregation and the sort inline.

Try It

Get the 7-day free trial of SheetXAI and open any Google Sheet where you're tracking hiring pipeline data, then ask it to pull your latest Async Interview responses directly into the sheet. The Async Interview integration is included in every SheetXAI plan.