How to Connect Klazify to Google Sheets (4 Methods Compared)

The Problem With Getting Sheet Data In and Out of Klazify

You have a Google Sheet full of domain names — publisher lists, prospect accounts, inbound leads, partner directories. You need each row enriched with IAB categories, firmographic data, social links, or tech stack, and you need it without copy-pasting every domain into an API console and transcribing the response by hand.

Klazify is good at answering one question per API call: what is this domain, who runs it, what technology does it use, and what does it look like? But the default path from a spreadsheet full of domains to a spreadsheet full of answers involves a lot of steps that have nothing to do with the actual analysis you're trying to run. You export the list, write or borrow a script, authenticate, handle rate limits, wrangle the JSON, and eventually paste columns back into a sheet that has probably changed while you were doing all of this.

Below are the four ways teams work around that. One of them skips the detour entirely.

Method 1: Manual Copy-Paste

The starting point for most people. Open Klazify's API console or a browser extension, paste in a domain, get the response, copy the fields you care about, switch back to your sheet, find the right row, paste them in. Repeat.

For a handful of one-off lookups, this is fine.

The problem arrives around row twelve. By row forty you have a sheet with inconsistent column formatting because you pasted JSON from three different endpoints into the same column. By row eighty you've stopped caring whether the confidence score is 0.94 or 0.94000 and you just want the thing to be over.

Domain enrichment is not a one-time task. Publisher lists get refreshed. Prospect pipelines grow. Inbound leads arrive in batches. Doing this by hand is a commitment to doing it again, and again, in the same punishing way.

Method 2: Zapier or Make

Both platforms have Klazify connector options or webhook steps. You can wire up a trigger — a new row in a sheet, a schedule, a form submission — call the Klazify categorize or company-data endpoint, and write the result back into a column.

Before diving into what that involves: do you know what a webhook trigger is? A field mapping panel? An HTTP action with JSON body parsing? An error handler for rate-limit responses? If those phrases feel abstract, this path is not going to get you to an answer today — skipping to Method 3 or 4 will.

If you are still here, the workflow is real and it works. You authenticate the Klazify HTTP step, map your domain column to the API request body, parse the response fields you need, and write them back to their respective columns. That covers one row at a time.

But one-row-at-a-time is the structural ceiling.

Sending 600 domains through a Zap means 600 trigger fires, 600 API calls, and a task log that becomes genuinely difficult to audit when row 214 returns an unexpected field name because the domain pointed to a parked page.

You probably just need the IAB category column filled in. You probably have no idea how to configure a Zap with a custom HTTP action and JSON field parsing — and there's no reason you should. So you hand it to whoever on your team builds these things and wait. And if that person is juggling three other projects, you wait longer.

Once you need to filter domains by category before writing them back, or join the enrichment results against a second tab, you've left what this automation can do natively.

Method 3: The Previous Generation — Connector Add-Ons

Until recently, the most practical repeatable path was a category of spreadsheet add-ons that let you configure API calls column by column. You picked your input range, you mapped the response fields to output columns, you saved the config, you ran it.

That was a genuine improvement over copy-paste. The mapping was consistent, the runs were repeatable, the output columns lined up the same way every time.

But you were still responsible for figuring out which Klazify endpoint to call, how to handle paginated or multi-value responses like tech stack arrays, what to do when confidence scores came back below your threshold, and which rows to skip because the domain had already been enriched last week. The add-on moved the data. The thinking was still yours. And when your sheet structure changed — a column rename, a new tab, a filter — the config broke until someone went back in and updated it.

This is the previous generation. It solved the transport problem but not the judgment problem.

The Easy Way: Using SheetXAI in Google Sheets

There is a different approach. SheetXAI is an AI agent that lives inside your Google Sheet. It reads your data, understands the structure of your tabs and columns, and through its built-in Klazify integration it can classify, enrich, or expand your domain list on request. No endpoint configuration, no field mapping, no JSON parsing. You just ask.

Example 1: Bulk-classify a publisher domain list by IAB category

For every domain in column A of the "Publishers" sheet, call Klazify and write the top IAB category label and confidence score into columns B and C

Each row gets its category label and a numeric confidence score. Domains that return multiple categories get the highest-confidence one written first, with sub-categories available if you ask for them.

Example 2: Enrich inbound leads with firmographic data before routing to sales

For all rows in the "Inbound Leads" tab, fetch company data from Klazify and add employee range, revenue band, and HQ country into columns D, E, and F — skip any row where column D is already filled

The pattern: enrichment with a guard clause in the same prompt, so you're not hitting the API twice for rows that already have answers.

Try It

Get the 7-day free trial of SheetXAI and open any Google Sheet with a column of domain names, then ask it to classify, enrich, or expand the list using Klazify. The Klazify integration is included in every SheetXAI plan.