The Problem With Getting Sheet Data In and Out of Perigon
You have a sheet full of data — brand mentions, competitor keywords, journalist names, company lists. You need it matched against Perigon's news index, or you need Perigon's article data pulled back into structured rows for reporting.
Perigon is good at surfacing structured news intelligence: article metadata, story clusters, journalist profiles, source directories, and semantic search across both news and Wikipedia. But getting that data into a Google Sheet and keeping it current is a different problem entirely. The usual approach is to export a CSV through the Perigon dashboard, reformat columns, paste into the sheet, then repeat every time stakeholders ask for a refresh.
Below are the four common ways teams handle this. Only the last one scales.
Method 1: Manual Copy-Paste
Open Perigon, run your search, export the results as CSV or copy the table. Open your sheet. Paste the data. Realign the columns. Strip out the fields you don't need. Add the columns you do.
That sequence takes between 15 and 45 minutes depending on how many keywords you're tracking.
If you're producing a weekly competitive coverage report, you're doing that sequence 52 times a year. The data is always slightly stale because you ran the pull on Monday morning and it's now Thursday. And the moment you add a new competitor to monitor, you have to rethink the whole column structure.
It's not that the pull is hard. It's that repeating any structured task by hand 52 times grinds away at the part of your brain that's supposed to be doing the analysis.
Method 2: Zapier or Make
Both platforms have Perigon connector options. You can wire up a trigger on a schedule, call the Perigon search or story clusters endpoint, and write each article back to your sheet as a row.
Before you go further — do you know what an API connector is? Have you configured field mapping before? Do you know the difference between a trigger and an action in Zapier? If those concepts feel unfamiliar, this path isn't the right one for you. Skip ahead to Method 4.
If you're still here: the wiring works. You authenticate, pick your trigger schedule, map the Perigon response fields to sheet columns, and test the Zap. It runs.
The structural problem is that trigger-per-row automation is not the same as a bulk pull.
Perigon can return 50 or 500 articles for a given query. Each article goes through the Zap as a separate task fire. That's 500 tasks on your Zapier plan. Field mapping breaks if Perigon adds or renames a response property. And the moment you want to filter by source tier, deduplicate against last week's rows, or cross-reference against your existing journalist sheet, you're chaining multiple Zaps together — and watching the cost and complexity multiply.
You probably just need this week's brand coverage in a clean sheet. You probably have no idea how to configure a multi-step Zap with conditional logic and dedup filters — and you shouldn't have to. So you send a Slack message to the person on your team who builds these, and now the request is sitting in their queue behind everything else they're working on.
Method 3: The Previous Generation — Connector Add-Ons
Until recently, the best repeatable option for pulling news API data into Google Sheets was a category of add-ons that let you configure saved query templates — pick your endpoint, set your parameters, map your columns, and save the config for future runs.
That was a genuine improvement over copy-paste. Configs were reusable. Output was consistent. You could hand off the template to someone else on the team.
But you were still responsible for every parameter decision — which Perigon endpoint, which fields to map, which date range to set, which sources to exclude. The add-on passed the data through, but all the judgment calls stayed with you. When Perigon updated a field name or you needed to add a new keyword to track, the config broke until someone fixed it.
This is the previous generation. It worked, but it asked too much of the operator.
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 sheet, understands what you're looking at, and through its built-in Perigon integration it can search for news articles, pull story clusters, look up journalist profiles, and write results back into your sheet — for you. No saved templates. No endpoint configuration. No reformatting.
Example 1: Pull a week of brand coverage into the Coverage sheet
Fetch all Perigon news articles from the last 7 days mentioning "Acme Corp" OR "BetaCo" OR "GammaTech" and write each one to the Coverage sheet with columns for headline, source, published date, and URL.
Each matching article lands as a new row. Headline in column A, source name in column B, published date in column C, article URL in column D.
Example 2: Enrich journalist names from a press list
For each journalist name in column A and outlet in column B of the Press List sheet, look them up in Perigon and write their Twitter handle, bio, and location into columns C, D, and E.
The pattern: instead of running a separate export for each journalist and then reformatting the results, you ask for lookup and writeback in a single prompt. SheetXAI handles the per-row API calls inline.
Try It
Get the 7-day free trial of SheetXAI and open any Google Sheet with brand keywords, journalist names, or competitor terms in a column, then ask it to pull the corresponding Perigon data. The Perigon integration is included in every SheetXAI plan.
More Perigon + Google Sheets guides
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Build a Media Source Audit Sheet From Perigon Data in Google Sheets
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