How to Connect Serply to Excel (4 Methods Compared)

The Problem With Getting Workbook Data In and Out of Serply

You have an Excel workbook full of data — research keywords, neighborhood location queries, product category terms, competitor brand names. You need those terms run through Google Search, Google Scholar, or Google Maps, and you need the results written back into the workbook without doing it manually for each row.

Serply is good at returning structured, real-time search data from Google's ecosystem via a simple API. But the gap between "I have an API key" and "this runs across all 200 rows in my workbook" is where most workflows fall apart. The default approach is to export a column to CSV, write a script that calls the API row by row, parse the JSON, and paste the columns back in.

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

Method 1: Manual Copy-Paste

The default with Excel is usually a CSV export. You pull the column of terms, run them through a script or Postman collection, get a CSV of results back, and then paste-merge it into the workbook — making sure the row order still matches.

For a single quick lookup, this is workable. For anything recurring — a weekly competitive keyword audit, a monthly location enrichment run — the export-paste-realign cycle compounds fast.

The data is easy to get. The part that wears people down is reassembling it into the right workbook structure every single time, especially when someone has added rows since the last export.

Method 2: Power Automate

Power Automate has HTTP action steps that can call Serply's API, and you can trigger those flows from an Excel row change or a schedule. The architecture is real.

Before continuing — a quick check. Do you know what an HTTP action is? How to configure Bearer auth in a flow? What a JSON schema looks like and how to parse one inside Power Automate? If those phrases are unfamiliar, you're better off skipping to Method 3 or 4.

If you're still here: the setup involves configuring the trigger (row added, scheduled, or manual), building the HTTP step with Serply's auth and query parameters, parsing the response with a Parse JSON step, and mapping the output fields back to your Excel columns.

The flow works. Getting it to work is where the time goes.

One row per trigger fire is the structural ceiling. A flow that runs per row is not the same as a single pass over your whole dataset. If you have 150 keywords, that's 150 trigger fires. If row 43 returns a schema Serply changed last week, that row silently fails and you won't know until you spot a blank cell.

You probably just need the top search results for each term and you have no idea how to wire an HTTP action with dynamic query parameters in Power Automate. So the task goes to whoever manages your business automations, and now you're in a queue behind their other projects.

Complexity grows fast once you add conditional logic, error retry, and multi-field response parsing. What starts as a simple flow becomes something that takes two hours to debug when it breaks.

Method 3: The Previous Generation — Connector Add-Ons

Until recently, the best option for repeatable workbook ↔ API workflows was a category of add-ins that let you configure a query template, point it at a column of inputs, and schedule the run. You set the endpoint, mapped the response fields to columns, saved the config.

That was a real step up from the export-paste cycle. Configs were reusable. Output was predictable. You didn't have to rebuild the mapping every week.

But you were still responsible for the template design, the field mapping, the schedule, and the conditional rules about which rows to include. The add-in got the data through, but the thinking was still entirely on you. And when Serply's response shape changed or you renamed a worksheet, the config broke until someone went in and repaired it.

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

The Easy Way: Using SheetXAI in Excel

There is a different way entirely. SheetXAI is an AI agent that lives inside your Excel workbook. It reads the workbook, understands what you're looking at, and through its built-in Serply integration it can run searches and write results back for you. No API docs, no Power Automate flows, no field mapping. You just ask.

Example 1: Bulk Scholar search across a keyword list

For each research topic in column A, search Google Scholar via Serply and write the top 3 paper titles, authors, and citation counts into columns B through G

SheetXAI reads column A, runs each term through Serply's Scholar endpoint, and fills in title, author list, and citation count across the next six columns — one row per topic, three results per row.

Example 2: Maps enrichment for a location dataset

Look up each query in column A using Serply Maps search and write the top business name, rating, address, and phone number into columns B, C, D, and E

The pattern: instead of exporting your queries, running them through a script, and realigning the output CSV, you describe what you need and SheetXAI runs the API calls and writes the results back in one pass.

Try It

Get the 7-day free trial of SheetXAI and open any workbook with a list of search terms or location queries, then ask it to run a Serply lookup across the column. The Serply integration is included in every SheetXAI plan.