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

The Problem with Getting Kommo Data Into and Out of Google Sheets

Kommo is a CRM built around conversational sales pipelines. It tracks leads, companies, contacts, pipeline stages, tasks, and the history of every stage change. If your team runs deal reviews, does migration work, or needs to analyze win/loss patterns, the data you need is in Kommo. But getting it into a Google Sheet — or pushing data the other way — is more work than it should be.

Kommo has an API. The API is capable. But the path between a Google Sheet and Kommo for most sales, ops, and RevOps users is either a CSV export, a manual copy-paste session, or a Zapier flow that fires row by row. None of those handle the cases that actually matter in practice: bulk imports of 300 leads, quarterly pipeline reviews where you update 40 deals from a single sheet edit, or analysis that joins Kommo events with loss reasons to produce a clean pivot.

Below are the four ways people typically bridge Google Sheets and Kommo. Only the last one handles the complex cases.

Method 1: Export to CSV, Edit in Sheets, Re-Import

The default approach, and the one that breaks first under any volume. You export from Kommo, open the file in Google Sheets, make changes, then import the modified CSV back. Kommo's import handles basic fields, but it does not handle relational updates like linking a contact to a company, updating pipeline stage from a name rather than an ID, or writing task records.

When this works:

• One-time data load of simple lead records
• Fewer than 100 rows with clean, fully-populated fields
• No relational linking between companies, contacts, and leads

When it breaks:

• Any update requires the import to match an internal Kommo record ID
• Stage names in your sheet do not match Kommo's canonical stage IDs
• You need to write back results to the sheet after the import runs
• You want to create tasks, not just leads or contacts

CSV round-trips also destroy context. You lose the audit trail. Kommo's event log knows when a stage changed, who changed it, and why. A CSV import bypasses all of that.

Method 2: Use Zapier or Make to Sync on Row Changes

The next level up is an event-driven automation. You wire Zapier or Make to watch for new rows in a Google Sheet, and when a row appears, the zap calls the Kommo API to create a lead or update a record.

This works for event-driven moments:

• New lead form submission → create Kommo lead
• New contact added to a sheet → push to Kommo contacts
• Row status updated → trigger a Kommo task

This fails for batch or analytical work:

• You cannot export 120 Kommo deals to a sheet in one trigger
• You cannot reassign 40 deals from a spreadsheet edit session
• You cannot join Kommo event logs with loss reasons and produce a pivot
• You cannot validate 400 import rows against a Kommo pipeline stage lookup

Row-by-row automations do not aggregate, they do not query, and they do not do the analysis step. When the work requires understanding all the data together — not just moving one row at a time — event-driven tools run out of room fast.

Method 3: The Previous Generation — CRM Connector Add-Ons

Until recently, the best option for bidirectional spreadsheet-to-CRM sync was a category of connector add-ons that gave you a configured sync panel. You picked the Kommo object type, you mapped the column fields, you set a schedule, and the add-on handled the refresh.

That was a real step up from CSV exports. The sync was repeatable, the field mapping lived in one place, and the team did not have to manually download files every week.

But you were still responsible for setting up every mapping, for deciding which direction the sync ran, for handling errors when a Kommo stage ID changed, and for writing any logic about which rows to include or exclude. The add-on moved the data. The thinking was still on you. And anything beyond basic field sync — joining event logs, producing a loss analysis pivot, validating import rows against a live Kommo lookup — was outside what the add-on could do.

This is the category we think of as the previous generation. It worked for scheduled syncs. It did not work for the analytical or relational work that actually drives CRM decisions.

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 the structure of what you are working with, and through its built-in Kommo integration it can query Kommo, push records, update stages, create tasks, and write results back to the sheet. No field mapping panels, no CSV round-trips, no automation flows to maintain — you just describe what you need.

Example 1: Your Data Is Already in the Sheet

You have a Conference Leads sheet with 350 rows, columns for name, email, company, and deal size. You need all of them in Kommo before Monday outreach starts.

Create a Kommo lead for every row in this sheet — use column A as the lead name, column B as the contact email, column C as the company name, and column D as the expected deal value in USD. Write the returned Kommo lead ID back to column E for each row.

SheetXAI reads the sheet, calls the Kommo API once per row, and writes each lead ID back as it goes. When it finishes, column E is fully populated. You have a permanent reference from the sheet to every Kommo record that was created.

Example 2: Your Data Lives in Kommo

If the data you need is in Kommo and you want to work on it in a sheet, you go the other direction:

List all leads in the Kommo Negotiation stage and write them to a new Pipeline Review sheet with columns: lead_id, lead_name, value, responsible_user, created_date. Then for any row where column F is 'Reassign', update the Kommo lead to set the responsible user to the user ID in column G.

SheetXAI pulls the Kommo data, writes the sheet, waits for you to fill in your action column, then you run a follow-up prompt to process the updates. One sheet, one agent, both directions, without exporting a file or configuring a sync.

Which Method Should You Use

For a one-time import of fewer than 50 simple lead records where all the field values are already clean, the CSV export path is fine. For an event-driven workflow where a single new row should always create a single Kommo record, Zapier or Make are a reasonable fit.

For any work that involves querying Kommo and writing results to a sheet, bulk-updating records from a sheet edit session, joining Kommo event data for analysis, or validating import data against live Kommo lookups, SheetXAI is the only option that handles it in a single prompt without configuration overhead.

If your team touches Kommo data in Google Sheets more than once a week — for pipeline reviews, migration prep, task creation, or win/loss analysis — the setup pays back by the second session.

Try It

Get the 7-day free trial of SheetXAI and connect it to your Kommo workspace, then ask it to pull your current pipeline into a sheet or push a batch of new leads from a sheet you already have. The Kommo integration is included in every plan.

For specific workflows, see how to bulk-import leads from a sheet into Kommo, how to run a pipeline review and bulk-update stages, or browse the full integrations directory.