How to Join Data in Google Sheets: A Practical Guide

1. Manual ways to join data in Google Sheets

Think of manual methods as your "first gear". They’re perfect when you’re prototyping a report or handling a small list.

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Method 1: Use the JOIN function inside a sheet

JOIN is built for turning many cells into a single, neatly formatted string.

Example: combine first and last name

1. Suppose first names are in A2:A, last names in B2:B.
2. In C2, enter: =JOIN(" ", A2, B2)
3. Drag the fill handle down column C.

Now each row contains a full name like Alex Chen.

Example: join a range into one comma-separated cell

1. You have tags in D2:D10.
2. In another cell, enter: =JOIN(", ", D2:D10)
3. You get tag1, tag2, tag3, ... in one cell.

See the official docs for syntax details: https://support.google.com/docs/answer/3094077

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Method 2: Concatenate with the & operator

If you’re only joining a few cells, you can skip JOIN and use &:

1. In C2, enter: =A2 & " " & B2
2. Drag down to apply to other rows.

Pros: very explicit and easy to debug. Cons: gets messy when you’re joining many cells or changing delimiters.

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Method 3: Build join keys for lookups

Sometimes you need to "join" data across two sheets, like matching CRM leads to billing data. You can’t do a true SQL join in native Sheets, but you can emulate it.

Step-by-step with helper keys:

1. In Sheet Leads, create a key column K with: =A2 & "|" & B2 (e.g., email + country)
2. In Sheet Billing, create the same style key in column K.
3. In Leads!L2, use VLOOKUP against Billing: =VLOOKUP(K2, Billing!K:Z, 2, FALSE)

JOIN isn’t doing the matching itself here, but it helps you build robust composite keys that power your lookups.

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Method 4: Manual merging with copy–paste

For very small datasets:

1. Confirm both sheets use the same column order.
2. Copy the rows from Sheet B.
3. Paste them under the data in Sheet A.
4. Use JOIN or & columns to format final values.

Pros: quick for < 50 rows. Cons: no audit trail, easy to misalign columns, impossible to scale.

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Method 5: Pseudo left-join with IMPORTRANGE + VLOOKUP

To approximate a left join (all rows from Sheet A, matched data from Sheet B):

1. In the destination file, allow access to the source file via IMPORTRANGE.
2. In A2, pull the left table (optional) with IMPORTRANGE.
3. Next to your left table (e.g., in column G), enter: =ARRAYFORMULA(IF(A2:A="","", VLOOKUP(A2:A, IMPORTRANGE("<URL_of_right_sheet>", "Sheet1!A:Z"), 2, FALSE)))
4. Use JOIN to tidy any multi-column outputs into single descriptive fields.

This is more advanced but still fully manual and formula-driven.

For more on combining ranges and functions, see the Sheets help center: https://support.google.com/docs

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2. No-code ways to join Google Sheets at scale

When you’re a founder or agency owner, you rarely have time to babysit formulas. No-code tools sit between "spreadsheet-only" and "full AI agent" and are ideal when your logic is stable but your data volume is growing.

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Method 6: Use Sheetgo to left join two Google Sheets

Sheetgo provides a visual way to combine multiple Google Sheets, including left joins.

Set it up:

1. Install Sheetgo from the Google Workspace Marketplace.
2. Create a new workflow and choose Create connection.
3. Select Multiple files and pick the two Google Sheets you want to merge.
4. In the configuration, choose Left join as the join type.
5. Select the join column (for example, email or account ID).
6. Choose your destination file and sheet.
7. Save and run the workflow; schedule automatic refreshes (e.g., hourly).

Full guide: https://www.sheetgo.com/blog/how-to-solve-with-sheetgo/how-to-left-join-two-google-sheets/

Pros:

• True left-join behavior with a UI.
• Scheduled updates keep your master sheet fresh.
• Great for recurring reporting pipelines.

Cons:

• Another tool to manage and pay for.
• Logic lives in Sheetgo, not directly in the spreadsheet.

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Method 7: Use add-ons like Coefficient to prep ranges for JOIN

Tools like Coefficient focus on pulling live data from CRMs, ad platforms, and warehouses into Google Sheets.

Typical workflow:

1. Use Coefficient to import live Salesforce/HubSpot data into one tab.
2. Import ad platform or analytics data into another tab.
3. Build helper columns (keys, clean names, etc.).
4. Use JOIN or TEXTJOIN to combine labels, tags, or dynamic filter strings.
5. Point dashboards or pivot tables at the joined, cleaned ranges.

Pros:

• Data stays fresh without CSV exports.
• You focus on the join logic and business rules.

Cons:

• Still requires manual formula setup.
• Cross-file joins may still need VLOOKUP/INDEX/MATCH tricks.

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3. Joining Google Sheets data with AI agents at scale

Manual and no-code tools are great until your workflows become truly multi-step: pulling from email, CRM, web apps, then shaping everything in Google Sheets for each client. That’s where an AI computer agent, such as one powered by Simular Pro, becomes your operations teammate.

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Method 8: Have an AI agent operate Google Sheets like a power user

With a computer-use agent, you describe the workflow once; the agent then clicks, types, and navigates across your desktop and browser like a human.

Example workflow for an agency owner:

1. The agent opens your browser, logs into Google Drive, and opens two client sheets.
2. It inserts new columns to build join keys (e.g., =A2 & "|" & B2).
3. It applies JOIN formulas where you need readable strings (tag lists, full names, UTM bundles).
4. It sets up or updates VLOOKUP/IMPORTRANGE-based pseudo joins.
5. It checks for errors (#N/A, blanks) and logs issues into a "Data QA" tab.
6. It saves and can notify your team via webhook or email.

Pros:

• No need to learn every advanced Sheets function.
• Works across multiple Google accounts, files, and tools.
• Transparent execution: every step is visible and inspectable.

Cons:

• Requires a bit of upfront workflow design.
• Best suited once your process is repeatable.

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Method 9: End-to-end data prep from web + apps into Google Sheets

Simular-style agents don’t stop at Sheets. They can:

1. Log into your CRM to export new leads.
2. Scrape campaign data from ad dashboards or analytics tools.
3. Paste or import the raw data into staging tabs in Google Sheets.
4. Use JOIN and related formulas (SPLIT, CONCATENATE) to normalize fields (e.g., building a unified campaign_key from platform, country, and offer).
5. Generate clean reporting tabs that your team or clients see.

Pros:

• Replaces multiple brittle integrations and scripts.
• Handles thousands to millions of steps with production-grade reliability.
• Easy to adjust when your schema or tools change.

Cons:

• More powerful, so you should invest in clear instructions and guardrails.

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Method 10: Nightly "data janitor" for Google Sheets

Imagine telling your AI agent: "Every night at 1 a.m., clean all our client reporting sheets." The agent can:

• Run through a checklist across dozens of sheets.
• Rebuild join fields.
• Re-apply JOIN formulas where new rows were added.
• Archive outdated tabs.

Over time, this becomes an invisible ops layer that keeps your Google Sheets universe joined, consistent, and ready for analysis—without a human ever dragging a fill handle again.