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If you run a sales or marketing team, Google Sheets is usually where raw data goes to hide: messy UTM tags, long product names, chaotic lead notes. The real value is locked inside those strings. Extracting just the pieces you need—first names, countries, coupon codes, SKUs—is what turns a passive sheet into a living dataset you can drive campaigns with.
Functions like LEFT, RIGHT, MID and REGEXEXTRACT (documented in Google’s Help Center let you surgically pull out exactly the text you care about. You can isolate area codes, strip tracking parameters, or grab IDs from URLs using RE2-powered regular expressions and capture groups.
But once the patterns work on 50 rows, the grind begins on 50,000. That’s where delegating to an AI computer agent changes the story. Instead of you re-building formulas for every new sheet, a Simular AI agent can open Google Sheets, apply the right extraction logic, test on samples, fix edge cases, and then run the workflow daily. Your role shifts from spreadsheet janitor to architect: you decide what “clean” looks like, the agent does the clicking, typing, and dragging at production scale.
Imagine you’re running a small agency. Every day, new leads land in a Google Sheet with subject lines like "[Webinar] Jane Doe – SaaS CMO – SF". All you really want is the first name, company, and city. Doing this row by row is a tax on your focus. Let’s walk through three layers of maturity: manual formulas, no‑code automations, and finally AI agents (like Simular) that take the work off your plate entirely.
These are your foundations. Even if you plan to automate later, you should know the basic tools.
Use these when the text you want always sits in the same position.
=LEFT(A2, 6)=ARRAYFORMULA(LEFT(A2:A, 6)) to fill a whole column.+1-408-555 US.=RIGHT(A2, 2)
=MID(A2, 8, 8)You can read more about these text functions in the Google Docs Editors Help Center: https://support.google.com/docs (search for "LEFT function", "RIGHT function", or "MID function").
When the position varies but there’s a marker word, combine SEARCH with LEFT or MID.
Extract everything before a marker:
promo_EU_summer_50off=LEFT(A2, SEARCH("_summer", A2) - 1)SEARCH returns the position where _summer starts._ isn’t included.
Extract everything after a marker:
promo_EU_summer_50off.=MID(A2, SEARCH("_summer", A2) + LEN("_summer"), 99)
When structure is messy but patterned, regex wins. Google Sheets uses RE2 regular expressions and documents REGEXEXTRACT here: https://support.google.com/docs/answer/3098244.
Basic syntax:
=REGEXEXTRACT(text, regular_expression)
Example 1 – First number in a sentence:
=REGEXEXTRACT(A2, "\d+")\d+ means "one or more digits". Result: 241.
Example 2 – Capture groups for multiple outputs:
=REGEXEXTRACT(A2, "You can also (\w+) multiple (\w+) from text.")extract and values.
Example 3 – Extract username from email:
alex.chen@example.com=REGEXEXTRACT(A2, "^([^@]+)")[^@]+ means "all characters until @".
Pros (manual methods):
Cons:
Once formulas work, the next pain is repetition. You don’t want to rebuild text extraction in every new sheet or client account.
Instead of writing formulas row-by-row, build a template that auto-expands.
Raw Subject, Clean First Name).=ARRAYFORMULA(IF(A2:A="",,REGEXEXTRACT(A2:A, "\[(.*)\]")))This is still “manual” but behaves like an automation: drop in data, get clean text.
Google Sheets lets you record a macro—no coding—then replay it.
Under the hood, Sheets stores this as Apps Script, but you interact with it as a one-click routine. See Google’s macro docs via the Help Center: https://support.google.com/docs (search "Record macros in Google Sheets").
If your text lives outside Sheets (CRMs, forms, email tools), no-code platforms can push it in already-extracted.
Typical pattern:
Pros (no-code automation):
Cons:
At some point, your spreadsheets start to look more like dynamic databases: thousands of rows, dozens of text formats, mixed languages, and edge cases galore. This is where an AI computer agent like Simular stops being a toy and becomes an operator on your team.
Sai is built to automate entire desktop workflows. That includes opening Google Sheets in the browser, inspecting cells, editing formulas, copying values, and logging results—with production‑grade reliability and transparent execution.
Story: Your sales ops manager used to spend Monday mornings fixing broken text extractions because marketing changed email subject templates again.
With a Simular AI agent you can:
Pros:
Cons:
Story: A marketing agency pulls daily exports from multiple tools: ad platforms, webinar software, CRM. All dump into one "Raw_Imports" sheet with ugly strings.
You can design a Sai workflow where the agent:
Pros:
Cons:
Instead of teaching everyone regex, you let teammates “ask” for extractions in plain language.
Example flow:
Now, Google Sheets stays your source of truth, but the mechanical spreadsheet work is offloaded to an AI operator that works across desktop, browser, and cloud.
Overall pros of AI agents:
Overall cons:
