

Every growth team eventually hits the same wall: your Google Sheets are full of gold, but you can’t see it through the noise. Typos in emails, random notes in phone fields, survey answers written in 20 different ways. REGEXMATCH is the pattern detector that turns that chaos into clear YES/NO logic.With a single formula, you can ask Sheets questions like “Does this cell contain a valid email?”, “Is this review negative?”, or “Is this lead from a .edu domain?” and get instant TRUE/FALSE answers you can filter, score, and trigger automations from. That’s why data analysts love REGEXMATCH—it’s a compact rule engine living inside your spreadsheet.Now imagine delegating those pattern rules to an AI computer agent running all day. Instead of you tweaking regex, an agent like Simular can open Google Sheets, generate and test REGEXMATCH formulas, copy them across thousands of rows, fix broken patterns, and wire the results into your CRM—while you focus on strategy, not syntax.
### 1. Manual ways to use REGEXMATCH in Google SheetsBefore you automate anything, you need to be fluent in how REGEXMATCH works natively.**1.1. Build your first REGEXMATCH formula**1. Open your sheet of raw data in Google Sheets.2. In an empty column, type a header like `Is valid?`.3. In the first cell under that header (e.g., `B2`), enter: `=REGEXMATCH(A2, "hello")`4. Press Enter. You’ll get `TRUE` if A2 contains "hello", otherwise `FALSE`.5. Drag the fill handle down to apply to all rows.Official docs: https://support.google.com/docs/answer/3098292**1.2. Validate email addresses**1. Assume emails are in column A.2. In `B2`, use a simple email pattern: ``` =REGEXMATCH(A2,"^[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Za-z]{2,}$") ```3. Drag down. Filter `FALSE` values to see broken emails.4. Use those results to clean or remove bad leads.**1.3. Flag leads by domain (e.g., .edu)**1. In `B2`, type: `=REGEXMATCH(A2, "\.edu$")`2. This returns `TRUE` when the email ends with `.edu`.3. Use Filter > Filter by condition > `Text is exactly TRUE` to isolate student or academic leads.**1.4. Tag sentiment in text reviews**1. Put reviews in column A.2. In `B2`, use: `=REGEXMATCH(A2, "(bad|broken|refund|angry|terrible)")`3. `TRUE` roughly equals negative sentiment; `FALSE` is neutral/positive.4. Use Conditional formatting with a custom formula `=REGEXMATCH($A2,"(bad|broken|refund|angry|terrible)")` to color negative rows red.**1.5. Combine REGEXMATCH with IF**Turn TRUE/FALSE into words:``` =IF(REGEXMATCH(A2,"com$"),".com lead","Other domain")```This makes the result easier for sales and marketing teams to read.More examples: https://support.google.com/docs/answer/3098292---### 2. No‑code automation methodsOnce your patterns work, you can stop copy‑pasting and let tools push REGEXMATCH across your stack.**2.1. Use ARRAYFORMULA for entire columns**Rather than dragging formulas manually:``` =ARRAYFORMULA(IF(A2:A="","",REGEXMATCH(A2:A,"^[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Za-z]{2,}$")))```* Put this in `B2`.* It auto-applies REGEXMATCH to every non-empty row in column A.* New rows are handled automatically.Learn ARRAYFORMULA patterns: https://support.google.com/docs/answer/3093275**2.2. Filter views for pattern-based segments**Combine FILTER + REGEXMATCH:``` =FILTER(A2:C, REGEXMATCH(A2:A, "\.edu$"))```* Creates a live list of `.edu` leads from your main data.* Perfect for separate outreach campaigns, without duplicating your master sheet.FILTER docs: https://support.google.com/docs/answer/3093197**2.3. Trigger workflows with Apps Script (light-code)**If you’re open to a tiny bit of script:1. Go to **Extensions > Apps Script**.2. Write a simple function that loops through rows, checks REGEXMATCH in a column, and sends an email or writes to another sheet.3. Add a time-driven trigger (e.g., every hour).Apps Script docs: https://developers.google.com/apps-script/guides/sheetsThis is still mostly point‑and‑click and scales beyond what formulas alone can do.---### 3. Scaling REGEXMATCH with AI agents (Simular)Manual regex is powerful but brittle. One new edge case and your leads slip through. An AI computer agent changes the game by operating your desktop, browser, and Google Sheets like a human—only faster and without fatigue.#### 3.1. AI agent as your regex assistantUsing Simular Pro (https://www.simular.ai/simular-pro), you can:* Describe the rule in plain English: “Mark rows TRUE when the email is valid and company name includes ‘labs’ or ‘ai’.”* Let the agent open your Google Sheet, draft a REGEXMATCH pattern, test it on sample rows, and refine until error rates drop.* Have the agent propagate formulas, add ARRAYFORMULA, and set up filters and conditional formatting.**Pros*** Non-technical teams don’t have to write regex.* Rapid experimentation: the agent can try several patterns and keep the best.* Every action is transparent and inspectable in Simular Pro logs.**Cons*** Initial onboarding time to define your data rules.* Best suited when you have repeatable, high-volume Sheets work.#### 3.2. End‑to‑end campaign data cleanupFor agencies and sales teams:1. Simular agent logs into your CRM, exports leads to Google Sheets.2. It inserts multiple REGEXMATCH formulas: email validity, domain type, phone format, UTM check.3. Cleans or flags bad rows, applies color‑coding, and writes a summary tab: total leads, valid vs invalid, top error types.4. Uploads the cleaned CSV back to your CRM or ad platforms.You get a continuously cleaned pipeline without touching a spreadsheet.#### 3.3. Multi‑source enrichment and quality controlSimular can also:* Scrape websites, LinkedIn, or tools like TradingView, push that data into Google Sheets, then* Use REGEXMATCH to validate tickers, URLs, or naming conventions before anything reaches your warehouse.**Pros*** Production‑grade reliability for workflows with thousands of steps, aligned with Simular’s design for long‑running agents.* Works across desktop, browser, and cloud tools, not just Sheets.**Cons*** Requires clear guardrails (what counts as a “valid” pattern) so the agent doesn’t over‑correct data.More about Simular’s approach and research-driven agents: https://www.simular.ai/about
Start with a simple use case: checking whether a cell contains a word or pattern.1. Open your Google Sheet and choose a column with text (e.g., A2:A).2. In the next column (B2), enter a basic formula: `=REGEXMATCH(A2, "hello")` This returns TRUE if A2 contains the string "hello" anywhere, FALSE otherwise.3. Drag the fill handle down from B2 to apply the formula to all rows.4. To check for a word at the **start** of the text, use `^`: `=REGEXMATCH(A2, "^Hello")`5. To check for a word at the **end**, use `$`: `=REGEXMATCH(A2, "world$")`6. Combine conditions by grouping with `|` (OR): `=REGEXMATCH(A2, "(hello|hi|hey)")`You now have a TRUE/FALSE column you can filter on. Official reference: https://support.google.com/docs/answer/3098292
To quickly spot invalid emails in Google Sheets, put all emails in one column (say, A). Then:1. In B1, type a header like `Valid email?`.2. In B2, paste this formula: ``` =REGEXMATCH(A2, "^[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Za-z]{2,}$") ``` This checks for `text@domain.tld` with a simple but practical pattern.3. Drag the formula down or wrap it in ARRAYFORMULA: ``` =ARRAYFORMULA(IF(A2:A="","", REGEXMATCH(A2:A, "^[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Za-z]{2,}$"))) ```4. Filter the `FALSE` values in column B to see problematic addresses.5. Optionally, combine with IF to label rows: `=IF(B2,"OK","Fix email")`This gives sales and ops teams a clear list of contacts to repair before importing into CRMs or sending campaigns.
REGEXMATCH shines when you need to segment text responses or notes by intent—like separating "interested" leads from "not now" responses.1. Assume customer messages are in column A.2. Decide on your intent keywords. For interest, maybe: `demo`, `pricing`, `ready to buy`.3. In B1, type `High intent?`.4. In B2, enter: ``` =REGEXMATCH(A2, "(?i)(demo|pricing|ready to buy|book a call)") ``` The `(?i)` makes the match case-insensitive.5. Drag down or convert to an ARRAYFORMULA to auto-apply.6. Now go to Data > Create a filter and filter B for TRUE to see high-intent messages.7. Create additional columns for other intents (support, churn risk, etc.) with their own patterns.This approach turns messy free-text into clear segments your sales or success team can act on immediately.
Combining REGEXMATCH with FILTER lets you create dynamic sublists based on patterns instead of manual filters.Example: show only `.edu` leads from a full export.1. Suppose your master data lives in A2:D, with emails in column B.2. On a new tab, decide where you want the filtered list to start (e.g., A2).3. Enter: ``` =FILTER(Leads!A2:D, REGEXMATCH(Leads!B2:B, "\\.edu$")) ``` Note: the dot is escaped as `\\.` in the string.4. Press Enter. You now see only rows where the email ends in `.edu`.5. Any time new data is added to the master sheet, this filtered view updates automatically.You can swap the regex to filter by campaign tags, country codes in phone numbers, or SKU patterns—anything REGEXMATCH can recognize.
When REGEXMATCH isn’t behaving, treat it like debugging a small program.1. **Test on a single, simple example.** Create a small test area with a few cells that *should* return TRUE and a few that *should* return FALSE.2. **Strip down the pattern.** If your regex is complex, start with a tiny version, e.g. `"com$"`, confirm it works, then gradually add pieces.3. **Escape special characters.** Characters like `.` `+` `*` `?` `(` `)` `[` `]` `|` often need escaping (`\.`) if you mean them literally.4. **Check anchors.** `^` locks you to the start of text; `$` to the end. Remove them temporarily to see if they’re the issue.5. **Use helper columns.** Break the logic into multiple REGEXMATCH calls instead of one giant pattern, then combine with `AND`/`OR`.6. **Refer to the RE2 syntax.** Google Sheets uses RE2: https://github.com/google/re2/wiki/SyntaxBy iterating in tiny steps, you’ll quickly find where your pattern breaks and regain confidence in your data checks.