Google Sheets Template: 7 LinkedIn Email Status Powerful Filters

If you've ever taken an export of a LinkedIn lead list and just been stuck on the same question--who should I email first and not hurt myself when it comes to deliverability?--this post is for you.

A raw LinkedIn list (even with emails) is not outreach ready. Some real life lists have typos, info@ role based inboxes, catch-all domains, duplicates, and stale addresses. The best way to prevent ruining your sender reputation is to segment by whether someone is verified or not and only scale if you have proof that your bounce rate is safe.

In this guide, you'll be creating a Google Sheets template that will automatically tidy up your list, clean up any verification labels (to make them VALID / RISKY / INVALID), create export-ready buckets and generate a simple send plan. You can use it with exports from any LinkedIn email scraper--then have the same workflow every time.

Who This Google Sheets Template Is For

This is a template for those operators that are doing outbound seriously - founders, SDRs, recruiters, agencies - all those that need to get from "LinkedIn leads" to "safe-to-send list" quickly.

It's especially useful when:

• You scrape or collect your leads once weekly and you need a process that is repeatable.
• Your verification tool has different terms for results (deliverable, unknown, catch-all etc.).
• You want one sheet on which your team can re-use without having to break formulas.
• You have to export clean segments into CRM or outreach tools (Hubspot, Pipedrive, Apollo like tools, etc.).

What this template does not do: make an email deliver magically. It helps your risk decrease by organizing the way you think about who you will contact first, how to treat uncertain addresses and how to stop re-mailing people who opted out.

VALID / RISKY / INVALID: What Do These Mean?

Your verification provider will have different names but you can boil it down to three results.

VALID: Safe to Send First

VALID will normally mean that the address syntax is correct, and that the domain/inbox appears to be deliverable. It's not a guarantee but it's the best starting segment to scale.

RISKY: Deliverability Depends on Strategy

RISKY often includes:

• Catch-All Domains (accept-all inboxes) -- if you're dealing with these, see our guide on catch-all email verification for a detailed breakdown.
• Role based addresses (info@, support@, careers@)
• Results "unknown" or "limited verification"

These addresses may work, though they can have spikes in terms of bounces if you blast them.

INVALID: Don't Email (Reference Only)

INVALID means that the email is not likely to be delivered. Don't send, keep for reporting, suppression or re-checking later if you have a strong reason to do so.

What Makes This Template Different From Simple Sheet Filtering

Most of the spreadsheets end at "filter by status." Which is not enough for reliable outbound. This template adds practical layers which make it "ops-ready":

• Status normalization: Normalize any provider labels to VALID/RISKY/INVALID without having to rewrite formulas.
• Priority deduping: If the same email comes in twice then keep the record with the "best" status and richest data. For a deep dive on deduplication logic, check out our guide to deduping LinkedIn leads in a spreadsheet.
• Risk scoring: A light-weight scoring system to ensure the prioritization of outreach with a safeguard of deliverability.
• Domain report: Identifying domains which drive risk (catch-all heavy, invalid spikes).
• Suppression control: A tab for preventing the re-sending to opt-outs or bounced recipients.

This is how you make a list into a repeatable system - not a one off clean up.

Template Structure: Tabs You Will Create

Create a new Google Sheet and create these tabs (exact names make it easier to read formulas):

1. README - Simple instructions, rules
2. RAWIMPORT - Paste/Import your exported list here
3. STATUSMAP - Maps of provider labels to VALID/RISKY/INVALID
4. CLEAN - Cleaned, deduped, normalized master table
5. VALIDBUCKET - Segment for being exported
6. RISKYBUCKET - Segment that is ready to be exported
7. INVALIDBUCKET - Segment that is for reference only
8. DOMAINREPORT - Risk by domain summarised
9. SUPPRESSION - Opt out, bounces, do not contact list
10. SENDPLAN - Outreach plan, batch plan

You can make it lean, but with these tabs, you can be sure that you don't get "formula spaghetti" when the sheet gets really large.

Step 1: Import Your LinkedIn List to RAWIMPORT

In RAWIMPORT, row 1 should be used as headers. Columns that are recommended minimum:

• Full Name
• Company
• Title
• LinkedIn URL
• Email
• Verification Status (label of your tool raw)
• Source (optional)
• Notes (optional)

If you're finding that your LinkedIn connections export is missing email data, a dedicated extraction tool can fill those gaps before you even reach this template.

Tips to Avoid Chaos Later On

• Keep Email in one column (no "email 1 / email 2" if you are not willing to expand the logic).
• Avoid merged cells.
• Don't attempt to "fix" emails in RAWIMPORT - the email should be edited in CLEAN, so that you can re-import safely.
• If your scraper will export into CSV format, then select File > Import > Upload and then select "Replace data in selected sheet."

Step 2: Cleaning and Dedupe -- CLEAN (No Loss of Best Record)

In CLEAN, you'll make emails standard, extract domains and de-dupe intelligently.

Clean Email + Extract Domain

Assuming RAWIMPORT email is in column E:

=ARRAYFORMULA(IF(RAWIMPORT!E2:E="",, LOWER(TRIM(RAWIMPORT!E2:E))))

Domain extraction:

=ARRAYFORMULA(IF(F2:F="",, REGEXEXTRACT(F2:F,"@(.+)$")))

(Here, F is your cleaned email column).

Priority Dedupe Rule (Keep Best Status)

A simple, reliable method:

1. Convert status into numeric rank (VALID=3, RISKY=2, INVALID=1)
2. Sort by email + rank desc
3. Leave the first instance of each of the emails.

You'll generate the rank in the next step and then, using SORT + UNIQUE logic (or SORTN), dedupe. This saves one of the most common mistakes: holding that first row that you imported - even though a later row has a better verification outcome. For a comprehensive walkthrough of canonical keys and merge rules, see our guide on deduping LinkedIn leads in a spreadsheet.

Step 3: Normalizing Verification Labels (STATUSMAP)

The different tools are writing out different labels. The fix is a mapping table.

In STATUSMAP:

• Column A: Raw label (e.g. deliverable, undeliverable, catch-all, unknown)
• Column B: Normalized label (VALID, RISKY, INVALID)

In CLEAN, normalize raw status (assuming RAWIMPORT status is column F):

=ARRAYFORMULA(IF(RAWIMPORT!F2:F="",,
  IFNA(VLOOKUP(LOWER(TRIM(RAWIMPORT!F2:F)), STATUSMAP!A:B, 2, FALSE),"RISKY")))

It is safer to default unknown labels to RISKY than it is to think that they are VALID.

Now create a rank:

=ARRAYFORMULA(IF(G2:G="",, SWITCH(G2:G,"VALID",3,"RISKY",2,"INVALID",1,2)))

Where G is the normalized value of the status column.

Step 4: Establish Export Ready Buckets (VALID / RISKY / INVALID)

Buckets should be "clean exports" which means:

• Only columns that you're going to be importing to CRM/outreach
• No helper columns unless absolutely necessary

Formula used in VALIDBUCKET:

=FILTER(CLEAN!A:Z, CLEAN!StatusNormalized="VALID")

For RISKYBUCKET, INVALIDBUCKET, change the condition.

Best Practice: Add a column in CLEAN called Export Ready? which returns a value of true if:

• Email is present
• Not in SUPPRESSION
• Status is the same as per rules of the bucket

That is, you get "safe segments" even with growing suppression.

Step 5: Guard Rails (Conditional Formatting + Data Validation)

This is where Sheets is a control panel as opposed to a dump.

Conditional Formatting

Normalized status column will be used:

• Text "VALID" -- green fill
• Text contains "RISKY" -- yellow fill
• Text contains "INVALID" -- red fill

Also highlight emails that are role based. Custom formula rule (assuming cleaned email is in column F):

=REGEXMATCH($F2,"^(info|support|sales|careers|hr|admin)@")

Data Validation

For any manual status overrides use:

Data > Data validation > Dropdown > VALID, RISKY, INVALID

This helps to avoid typos such as "Vald", which silently break filters.

Step 6: Develop a Simple Risk Score for Prioritizing Outreach

Buckets become a send order with the help of a score.

Start with a base score:

• VALID = 100
• RISKY = 60
• INVALID = 0

Then subtract risk factors:

• Role-based email: -20
• Catch all domain flag (if given): -15
• Missing LinkedIn URL: -10 (lower confidence lead)

Scoring formula (conceptual sample):

=ARRAYFORMULA(IF(StatusNormalized="",
  ,
  IF(StatusNormalized="INVALID",0,
    IF(StatusNormalized="VALID",100,60)
    -IF(RoleBased=TRUE,20,0)
    -IF(CatchAll=TRUE,15,0)
    -IF(LinkedInURL="",10,0)
  )))

Why this works: You stop arguing "should we email risky?" and start to operate based on "send highest confidence first and then test risky in controlled batches." If you want to understand why email match rate is low and how risk factors play into it, that guide digs deeper into the scoring logic.

Step 7: DOMAINREPORT -- Find Out Where Your Risk Is Coming From

Many problems with deliverability are not random. They cluster by domain.

In DOMAINREPORT use pivot like summary:

• Domain
• Count of emails
• % VALID / % RISKY / % INVALID

You can do this with the help of a pivot table or in a QUERY based table.

Actionable Insights You Will Receive

• Domains with abnormally high rates of INVALID (often scraping errors / out-of-date lists)
• Catch all heavy domains that you should send smaller batches of tests in
• Domains you may want to not outreach to at all (based on your outreach goals)

Domain Risk Grade

• A = >80% VALID
• B = 60-80% VALID
• C = 40-60% VALID
• D = <40% VALID

Step 8: SENDPLAN -- How to Email VALID First, and Test RISKY Safely

Any "magic tool" has less protection on your sending domain than a smart plan.

Suggested Sending Sequence

1. VALID first (highest scores are considered first)
2. RISKY test batches (small volume, keep your bearings with regards to bouncing)
3. Never send INVALID

A Practical Batch Method

• Batch 1: Top 100 VALID
• Batch 2: Next 200 VALID
• Batch 3: RISKY test (20-50 contacts)

If bounce is low, continue to slowly increase RISKY volume.

Export Flow

Each bucket tab should be ready to export:

1. Remove helper columns
2. Have consistent headers that you expect to get from your CRM/outreach tool

Then File > Download > CSV for that tab.

SUPPRESSION: The Tab That Prevents Painful Mistakes

If you are doing outbound for more than a week, you need to suppress.

In SUPPRESSION, track:

• Email
• Reason (opt out, hard bounce, complain, manual DNC)
• Date added
• Source (campaign/tool)

Then in CLEAN flag emails as suppressed:

=ARRAYFORMULA(IF(EmailClean="","",
  IF(COUNTIF(SUPPRESSION!A:A, EmailClean)>0, TRUE, FALSE)))

Lastly, ensure every bucket filter does not have suppressed leads.

This one tab avoids making the most expensive mistake of reaching out - sending an e-mail to someone who opted out or bounced hard - again.

Compliance and E-E-A-T Notes (What You Should Be Able to Explain)

If you're using data from LinkedIn as your source of outreach, you should be able to be very specific about your process and safeguards:

• Purpose limitation: Only collect fields that you really use.
• Opt-out handling: Honour unsubscribes fast and permanently.
• List hygiene: Suppress hard bounce and imposition of complaints.
• Auditability: Keep basic log of from where and when it was imported.

This template supports this: it supports storage of suppression, it will keep normalization transparent, it will not do "silent" changes - it separates RAWIMPORT from CLEAN.

(And yes - the rules vary from region to region, use case to use case. If you're in scale and operating, try to find some legal advice for your jurisdiction and market.)

Wrap-up: Make Any LinkedIn Export a Safe Outreach System

A LinkedIn email list has worth when it comes to being operational: cleaned, segmented, prioritized, safe to send. This Google Sheets template gives you a repeatable workflow:

1. Normalize the status of the verification to VALID / RISKY / INVALID
2. Dedup without losing the best record
3. Bucket leads to export ready tabs
4. Score risk to send smarter
5. Track suppression, so you won't burn up reputation

If you want this to plug nicely into your sourcing workflow, couple it with your LinkedIn export process so that every new list ends up in the same system - no reinventing, no messy manual filtering.