How to Use LinkedIn Sales Navigator (Filters, Exports and the ToS Line)

Sales Navigator is the best B2B search index in existence, and most teams use maybe a fifth of it.

They run a title-and-company-size filter, scroll the results, open a few profiles, and copy names into a spreadsheet by hand. That is a very expensive way to use a tool that can express a search like “companies that grew headcount 20 percent in the last year, where the person changed roles in the last 90 days, and someone in my network already works there.”

This is a practical guide to the parts that actually matter: the filters worth learning, how to get a search out of LinkedIn and into a sequence without manual copying, and where the line sits between efficient and against LinkedIn’s terms.

What Sales Navigator is actually for

It is worth being precise, because the mental model determines whether you get value.

Sales Navigator is a search and monitoring layer over LinkedIn’s member and company graph. Its unique asset is not contact data. It has no email addresses and no phone numbers. Its asset is that LinkedIn’s data is maintained by the people it describes, which makes it the most current source in B2B for three specific things: who works where right now, what their actual role is, and when that changed.

That is the job. Everything else in your stack, the email address, the phone number, the sequencing, the deliverability, happens elsewhere. Teams that expect Sales Navigator to be a data provider are disappointed. Teams that use it as the targeting layer and pair it with an enrichment layer get a lot out of it.

Pricing sits at roughly $99 per user per month for Core, with Advanced around $150 and Advanced Plus quoted per organisation. The official product pages carry current numbers.

The filters that separate a good list from a mediocre one

Most people use three filters. There are far more, and a handful change the quality of a list completely.

Timing filters, the highest-value group

These express when, which is the hardest thing to get from any other source.

• Changed jobs in the last 90 days. The strongest single filter in the product. New leaders re-evaluate tooling in their first quarter, arrive with preferences from a previous employer, and have a mandate to change things. This one filter reliably outperforms most ICP refinements.
• Company headcount growth. Growth means budget, new problems and new hires. Combined with a department filter it tells you which function is growing.
• Recent senior leadership hire. Same logic as job changes, applied at the account level.
• Posted on LinkedIn in the past 30 days. A proxy for being reachable at all. Someone active on the platform is more likely to see a message than a dormant profile.

Precision filters

• Years in current position. Under one year is a change signal. Over five suggests entrenchment and, often, ownership of the current tooling.
• Seniority level plus function, rather than job title text. Titles are wildly inconsistent across companies. Function and seniority generalise where title strings do not.
• Excluded titles. The most underused field in the product. Removing consultants, students, freelancers and irrelevant adjacent functions frequently improves a list more than any additive filter.
• Account exclusions. Suppress existing customers, open opportunities and current employers of your team. Nothing damages credibility faster than prospecting an existing customer.

Relationship filters

• Connections of a specific colleague. Warm paths, made explicit.
• Shared experiences. Same former employer, same school. Genuine common ground rather than manufactured rapport.
• Following your company. A quiet first-party signal sitting inside a third-party tool. These people opted in.

A practical construction pattern: start broad on function and seniority, exclude aggressively, then layer one timing filter. A list of 200 people who changed roles this quarter in a growing company will outperform 2,000 matched on title alone, and it takes less time to work.

Boolean search, briefly but correctly

The keyword field accepts boolean, and it works in the title field too. The syntax is standard and worth committing to memory:

• AND, OR, NOT in capitals.
• Quotation marks for exact phrases: "revenue operations".
• Parentheses for grouping: ("head of sales" OR "vp sales") NOT assistant.

Two things that trip people up. There is no wildcard, so market* does not work and you have to enumerate variants. And boolean in the title field searches current title only, so pair it with the seniority filter rather than relying on it alone.

A workable title search for a sales leader, allowing for title inflation and regional variation:

("vp sales" OR "vice president of sales" OR "head of sales" OR "sales director" OR "cro" OR "chief revenue officer") NOT (assistant OR coordinator OR intern OR "sales development")

Getting the list out, which is where the workflow usually breaks

Here is the actual bottleneck. You have built an excellent search returning 400 people. Now what?

The manual path is what most teams do: open each profile, copy the name and company, paste into a sheet, then run that sheet through an enrichment tool to find emails, then upload the result into a sequencer. For 400 contacts that is hours of work, and it has to be redone every time the search should be refreshed.

The important thing to understand is that the search itself is the durable object, not the list. A saved search is a definition. The people matching it change every week as roles change and companies grow. Any workflow that treats the export as a one-time artefact goes stale immediately.

The efficient pattern is to hand the search to a tool that can resolve it, enrich the results, and load them into a sequence, rather than hand-copying the output. Salesgear supports importing directly from a Sales Navigator search URL, which collapses the copy-enrich-upload loop into a single step and means refreshing the list is re-running the import rather than repeating the manual work. Teams pulling large lists from a single saved search feel this most, because the manual version simply does not scale past a few hundred.

Whatever tool you use, the enrichment step is unavoidable, because Sales Navigator has no email addresses. What matters is that verification happens at the point of use rather than being served from an old cache. The reasoning is in best B2B data enrichment tools, and the finding mechanics in verified email addresses and LinkedIn email finder.

Staying on the right side of LinkedIn’s terms

This deserves a direct answer, because the space is full of tools that quietly put your account at risk.

LinkedIn’s User Agreement prohibits scraping, using bots or automated methods to access the service, and creating false identities. Enforcement is real and has escalated: restricted accounts, permanent bans, and in some cases legal action against the tool vendors.

The distinction that matters is who performs the action on LinkedIn.

Lower risk, because a person is acting and software is organising the work:

• Using Sales Navigator search and saved searches as intended.
• Reading profiles yourself and taking notes.
• Resolving a search through a tool that uses permitted access paths, then enriching contact data from separate sources.
• Sequencing LinkedIn tasks to a human, where the rep sends the message.

Higher risk:

• Browser automation that clicks, connects and messages on your behalf at volume.
• Bulk scraping of profile pages.
• Tools promising hundreds of automated connection requests a day.

The practical guidance: keep the sending of LinkedIn messages a human action and use software to decide who, when and what. That is both lower risk and, in our experience, more effective, because volume is not what makes LinkedIn work. Our compliant approach to LinkedIn in a multichannel sequence is described in how LinkedIn fits into outreach campaigns and the strategy side in the LinkedIn outreach strategy guide.

Using Sales Navigator as a signal monitor, not just a search box

The feature teams ignore most is monitoring, and it is arguably the better use of the subscription.

Saved leads and saved accounts generate alerts: job changes, company news, posts. That turns Sales Navigator from a list builder into a timing engine. Rather than asking “who should I contact,” you ask “who just became worth contacting.”

A workable weekly routine, about twenty minutes:

1. Save your target accounts, the few hundred you genuinely want, not your whole TAM.
2. Save the relevant contacts at each.
3. Once a week, review alerts only. Job changes and leadership hires first.
4. Anyone who changed roles goes into this week’s outreach, referencing the change honestly.
5. Anyone whose company posted relevant news goes in second.

This produces a small, timely list every week without building anything new. And because the signals are public, dated and specific, you can reference them in a message without being vague or creepy, which is the failure mode of anonymous intent signals. That contrast is the subject of why B2B intent data is wrong more often than you think.

What Sales Navigator will not do

Worth being clear, because the gaps determine the rest of your stack.

• No email addresses or phone numbers. You need an enrichment layer.
• Self-reported data. People inflate titles, delay updates and leave stale roles up. It is the most current source available and it is not audited.
• Weak coverage of non-LinkedIn markets. Coverage varies significantly by region and industry. Sectors with low LinkedIn adoption are thin regardless of your filters.
• No sending infrastructure. InMail exists and is limited and expensive at scale. Email sequencing, deliverability and warm-up happen elsewhere, which is its own discipline. See the sending domain playbook.
• No research depth. It tells you who someone is, not why to contact them. That inference layer is separate, and covered in why AI prospect research gets it wrong.

A workflow that holds together

Putting it together, end to end:

1. Define the search in Sales Navigator. Function and seniority, aggressive exclusions, one timing filter. Save it.
2. Import the search into your sequencing tool rather than copying results by hand, so refreshing is one action.
3. Enrich and verify at the point of use, not from a cache.
4. Research the ones worth researching. Not all 400. The 40 with a real timing signal.
5. Sequence multichannel, with LinkedIn steps as human tasks and email on properly warmed sending domains.
6. Save the accounts and work the alerts weekly. This is the compounding part.
7. Re-run the search monthly. The definition is durable, the membership is not.

Step two is where most of the time is won, and step six is where most of the meetings come from. Teams tend to over-invest in step one and skip step six entirely.

If you want the Sales Navigator search, the enrichment, and the multichannel sequence in one place rather than three, that is what Salesgear’s prospecting workflow is built around, with Sales Navigator import as the entry point. The wider tool landscape is in B2B prospecting.

Frequently asked questions

Can you export contacts from Sales Navigator?

Sales Navigator has no native bulk export, and browser tools that scrape profile pages breach LinkedIn’s User Agreement and put your account at risk. The workable approach is to pass the saved search to a tool that resolves it through permitted access paths and enriches contact details from separate sources, so the search definition stays the durable object and refreshing is a single action.

Does Sales Navigator include email addresses?

No. It has no email addresses and no phone numbers. It is a search and monitoring layer over LinkedIn’s member graph, so its value is knowing who works where right now and when that changed. You need a separate enrichment and verification layer for contact details.

What is the most useful Sales Navigator filter?

Changed jobs in the last 90 days. New leaders re-evaluate tooling in their first quarter, bring preferences from previous employers, and have a mandate to change things. Pair it with aggressive title and account exclusions, which improve list quality more than most additive filters.

Is LinkedIn automation against the terms of service?

LinkedIn’s User Agreement prohibits bots, automated access and scraping, and enforcement includes account restriction and permanent bans. The safe line is who performs the action: software deciding who to contact and when is fine, software clicking connect and send on your behalf at volume is not. Keep LinkedIn sends as human tasks within your sequence.

Is Sales Navigator worth $99 a month?

It depends on whether you use the monitoring features. As a search box alone it is hard to justify against cheaper data tools. As a timing engine, saved accounts generating weekly job-change and leadership alerts you actually work, it is one of the better value tools in outbound, because that timing data is genuinely difficult to source elsewhere.