The LinkedIn Automation Stack That Actually Executes: nRev + Captain Data

If you're managing LinkedIn prospecting today, you know the pain:

You scrape post comments in Captain Data. Export to CSV. Import to your CRM. Manually score which commenters are worth reaching out to. Draft personalized emails one by one. By the time you're done, the moment is cold and half your leads have moved on.

Or maybe you're using Clay + Captain Data with a webhook. You've spent 3 hours debugging field mappings. Your enrichment waterfall burns credits on duplicate lookups. And at the end of all that? You still have to manually trigger your outreach tool.

Today, that changes.

nRev now has native Captain Data integration. What gets scraped from LinkedIn gets scored, enriched, and actioned automatically—in one workflow, with zero manual steps.

What This Integration Unlocks

Captain Data Pulls. nRev Executes.

Captain Data is built for one thing: extracting high-quality B2B intelligence from LinkedIn at scale. It does this better than any tool on the market, using official APIs and safe scraping methods that won't get your account flagged.

But extraction is only half the job. What happens after you pull 500 LinkedIn post commenters? Or scrape job postings from 100 target companies? That's where most teams hit the wall.

nRev closes the loop. LinkedIn data flows directly into our AI workflow engine, where it gets:

• Enriched with contact info, firmographics, and tech stack data
• Scored by ICP fit, engagement quality, and timing signals
• Routed to the right playbook based on your custom rules
• Actioned with personalized outreach, CRM updates, and team notifications

No CSV exports. No webhook debugging. No middleware. Just drag-and-drop workflow nodes that turn LinkedIn signals into revenue.

Native Nodes. Not API Gymnastics.

Here's what makes this different from bolting Captain Data onto Clay or Zapier:

You don't manage the integration. We do.

In nRev's workflow builder, you'll find native Captain Data nodes for every major LinkedIn data source:

• Get Post Comments - Track who's engaging with your content
• Get Post Reactors - Find warm leads who liked or reacted
• Get Posts by Company - Monitor competitor activity and hiring signals
• Get Company Profile - Enrich account data in real-time
• Get Person Profile - Build prospect lists from LinkedIn
• Search LinkedIn Posts - Find intent signals across your ICP
• Get Comments by Person - Identify your most engaged prospects
• Get Reactions by Person - Track individual engagement patterns
• Search LinkedIn Posts Advanced - Complex queries with multiple filters

Drag any of these into your workflow. Configure in 30 seconds. Connect to enrichment, scoring, and outreach nodes. Done.

No API keys to copy-paste. No webhook URLs to manage. No "test your connection" anxiety. It just works.

How It Works: Four Steps from LinkedIn Signal to Executed Action

Step 1: Captain Data Extracts

Pick your data source. Maybe you want to track who comments on your LinkedIn posts. Or scrape companies posting engineering job openings. Or find people who reacted to competitor content.

Drop the appropriate Captain Data node into your nRev workflow. Configure your query (paste a post URL, define search filters, set your criteria). Captain Data pulls the data in real-time.

Step 2: nRev Enriches

Raw LinkedIn data is a starting point, not a complete picture. nRev automatically enriches each record with:

• Contact information (email, phone, direct dials)
• Company data (size, funding, tech stack, industry)
• Role verification (actual title vs. LinkedIn title)
• Engagement history (previous interactions with your brand)

Use your existing enrichment stack—Apollo, Clearbit, Lusha, whatever you've already invested in. Or use nRev's built-in enrichment. Either way, it happens automatically in the workflow.

Step 3: nRev Routes with Intelligence

Not every LinkedIn signal deserves the same action. nRev uses conditional logic to route different records to different playbooks:

High-fit prospects (VP+ at Series B companies in your target industry) → Instant Slack notification to account owner with context and a draft message

Medium-fit leads (IC roles at target companies) → Added to warm nurture sequence with personalized first touch

Low-fit or out-of-ICP → Logged in CRM for future reference, no outreach triggered

You define the rules. nRev executes them consistently, every time.

Step 4: nRev Executes and Closes the Loop

This is where nRev separates itself from data tools like Clay. We don't just prepare data—we act on it:

• CRM updates: Create records, update fields, log activities, assign tasks
• Outreach execution: Send personalized emails, trigger sequences, schedule follow-ups
• Team notifications: Alert account owners in Slack with full context
• Feedback loops: Failed enrichments, bounced emails, and disqualifications feed back to Captain Data to refine future scraping

The result? LinkedIn engagement turns into sales conversations in minutes, not days.

Real-World Playbooks: What You Can Build Today

Playbook 1: Content Engagement → Booked Meetings

The Scenario:You publish a LinkedIn post about RevOps automation. 47 people comment. Some are your ideal customers. Some are students. Some are competitors. Who do you reach out to first?

The Old Manual Way:

1. Click through 47 profiles manually
2. Guess who's worth your time based on their title
3. Copy-paste their info into your CRM
4. Draft a personalized email referencing their comment
5. Send it 3 days later when you finally get through the list
6. Wonder why your response rate is 8%

With nRev + Captain Data:

1. Captain Data node: "Get Post Comments" (pulls all 47 commenters instantly)
2. nRev enriches each commenter with company data and contact info
3. nRev scores by ICP fit:
   • A-tier (VP+ at $5M+ ARR SaaS companies): 4 people
   • B-tier (Manager+ at target companies): 12 people
   • C-tier (Out of ICP or low intent): 31 people
4. nRev routes by tier:
   • A-tier: Instant Slack to account owner - "Sarah Chen (VP Sales, Acme Corp) just commented on your RevOps post. Here's her email and a draft: 'Sarah, loved your take on X. Most VPs I talk to struggle with Y—does that resonate?'"
   • B-tier: Auto-added to warm outreach sequence with comment reference
   • C-tier: Logged in CRM, no action
5. Result: 4 high-value conversations started within 30 minutes while the post is still trending

Why It Works:You're reaching out while they're actively thinking about your topic, with personalized context they just gave you, prioritized by who's most likely to buy.

Playbook 2: Competitor Monitoring → Switch Campaigns

The Scenario:Your main competitor posts about their "new pricing" or "Q1 product updates." Their customers and prospects are commenting and reacting. Some are happy. Some are frustrated. This is your opportunity.

With nRev + Captain Data:

1. Captain Data node: "Get Post Reactors" on competitor posts (tracks everyone who engaged)
2. nRev enriches each reactor (are they a current customer? A prospect? Someone in your ICP?)
3. nRev analyzes comment sentiment:
   • Frustrated comment: "Their pricing is insane now" → High-priority switch candidate
   • Neutral reaction: Just liked the post → Medium-priority nurture
   • Positive comment: "Love this update!" → Low priority (they're happy)
4. nRev triggers different campaigns:
   • Frustrated users: "We solve [specific pain point] differently. Here's how we price..." outreach
   • Neutral engagers: Add to content nurture with competitive positioning
   • Happy users: Log for future (they might switch later)
5. Result: You're having conversations with prospects who are actively evaluating your competitor, with context about what they care about

Why It Works:You're intercepting buying intent at the exact moment prospects are engaging with your competition. They're already thinking about the problem—you're just offering a better solution.

Playbook 3: Hiring Signals → Account-Based Outreach

The Scenario:Target companies post "We're hiring!" for Sales, RevOps, or GTM roles. This is a signal they're scaling. Which means they probably need tools that support growth.

With nRev + Captain Data:

1. Captain Data node: "Get Posts by Company" filtered for hiring keywords ("we're hiring," "join our team," "now hiring")
2. nRev enriches each company (funding stage, current tech stack, decision-makers)
3. nRev scores hiring velocity:
   • Posted 5+ roles in 30 days = Scaling fast = High intent
   • Posted 1-2 roles = Steady hiring = Medium intent
4. nRev identifies decision-makers (VP Sales, CRO, Head of RevOps)
5. nRev auto-drafts contextual outreach:
   • "Saw you're expanding your sales team with 3 new AEs. Most companies hiring that fast hit pipeline visibility challenges around the 6-month mark. Want to see how [Similar Company] solved this while scaling from 5 to 20 reps?"
6. Result: Reach buyers when they have budget, urgency, and a mandate to improve processes

Why It Works:Hiring = budget allocated. You're reaching out with a relevant message at exactly the right time in their growth curve.

Playbook 4: Hyper-Personalized Prospecting at Scale

The Scenario:You want to build a list of 500 VPs of Sales who recently engaged with content about "outbound automation" or "sales tech stack." Then send them personalized outreach that references their specific engagement.

The Clay + Phantombuster Way:

1. Build a Phantombuster scraper to pull LinkedIn post engagers (costs execution hours, risks account bans)
2. Export CSV
3. Import to Clay
4. Run 6 enrichment waterfalls (company data, email, phone, tech stack) - burn credits on every lookup, including failures
5. Use Clay AI to generate emails (generic templates that sound AI-written)
6. Export to Instantly or Smartlead for sending
7. Manually track deliverability and replies
8. Time invested: 4-6 hours for setup, ongoing manual management

With nRev + Captain Data:

1. Captain Data node: "Search LinkedIn Posts Advanced" (e.g., posts containing "outbound" with comments from VPs of Sales in last 30 days)
2. nRev enriches in real-time (company data, contact info, tech stack) - only runs enrichment on valid records
3. nRev scores by ICP fit + engagement recency (someone who commented yesterday is hotter than 29 days ago)
4. nRev generates personalized emails with GPT-4:
   • "Hi [Name], saw your comment on [Author]'s post about outbound automation. You mentioned [specific point from their comment]. Most VPs I talk to..."
5. nRev sends via your connected email tool (Instantly, Smartlead, or native sending)
6. nRev tracks opens, replies, and bounces - automatically adjusts follow-up cadence
7. Time invested: 15 minutes to build, runs on autopilot

The Difference:

• Time: 4-6 hours → 15 minutes
• Cost: Clay ($149-800/mo) + enrichment credits + Phantombuster ($69-439/mo) + outreach tool → nRev handles it all
• Quality: AI-generated templates that sound robotic → Context-aware messages that reference actual behavior
• Maintenance: Constant webhook debugging and credit management → Set it and forget it

Why This Beats the Alternatives You're Using Today

vs. Clay + Captain Data (via webhook)

Most RevOps teams using Captain Data today are either:

1. Exporting CSVs and manually importing them to other tools
2. Using Clay with a webhook connection to receive Captain Data outputs

Here's why the nRev approach is fundamentally different:

The Real Cost Difference:

Clay users typically pay:

• Clay: $149-$800/month (depending on usage)
• Captain Data: $99-$500/month
• Enrichment credits: $50-$200/month (Apollo, Clearbit, etc.)
• Outreach tool: $30-$200/month (Instantly, Smartlead)
• Zapier: $20-$70/month for premium features
• Total: $348-$1,770/month for a duct-taped stack

nRev consolidates enrichment, workflow automation, and outreach execution into one platform. See pricing →

vs. Phantombuster + Manual Process

Phantombuster pricing ranges from $69 to $439 per month, with strict execution time limits. Users on the $69 Starter plan get 20 hours of execution time. Sounds like a lot until you realize:

• Scraping 1,000 LinkedIn profiles takes 3-5 hours
• Running daily automation hits the limit in a week
• Rate limits are much more restrictive than manual actions, with Phantombuster suggesting staying under 80 profile visits daily to avoid detection

Beyond cost, there are operational headaches:

• Risk of account bans when automation runs too aggressively
• Scripts break frequently when LinkedIn updates their platform, requiring constant monitoring
• No built-in enrichment—you have to export and enrich elsewhere
• No action layer—Phantombuster extracts data, then you figure out what to do with it

nRev + Captain Data solves all of this:

Who This Integration Is Built For

RevOps Engineers

You're tired of managing a Frankenstein stack of Captain Data → Clay → Zapier → HubSpot → Instantly. You want one platform that handles the entire flow from LinkedIn signal to executed outreach. You appreciate drag-and-drop simplicity but also want the flexibility to build complex conditional logic.

You'll love this because: Native nodes eliminate middleware hell. You can build sophisticated multi-step workflows in 15 minutes that used to take you 6 hours and three different tools.

GTM Engineers at Series A-C Companies

You're responsible for pipeline generation with a lean team. You need to do more with less tooling. LinkedIn is your best channel, but you don't have bandwidth to manually process hundreds of prospects per week.

You'll love this because: Automated execution means you're not just building lead lists—you're actually working them. One person can handle workflows that used to require a team.

Sales Ops Leaders

You're managing Captain Data or Clay for your team but drowning in manual CRM updates and export/import cycles. Your reps complain about data quality. Your CSO wants to know why it takes 3 days to follow up on warm LinkedIn engagement.

You'll love this because: Real-time processing means leads hit your CRM instantly, fully enriched, with context and next actions already defined. Your team stops doing data entry and starts selling.

Marketing Ops Teams

You're running LinkedIn content plays and event campaigns, but you struggle to convert engagement into pipeline. Post comments and event attendees sit in spreadsheets while your SDRs work cold lists instead.

You'll love this because: Content engagement becomes a qualified lead pipeline. Every post comment, every event signup, every webinar attendee gets scored and routed automatically. Marketing attribution becomes trackable end-to-end.

You'll Love This Integration If You:

• Currently use Clay or Phantombuster for LinkedIn data but manually handle everything that comes next
• Have Captain Data (or are considering it) but don't have engineering resources to build custom workflows
• Believe LinkedIn is your best channel but lack the automation to scale it without hiring 3 SDRs
• Are technical enough to appreciate drag-and-drop simplicity but don't want to code integrations
• Want one platform for data extraction, enrichment, and execution—not five tools held together with Zapier

This Might Not Be For You If:

• You're looking for a LinkedIn bot that violates TOS (Captain Data uses safe, API-first methods)
• You only need basic profile enrichment (just use Apollo or Clearbit directly)
• You're not ready to execute outbound (this is built for teams who want data AND action)
• You're a solo founder just getting started (this is for teams doing volume prospecting)

Getting Started: From Zero to First Workflow in 15 Minutes

What You'll Need:

• Active nRev account (sign up here if you don't have one)
• Captain Data account (sign up here or connect your existing account)

Setup Process:

Step 1: Connect Captain Data (2 minutes)

1. In nRev: Go to Integrations → Find "Captain Data"
2. Click "Connect"
3. One-click OAuth authorization (no API keys, no webhook URLs)
4. Done

Step 2: Build Your First Workflow (10 minutes)

1. Open nRev's workflow builder
2. Drag in a Captain Data node from the left sidebar
   • Example: Choose "Get Post Comments"
3. Configure the node:
   • Paste your LinkedIn post URL
   • Set any filters (comment length, commenter criteria, date range)
4. Add an enrichment node (Apollo, Clearbit, or nRev's built-in enrichment)
   • Map fields: LinkedIn profile URL → email lookup
5. Add scoring logic:
   • Filter by company size (e.g., 50-500 employees)
   • Filter by title (e.g., contains "VP" or "Head of" or "Director")
   • Score by engagement quality (comment length, thoughtfulness)
6. Add action nodes:
   • High-score leads → Send to CRM + Notify account owner in Slack
   • Medium-score leads → Add to nurture sequence
   • Low-score leads → Log only, no outreach
7. Name your workflow, activate it

Step 3: Test with Sample Data (2 minutes)

1. Click "Test Run" with a few sample records
2. Review the output: Did records get scored correctly? Are CRM fields mapping properly?
3. Make any adjustments

Step 4: Go Live (1 minute)

1. Activate the workflow
2. Monitor the dashboard to see records flowing through
3. Check Slack for notifications, CRM for new records

Total Time Investment:

• First workflow: 15 minutes
• Production-ready setup (with testing and CRM mapping): 1 hour

Pricing: Consolidate Your Stack, Cut Your Costs

We don't price like Clay (pay per credit, burn through your budget on failed enrichments). We don't price like Phantombuster (pay for execution hours you may or may not use).

nRev pricing is simple and transparent. View full pricing details →

The Math on Stack Consolidation:

What most teams pay today:

• Clay: $149-$800/month
• Captain Data: $99-$500/month
• Apollo/Clearbit enrichment credits: $50-$200/month
• Instantly/Smartlead for outreach: $30-$200/month
• Zapier premium: $20-$70/month
• Total: $348-$1,770/month

With nRev + Captain Data:

• nRev: See pricing page
• Captain Data: Starting at $99/month
• Everything else is included: Enrichment, CRM sync, outreach execution, workflow automation

Most customers save 40-60% versus stacking Clay + Apollo + Instantly + Zapier. Plus you get:

• One bill instead of five
• One platform to learn instead of five
• One support team instead of five
• Faster time-to-value (15 minutes vs. 4+ hours for first workflow)

Frequently Asked Questions

Do I need to know how to code?

No. If you can build a Zap or a Clay table, you can build an nRev workflow. Everything is drag-and-drop nodes with simple configuration forms. Zero coding required.

How is this different from Clay + Captain Data via webhook?

Three main differences:

1. Native integration - No webhook configuration, no field mapping, no broken connections
2. Execution layer - nRev actually executes outreach and CRM updates; Clay just prepares data
3. All-in-one platform - Enrichment, scoring, CRM sync, and outreach in one tool vs. duct-taping four tools together

Will this get my LinkedIn account banned?

No. Captain Data uses official APIs and follows LinkedIn's rate limits. Unlike browser-based scrapers (Phantombuster, Expandi) that simulate human clicks, you're making legitimate API calls. Captain Data has been operating safely for years with thousands of users.

Can I use my existing Captain Data account?

Yes! Connect your existing Captain Data account in one click during setup. All your existing Captain Data workflows and data stay intact. You're just adding nRev as an execution layer.

What if I don't have Captain Data yet?

You can sign up for Captain Data directly and connect it to nRev. We'll have a partnership link soon that provides additional benefits to new Captain Data users coming from nRev.

How long does setup take?

Most users build their first workflow in under 15 minutes. Production-ready workflows with full CRM mapping and testing typically take about 1 hour. Compare that to 4-6 hours for a similar setup in Clay with webhook configuration and enrichment waterfall debugging.

What CRMs does this integrate with?

nRev syncs natively with HubSpot, Salesforce, Pipedrive, and Copper. Updates flow automatically—no Zapier needed. If you use a different CRM, we can typically set up a custom integration or use our webhook output to connect via Zapier.

Do I still need Apollo or Clearbit?

You can use your existing enrichment providers with nRev, or use nRev's built-in enrichment. Most customers find they can reduce their Apollo/Clearbit spend because nRev's smart enrichment only runs lookups when needed (not on duplicate records or failed matches).

What happens if Captain Data has an outage?

nRev workflows automatically retry failed operations. If Captain Data is temporarily unavailable, your workflow will pause and resume when the service is back. You'll get a notification if any workflow is blocked for more than 30 minutes.

Can I A/B test different outreach messages?

Yes. Build multiple workflows with different messaging and route a percentage of leads to each variant. nRev tracks performance by workflow so you can see which messaging converts better.

Is there a free trial?

Yes. Sign up for nRev and get 14 days to test the platform, including the Captain Data integration. No credit card required to start.

What to Build First: Starter Workflow Recommendations

Not sure where to start? Here are three workflows most teams build in their first week:

Workflow 1: Post Engagement Response (Easiest)

Goal: Turn LinkedIn post comments into warm conversations
Captain Data Node: Get Post Comments
Time to Build: 10 minutes
Impact: High (catch prospects while they're engaged)

Workflow 2: Competitor Monitoring (Medium)

Goal: Find prospects engaging with competitor content
Captain Data Node: Get Post Reactors
Time to Build: 20 minutes
Impact: Medium-High (target in-market buyers)

Workflow 3: Hiring Signal Prospecting (Advanced)

Goal: Reach companies showing growth signals
Captain Data Node: Search LinkedIn Posts Advanced
Time to Build: 30 minutes
Impact: High (timing + relevance = conversion)

Start with Workflow 1, then expand from there.

Ready to Turn LinkedIn Data into Revenue?

The old way: Extract data → Export CSV → Import somewhere else → Manually process → Maybe take action → Watch leads go cold

The new way: LinkedIn signal → nRev workflow → Executed action → Tracked outcome

Captain Data finds the intelligence. nRev turns it into revenue. Automatically.

Get Started with nRev + Captain Data →

Questions? view our full documentation →