✦ How It Works

The Play Sequence Behind
Competitive Intelligence

A complete breakdown of the step-by-step logic, data sources, and automations that power nRev's competitive prospect tracker.
Explore the 6 PhasesTechnical Specs
Multi-Source Data
2hr Monitoring
Privacy Compliant
Instant Alerts

THE PLAY SEQUENCE

The 6-Phase Workflow

From competitor discovery to actionable intelligence, here's exactly how nRev turns public LinkedIn activity into competitive advantage.
1

Competitor Sales Rep Discovery

Build and maintain a current list of all sales-facing employees at competitor companies.

Data Sources

LinkedIn Company Pages

Employee lists and org structure

LinkedIn Job Titles

Filter: SDR, BDR, AE, VP Sales, CRO

LinkedIn Profile URLs

Store for ongoing monitoring

ZoomInfo / Apollo

Email & phone enrichment

Logic Flow

Input: Competitor company LinkedIn URL
nRev scrapes company LinkedIn page
Filters employees by job title keywords:
  • Sales, SDR, BDR, AE, Account Executive, Business Development
  • Manager, Director, VP, Chief Revenue Officer
Extracts LinkedIn profile URLs for each person
Stores in monitoring database
Updates every 7 days (to catch new hires, role changes)
Output: Database of 20-200 competitor sales reps

Example Result

Competitor:
Clay.com
Monitored Profiles:
47
SDRs/BDRs:
15
Account Executives:
18
Sales Managers:
8
VPs of Sales:
4
CRO/Founders:
2
Last Updated:
Jab 28, 2025
50-200 credits per competitor (initial scan)
10-30 credits/week for ongoing updates
2

LinkedIn Engagement Monitoring

Track all public LinkedIn activity (likes, comments, shares, posts) from competitor sales reps.

Data Sources

Activity Feeds

Public actions visible without connections

Post Data

Author, content, timestamp, engagement

Profile Data

Company, title, location of engaged parties

Logic Flow

For each competitor sales rep in database:
Every 2 hours:
  • Check their LinkedIn activity feed
  • Extract any new likes, comments, shares, posts
For each engagement:
  • Get the LinkedIn post URL
  • Extract post author (person or company)
  • Extract post content/topic
  • Timestamp the engagement
Store all engagements in database

Example Result

Not Accessible
What Gets Captured
✕
Private messages
(not accessible)
✓
Competitor sales rep likes a LinkedIn post
✕
Connection requests
(not public)
✓
Competitor sales rep comments on a post
✓
Competitor sales rep shares/reposts content
✓
Competitor sales rep tags a company in their posts

Example Engagement Captured

engagement_log.json
{
  "date": "Jan 30, 2025, 2:14 PM",
  "competitor_rep": {
    "name": "John Smith",
    "title": "AE a Clay.com"
  }
  "action": "commented_on_post",
  "post_author": {
    "name": "Sarah Johnson",
    "title": "VP Sales a Acme Corp"
  },
  "post_content": "Hiring our first RevOps hire! Excited to scale our GTM motion..."
  "comment": "Congrats Sarah! Would love to chat about how Clay can help..."
}
3

ICP Qualification (The "Filter" Layer)

Determine if the person/company the competitor engaged with matches YOUR ideal customer profile. Filter out noise.

Data Sources

LinkedIn Profile

Job title, company, location

Enrichment APIs

Clearbit, BuiltWith, ZoomInfo

Your CRM

Existing accounts, deal stages, win/loss

ICP Definition (You Provide This)

engagement_log.json
ICP Definition:
  company_size: 50-500 employees industry:
    - B2B SaaS
    - FinTech
    - Healthcare Tech 
  funding_stage:
    - Series A
    - Series B
    - Bootstrapped with revenue 
  geography:
    - North America
    - Western Europe
  tech_stack:
    - Salesforce OR HubSpot 
  roles:
    - VP Sales
    - CRO
    - Head of Revenue
    - VP Marketing

Logic Flow

Competitor engages with LinkedIn post
Extract post author → Identify person & company
Enrich company data:
  • Company size (# employees)
  • Industry/sector
  • Funding stage (if startup)
  • Location/HQ, Tech stack, LinkedIn followers
Enrich person data:
  • Job title, Seniority level, Department
AI-powered ICP matching:
  • Compare enriched data against your ICP definition
  • Score 0-10 (10 = perfect ICP fit)
  • Threshold: Only proceed if score ≥ 7
IF score ≥ 7 → Flag as "High Priority"
IF score 4-6 → Flag as "Medium Priority"
IF score < 4 → Discard (noise)

Example ICP Match

enriched_data.json
Post Author: Sarah Johnson (VP Sales a Acme Corp)

Enriched Data:
  Company: Acme Corp 
  Size: 250 employees
  Industry: B2B SaaS
  Funding: Series B ($20M)
  Location: San Francisco, CA
  Tech Stack: Salesforce, HubSpot, LinkedIn
Sales Nav
  Role: VP Sales

9.2/10

ICP Score

Match Reasons:

✓
Body/Body-1/Medium
✓
Perfect industry match (B2B SaaS)
✓
Right funding stage (Series B)
✓
Uses Salesforce (tech stack match)
✓
Decision-maker role (VP Sales)
PROCEED TO ALERT
20-50 credits per engagement - enrichment costs
4

CRM Cross-Reference (Risk Assessment)

Check if this company/person is already in your CRM. Determine relationship status and risk level.

Logic Flow

Qualified ICP Match detected
Search your CRM (Salesforce/HubSpot) for:
  • Company name match
  • Domain match
  • Contact name match
IF FOUND → Determine status:
  • Active Opportunity (Stage 1-5)
  • Closed-Won (Current Customer)
  • Closed-Lost (Former Prospect)
  • Churned Customer, Old Lead (no active engagement)
IF NOT FOUND → Flag as "New Prospect Opportunity"

ICP Definition (You Provide This)

CRITICAL RISK

Immediate Action Required
  • Competitor engaging with Active Opportunity in late stages (Stage 3+)
  • Competitor engaging with Current Customer

HIGH RISK

Action Recommended
  • Competitor engaging with Active Opportunity in early stages
  • Competitor engaging with Closed-Lost from <12 months ago

OPPORTUNITY

Add to Pipeline
  • Competitor engaging with ICP match NOT in your
  • CRM Indicates in-market buyer

LOW RISK

Monitor
  • Competitor engaging with old leads (>2 years)
  • Competitor engaging with churned customers (>2 years)
Company: Acme Corp
CRM Status: ✅ FOUND
🚨 CRITICAL
Opportunity ID: #12345
Opportunity Name: "Acme Corp - Sales Automation"
Stage: Stage 3 - Proposal Submitted
Amount: $450,000
Close Date: March 15, 2025
Owner: Mike Chen (AE)
Champion: Sarah Johnson (VP Sales)

Risk Level: 🚨 CRITICAL
Why: Competitor engaging with our champion in late-stage deal
5

Alert Generation & Delivery

Send actionable, contextualized alerts to the right people at the right time.

Slack

Primary

Email

Secondary

CRM Log

Always

Dashboard

Optional
5-10 credits per alert- formatting, CRM logging
6

CRM Cross-Reference (Risk Assessment)

Check if this company/person is already in your CRM. Determine relationship status and risk level.

Digest Contents

CRM Status: ✅ FOUND

Competitive Activity Summary

  • Total engagements tracked last week
  • Breakdown by competitor
  • Most active competitor sales reps

Account Risk Assessment

  • Accounts with multiple competitor touches
  • New competitors detected in your pipeline
  • Accounts moving from low → high risk

Example Weekly Digest

Weekly Competitor Intelligence Digest

Week of Jan 24-30, 2025

47

Primary

23

Secondary

5

Always
🟢

  Activity Summary

47

Primary

23

Secondary

5

Always
1. Clay.com
18 (38%)
2. Apollo.io
14 (30%)
3. ZoomInfo
09 (19%)
🔴

  HIGH RISK ACCOUNTS

🚨  Acme Corp - 3 competitors detected, Active Opp ($450K)
🚨  TechFlow Inc - 2 competitors, Customer (at risk of churn)
⚠️   DataSync Co - New competitor activity, Stage 2 Deal
🔴

  WIN/LOSS TRACKING

2 Wins

Both had early competitor detection (avg 3 weeks notice)

2 Wins

Both had early competitor detection (avg 3 weeks notice)

YTD Competitive Win Rate: 67% (when competitor detected early)

Early detection increasing win rate by ~15%

Technical Specifications

Everything you need to know about data handling, integrations, and system requirements.

Update Frequency

Competitor rep discovery
Every 7 days

LinkedIn engagement monitoring
Every 2 hours

CRM sync
Real-time (webhooks) or every 30 min

Data Retention

Competitor rep discovery
Every 7 days

LinkedIn engagement monitoring
Every 2 hours

CRM sync
Real-time (webhooks) or every 30 min

Privacy & Compliance

Data scope
Public LinkedIn activity only

No scraping of
Private profiles or DMs

GDPR
Compliant (DPA available)

SecurityGDPR
SOC 2 Type II certified

Integrations Required

LinkedIn
Public LinkedIn activity only

CRM
Salesforce OR HubSpot (OAuth)

NotificationsGDPR
Slack (OAuth) or Email (SMTP)

Integrations Optional

Enrichment
Clearbit / ZoomInfo

Review monitoring
G2 / Capterra

Data export
Your data warehouse

Credit Consumption

Initial setup
200-500 credits

Ongoing
1,000-3,000 credits/week

Weekly digest
100 credits

Customization Options

Configure nRev to match your exact needs. Every aspect is fully customizable.

ICP Definition

  • Company size range
  • Industries (include/exclude)
  • Funding stages
  • Geographic regions
  • Tech stack requirements
  • Custom firmographic criteria

Competitor List

  • Add/remove competitors anytime
  • Track 3-20+ competitors (based on plan)

Alert Thresholds

  • ICP match score threshold (default:7/10)
  • Alert frequency (real-time, daily, weekly)
  • Risk levels to alert on

Alert Routing

  • Route to different Slack channels by deal stage
  • Assign alerts to specific users/teams
  • Escalation rules for Critical alerts

Monitoring Scope

  • Track all accounts vs. only active opportunities
  • Include/exclude customer monitoring
  • Geographic focus filtering

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Not Spreadsheets.

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