This scraper evaluates LinkedIn profiles and produces a 1–10 activity score that reflects how active and responsive each lead is. By understanding posting habits, engagement levels, and profile completeness, it helps you target prospects who are more likely to reply. If you're in sales, recruiting, or partnership outreach, this tool gives you a data-backed way to prioritize the right people.
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The LinkedIn Activity Index Scraper analyzes a profile URL and compiles engagement signals such as recent posts, reactions, activity frequency, and completeness indicators. It generates an activity score along with recommendations and insights to guide outreach decisions.
- Filters out inactive profiles so your outreach isn't wasted.
- Surfaces leads with real engagement signals, boosting reply rates.
- Breaks down scoring factors transparently so you understand each result.
- Provides detailed profile summaries beyond just the score.
- Helps automate pre-qualification in sales or recruiting pipelines.
| Feature | Description |
|---|---|
| Activity Scoring | Produces a 1–10 score based on multiple engagement and completeness metrics. |
| Profile Summary Extraction | Retrieves full name, headline, location, network size, premium status, and more. |
| Engagement Metrics | Counts posts, reactions, and time since last activity. |
| Recommendation Engine | Generates natural-language outreach advice with indicators. |
| Insight Generation | Highlights key strengths or red flags in the profile. |
| Performance Transparency | Includes processing time, timestamps, and status details in the output. |
| Field Name | Field Description |
|---|---|
| success | Whether the profile analysis completed successfully. |
| linkedin_url | The analyzed profile link. |
| activity_score | Activity score from 1–10. |
| recommendation | Text-based recommendation based on the score. |
| score_breakdown | Points by category such as completeness, premium status, engagement, and activity recency. |
| profile_summary | Details including full name, headline, location, follower and connection counts, premium/creator flags, and profile picture URL. |
| activity_metrics | Last activity date, days since activity, posts and reactions over the last 30 days. |
| insights | Key takeaways about the profile’s behavior. |
| analyzed_at | Timestamp of the evaluation. |
| processingTime | Duration of the analysis. |
| statusCode | HTTP status code recorded for the run. |
[
{
"success": true,
"linkedin_url": "https://linkedin.com/in/example",
"activity_score": 8,
"recommendation": "High activity — strong prospect",
"score_breakdown": {
"profile_completeness": 3,
"premium_status": 1,
"network_size": 2,
"recent_activity": 1,
"engagement_frequency": 1
},
"profile_summary": {
"full_name": "Jordan Smith",
"headline": "Sales Operations Manager",
"location": "New York, USA",
"connection_count": 980,
"follower_count": 1200,
"is_premium": true,
"is_creator": false,
"profile_picture_url": "https://media.linkedin.com/profilepic.jpg"
},
"activity_metrics": {
"last_activity_date": "2024-03-01",
"days_since_last_activity": 4,
"posts_last_30_days": 6,
"reactions_last_30_days": 42
},
"insights": [
"Consistent posting frequency",
"Good engagement levels",
"Large network size"
],
"analyzed_at": "2024-03-05T12:20:44Z",
"processingTime": 3.41,
"statusCode": 200
}
]
LinkedIn Activity Index Scraper/
├── src/
│ ├── main.js
│ ├── analyzer/
│ │ ├── activity_scoring.js
│ │ ├── metrics_collector.js
│ │ └── insights_generator.js
│ ├── scraper/
│ │ ├── profile_fetcher.js
│ │ └── html_parser.js
│ ├── utils/
│ │ ├── normalize.js
│ │ └── logger.js
│ └── config/
│ └── settings.example.json
├── data/
│ ├── sample_input.json
│ └── sample_output.json
├── package.json
└── README.md
- Sales teams prioritize leads with high engagement likelihood to boost reply rates and pipeline volume.
- Recruiters target actively engaged talent and avoid dormant profiles.
- Partnership teams identify responsive founders, creators, or executives.
- Growth teams enrich CRM records with dynamic activity scores.
- Automation builders integrate profile scoring into workflows for hands-off qualification.
Does it work for any LinkedIn profile?
Yes, as long as the profile is publicly accessible.
How is the activity score calculated?
It combines completeness, premium status, network size, recent activity, and engagement frequency.
Can I rely on the recommendation output?
Recommendations are generated from the score and offer practical outreach guidance.
Does it store or reuse my profile data?
No—each run analyzes only the provided URL and returns the results.
Primary Metric:
Completes most profile evaluations in a few seconds using optimized scraping and parsing routines.
Reliability Metric:
Maintains consistent scoring accuracy due to standardized metric collection.
Efficiency Metric:
Consumes minimal resources, enabling high-throughput lead analysis.
Quality Metric:
Produces richly detailed, actionable insights ideal for CRM enrichment and outreach optimization.
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