# Linkedin Analytics

> Analyze LinkedIn performance, track engagement metrics, and manage reactions/comments via Publora MCP

- Skill: `jhamidun/linkedin-analytics` (Agent Skill)
- Install (CLI): `npx skillmds@latest add jhamidun/linkedin-analytics`
- Raw SKILL.md: https://api.skillmd.com/api/skills/jhamidun/linkedin-analytics/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Data & Analytics
- Author: JHamidun (https://skillmd.com/u/jhamidun)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/jhamidun/linkedin-analytics

---


# LinkedIn Analytics

Get detailed analytics for your LinkedIn posts and profile using the Publora MCP server. Track impressions, engagement, follower growth, and interact with posts through reactions and comments.

## Prerequisites

**Plans:** Starter (free), Pro, Premium - LinkedIn is available on all plans including free.

### Getting Started

1. **Create account** at [publora.com/register](https://publora.com/register) (free)
2. **Connect LinkedIn** via OAuth in [Publora Dashboard](https://publora.com/dashboard)
3. **Get API key** at [publora.com/settings/api](https://publora.com/settings/api)
4. **Configure MCP** in Claude Desktop (`~/.claude/claude_desktop_config.json`):

```json
{
  "mcpServers": {
    "publora": {
      "type": "http",
      "url": "https://mcp.publora.com",
      "headers": {
        "Authorization": "Bearer YOUR_API_KEY"
      }
    }
  }
}
```

### REST API Fallback

If the MCP server is unavailable or returns errors, use the REST API directly:

**Base URL:** `https://api.publora.com/api/v1`

**Authentication:** Use `x-publora-key` header (NOT `Authorization: Bearer`):

```bash
# Get your connected platforms
curl -X GET "https://api.publora.com/api/v1/platform-connections" \
  -H "x-publora-key: sk_your_api_key"

# Get post statistics
curl -X POST "https://api.publora.com/api/v1/linkedin-post-statistics" \
  -H "x-publora-key: sk_your_api_key" \
  -H "Content-Type: application/json" \
  -d '{
    "platformId": "linkedin-abc123",
    "postedId": "urn:li:share:7123456789012345678",
    "queryTypes": "ALL"
  }'

# Get account statistics
curl -X POST "https://api.publora.com/api/v1/linkedin-account-statistics" \
  -H "x-publora-key: sk_your_api_key" \
  -H "Content-Type: application/json" \
  -d '{
    "platformId": "linkedin-abc123",
    "queryTypes": "ALL"
  }'
```

**Platform ID Format:** `linkedin-{id}` where `{id}` is from `/platform-connections` response.

Example IDs: `linkedin-XXXXXXXXXX`, `linkedin-abc123xyz`

📖 **Full API documentation:** [docs.publora.com](https://docs.publora.com)

## Analytics Tools

### linkedin_post_stats
Get engagement metrics for a specific LinkedIn post.

**Parameters:**
- `postedId`: LinkedIn post URN (e.g., `urn:li:share:123456` or `urn:li:ugcPost:123456`)
- `platformId`: Platform connection ID (e.g., `linkedin-abc123`)
- `queryTypes` (optional): Metrics to fetch: `IMPRESSION`, `MEMBERS_REACHED`, `RESHARE`, `REACTION`, `COMMENT`

**Response includes:**
- Impressions (total views)
- Unique impressions (members reached)
- Reactions count
- Comments count
- Shares/reposts
- Engagement rate

### linkedin_account_stats
Get aggregated statistics for your LinkedIn account.

**Parameters:**
- `platformId`: Platform connection ID
- `queryTypes` (optional): Metrics to fetch
- `aggregation` (optional): `DAILY` or `TOTAL` (default: TOTAL)

### linkedin_followers
Get follower count or growth over time.

**Parameters:**
- `platformId`: Platform connection ID
- `period` (optional): `lifetime` or `daily`
- `dateRange` (optional): For daily period: `{start: {year, month, day}, end: {year, month, day}}`

### linkedin_profile_summary
Get a combined profile overview with followers and stats.

**Parameters:**
- `platformId`: Platform connection ID
- `dateRange` (optional): Date range for stats

## Engagement Tools

### linkedin_create_reaction
React to a LinkedIn post.

**Parameters:**
- `postedId`: LinkedIn post URN
- `platformId`: Platform connection ID
- `reactionType`: One of the following:

| Type | Description |
|------|-------------|
| `LIKE` | Standard thumbs up |
| `PRAISE` | Clapping hands / applause |
| `EMPATHY` | Heart / love |
| `INTEREST` | Lightbulb / insightful |
| `APPRECIATION` | Supportive |
| `ENTERTAINMENT` | Funny / laughing |

### linkedin_delete_reaction
Remove your reaction from a post.

**Parameters:**
- `postedId`: LinkedIn post URN
- `platformId`: Platform connection ID

### linkedin_create_comment
Post a comment on a LinkedIn post (max 1,250 characters).

**Parameters:**
- `postedId`: LinkedIn post URN
- `platformId`: Platform connection ID
- `message`: Comment text (max 1,250 characters)
- `parentComment` (optional): Comment URN for nested replies

### linkedin_delete_comment
Remove a comment you made.

**Parameters:**
- `postedId`: LinkedIn post URN
- `commentId`: Comment URN or numeric ID
- `platformId`: Platform connection ID

## Example Prompts

### Weekly Performance Review
```
Analyze my LinkedIn performance for the last 7 days.
Show me:
1. Which posts performed best
2. My engagement rate trends
3. Follower growth
4. Recommendations for improvement
```

### Post Analysis
```
Get detailed stats for my last 5 LinkedIn posts and identify patterns in what content resonates with my audience.
```

### Engagement Campaign
```
React with PRAISE to my colleague's post about their promotion (urn:li:share:123456) and add a congratulatory comment.
```

### Follower Tracking
```
Show my LinkedIn follower growth for the last 30 days. How many new followers did I gain each week?
```

## Metrics Reference

| Metric | Description |
|--------|-------------|
| `IMPRESSION` | Total times content appeared in feeds |
| `MEMBERS_REACHED` | Unique LinkedIn members who saw the post |
| `RESHARE` | Number of reposts/shares |
| `REACTION` | Total reactions (all types combined) |
| `COMMENT` | Number of comments |

## Engagement Rate Benchmarks

**Average LinkedIn engagement rates by follower count:**

| Followers | Good Engagement Rate |
|-----------|---------------------|
| < 5K | 3-5% |
| 5K-50K | 2-3% |
| 50K+ | 1-2% |

**Good performing posts typically have:**
- 2x your average impressions
- Comment-to-reaction ratio above 10%
- Engagement rate above your baseline

## Important Notes

1. **Analytics delay**: LinkedIn analytics may take up to 24 hours to fully populate. Querying immediately after posting returns partial data.

2. **URN formats**: LinkedIn URLs use `urn:li:activity:xxx` but the API requires `urn:li:share:xxx` or `urn:li:ugcPost:xxx`. Use the `postedId` from Publora's `get_post` response for accurate URNs.

3. **Caching**: Analytics responses may be cached. The response includes a `cached` field indicating if data came from cache.

4. **Rate limits**: LinkedIn has approximately 200+ API calls per hour. Implement backoff on 429 errors.

## Troubleshooting

| Error | Cause | Solution |
|-------|-------|----------|
| "Platform ID not found" | Invalid connection ID | Run `list_connections` to get valid IDs |
| "Post not found" | Wrong URN format | Use `urn:li:share:` or `urn:li:ugcPost:` format |
| 429 Too Many Requests | Rate limited | Wait and retry with exponential backoff |
| "message cannot exceed 1250 characters" | Comment too long | Shorten comment to under 1,250 chars |

---

## Thread Engagement Tracking (compounding layer)

Самый ценный engagement-сигнал на LinkedIn — **личный ответ автора поста на твой коммент**. Не лайк, не репост — именно ответ. Он переводит тебя из «прохожего» в «коллегу», открывает DM, и его видят все, кто заходит в тред.

### Окно ответа автора — 6-24 часа

Эмпирически (замеры практиков LinkedIn): авторы отвечают на комменты **в окне 6-24 часа после публикации**. Раньше — пост ещё не набрал критическую массу. Позже — автор уже ушёл в следующий пост. Если отвечаешь автору, который ответил тебе → **тоже в этом окне** для максимума thread momentum.

### Daily report shape

```text
| Posted | Author        | Post           | Comment                      | Reply?           | Stage   | Action       |
|--------|---------------|----------------|------------------------------|------------------|---------|--------------|
| 18h    | Alex M.       | legaltech SaaS | "moat moved to taste"        | ✅ автор ответил | Warm    | Reply NOW    |
| 22h    | Dana R.       | CRM-вендор     | "integration depth moat"     | No               | Cold    | Skip         |
| 3h     | Priya S.      | retail-AI      | "twin economies"             | No               | Watch   | Check in 3h  |
```

**Stage decision:**
- `Watch` — <6h, ещё рано проверять
- `Warm` — 6-24h И автор ответил → срочно follow-up
- `Warm-no-reply` — 6-24h, автор не ответил → дополнительный коммент опасен (выглядит как push)
- `Cold` — >24h без ответа → закрыть, идти дальше

### Implementation sketch

Сейчас Publora `linkedin-post-statistics` возвращает count реакций/комментов, но **не парсит сам тред**. Чтобы вытащить, кто ответил на твой коммент, нужно идти через ScrapeCreators (есть в твоём `linkedin` скилле):

```bash
# Список комментариев под постом, с авторами
curl -s "https://api.scrapecreators.com/v1/linkedin/post-comments?url=<POST_URL>" \
  -H "x-api-key: $SCRAPECREATORS_API_KEY" | python3 -m json.tool
```

В ответе для каждого коммента есть `replies[]`. Для своих комментов проверяешь, есть ли в `replies[].author.urn` URN автора поста — если да, это «author replied» сигнал.

### Готовый скилл — `linkedin-thread-engagement`

Полная реализация в `~/.claude/skills/linkedin-comment-drafter/references/linkedin-thread-engagement/SKILL.md` с:
- Daily monitoring всех твоих недавних комментов
- Авто-классификация по стадиям (Watch/Warm/Cold)
- Драфт follow-up reply через `linkedin-reply-handler` (с правильным top-level `parentComment` URN при 2-level flattening)
- Routing к DM при «автор-открыл-беседу» сигнале

### Метрики качества thread engagement (а не просто посты)

| Метрика | Что считать | Хорошее значение |
|---|---|---|
| Author reply rate | (комменты с ответом автора) / (всего комментов) | >15% |
| Author follow rate | (новые подписки от авторов) / (комменты с ответом) | >30% |
| DM-from-thread rate | (DM от автора в течение 7 дней) / (warm-stage комменты) | 5-10% |
| Avg time-to-reply | Median ч от твоего коммента до ответа автора | <12h |

Если author reply rate <5% → коммент-стратегия не работает (банальные takes, поздно зашёл, ICP не совпадает). См. `linkedin-comment-drafter/references/comment-templates.md` за паттернами «first-commenter / data-first / answer-the-closing-question / quotable-reframe».