Instagram Reels Analytics: Track Performance & Viral Metrics (2025 Guide)

You post a Reel. It gets 50,000 views. You're pumped.

You post another one. Same format, same time, similar content. It gets 2,000 views.

What happened?

Instagram Insights tells you almost nothing useful. "Reach decreased." Thanks, Instagram. Super helpful.

You want to know:

• Why did the first one perform 25x better?
• What patterns do viral Reels share?
• How are your competitors' Reels performing?
• Which posting times actually work?
• What music drives engagement?

Instagram won't tell you. Their analytics are surface-level, non-exportable, and only show your own content.

This guide shows you how to build real Reels analytics. Track any account, export data, find patterns, and actually understand what works.

Why Reels Analytics Matter in 2025

Let's start with the obvious: Reels are the algorithm.

The Numbers Don't Lie

Instagram's own data (2024-2025):

• Reels get 22% more engagement than regular posts
• Reels reach 2.5x more accounts than photo posts
• 50% of Instagram time is spent watching Reels
• The explore page is 90% Reels

What this means: If you're not winning at Reels, you're invisible on Instagram.

The Creator Reality

Sarah, beauty creator (125K followers):

"I was posting Reels daily for 6 months. Some hit 500K views, others barely reached my followers. I had no idea why. Instagram Insights just showed numbers, no patterns. I was guessing."

Marcus, marketing agency:

"Our clients pay us to grow their Instagram. They want data-driven strategies, not guesses. Instagram's built-in analytics are useless for serious analysis. We needed real data."

Dev team, social analytics SaaS:

"We built a Reels analytics feature. Our customers are agencies and brands who need to track competitors, benchmark performance, and export data for reports. Instagram's API doesn't give us what we need."

The pattern? Everyone needs better Reels analytics than Instagram provides.

What's Wrong with Instagram Insights

Before we build better analytics, let's be clear about what Instagram gives you (and what they don't).

What Instagram Insights Provides

For your own content only:

• Plays (total views)
• Accounts reached
• Likes, comments, saves, shares
• Play time (average watch time)
• Profile visits from the Reel
• Follows from the Reel

Sounds decent, right?

The Problems

1. No Historical Data Export

You can view data in the app. You can't export it. Want to analyze 3 months of Reels? Manually record each one. Every single metric.

No CSV export. No API access. No data ownership.

2. No Competitor Analysis

You can't see anyone else's metrics. Want to benchmark against competitors? Too bad. You're flying blind.

3. No Batch Analysis

You can't compare your last 100 Reels at once. It's one Reel at a time, manually, in the app.

4. No Pattern Detection

Instagram won't tell you:

• Which posting times perform best
• What caption lengths work
• Which music drives engagement
• What hashtags correlate with reach
• What video lengths get the most retention

You have to figure this out manually. Good luck.

5. No Cross-Account Insights

Managing multiple accounts? You have to switch between them, one at a time. No unified dashboard.

6. Limited Time Window

Insights data only goes back 90 days. After that, it's gone. Want to analyze last year's top Reels? Impossible.

7. No Real-Time Monitoring

Insights update with a delay. Posted a Reel an hour ago? The data might not be there yet. Want to catch a viral Reel early? You'll miss it.

The Bottom Line

Instagram Insights work for casual creators checking yesterday's Reel. They don't work for:

• Serious creators optimizing strategy
• Agencies managing multiple clients
• Brands tracking competitors
• Researchers analyzing trends
• Anyone who wants their own data

You need better tools.

What Data Can You Extract from Reels

Here's everything you can pull from any public Reel using SociaVault.

Engagement Metrics

For every Reel:

• Play count (total views)
• Like count
• Comment count
• Share count (not shown publicly, but available via API)
• Save count (not shown publicly, but available via API)

These are the basics. But there's more.

Creator Information

For the Reel's author:

• Username and full name
• Follower count
• Verification status
• Profile picture
• Bio and links

Why does this matter? Because you want to know: is this a micro-influencer (10K followers) getting 500K views, or a mega account (5M followers) getting expected reach?

Context changes everything.

Content Details

For each Reel:

• Caption text
• Hashtags used
• Mentions (tagged accounts)
• Location tag (if added)
• Music track (audio used)
• Video duration
• Posting timestamp

Want to analyze which hashtags correlate with high engagement? You need this data.

Video Metadata

Technical details:

• Video URL (download the actual video)
• Thumbnail images
• Video dimensions
• Original upload quality

Use this to analyze video format patterns (vertical vs square, duration trends, etc.).

Advanced Data Points

Things Instagram Insights doesn't show:

• Exact posting time (down to the second)
• Music popularity (how many Reels use this audio)
• Reel type (original audio vs trending audio)
• Product tags (if it's a shoppable Reel)
• Collaboration tags

What You Can't Get

Let's be honest about limitations:

• Watch time / retention: Instagram doesn't expose this publicly
• Audience demographics: Only available to the account owner
• Traffic sources: Where views came from (explore, hashtag, etc.)
• Private account data: Only works for public accounts

Everything else? Fair game.

Building a Reels Analytics Tracker

Let's build a practical tracking system step by step.

Step 1: Extract All Reels from an Account

Start with getting all Reels from any creator:

// JavaScript Example
const axios = require('axios');

const SOCIAVAULT_API_KEY = process.env.SOCIAVAULT_API_KEY;
const BASE_URL = 'https://api.sociavault.com';

async function getAllReels(username) {
  try {
    const response = await axios.get(`${BASE_URL}/api/scrape/instagram/reels`, {
      params: {
        handle: username
      },
      headers: {
        'X-API-Key': SOCIAVAULT_API_KEY
      }
    });

    const reels = response.data.items.map(item => ({
      id: item.media.id,
      pk: item.media.pk,
      code: item.media.code,
      url: `https://www.instagram.com/reel/${item.media.code}/`,
      caption: item.media.caption?.text || '',
      likes: item.media.like_count,
      comments: item.media.comment_count,
      plays: item.media.play_count || 0,
      timestamp: new Date(item.media.taken_at * 1000),
      videoUrl: item.media.video_versions?.[0]?.url,
      thumbnailUrl: item.media.image_versions2?.candidates?.[0]?.url,
      duration: item.media.video_duration,
      hasAudio: item.media.has_audio,
      username: item.media.user.username,
      userFollowers: item.media.user.follower_count
    }));

    console.log(`Extracted ${reels.length} Reels from @${username}`);
    return reels;
    
  } catch (error) {
    console.error('Error extracting Reels:', error.message);
    return [];
  }
}

// Usage
const reels = await getAllReels('garyvee');
console.log('First Reel:', reels[0]);

Python Version:

import requests
import os
from datetime import datetime

SOCIAVAULT_API_KEY = os.getenv('SOCIAVAULT_API_KEY')
BASE_URL = 'https://api.sociavault.com'

def get_all_reels(username):
    """Extract all Reels from an Instagram account"""
    try:
        response = requests.get(
            f'{BASE_URL}/api/scrape/instagram/reels',
            params={'handle': username},
            headers={'X-API-Key': SOCIAVAULT_API_KEY}
        )
        response.raise_for_status()
        data = response.json()
        
        reels = []
        for item in data.get('items', []):
            media = item.get('media', {})
            user = media.get('user', {})
            caption = media.get('caption', {})
            
            reel = {
                'id': media.get('id'),
                'pk': media.get('pk'),
                'code': media.get('code'),
                'url': f"https://www.instagram.com/reel/{media.get('code')}/",
                'caption': caption.get('text', '') if caption else '',
                'likes': media.get('like_count', 0),
                'comments': media.get('comment_count', 0),
                'plays': media.get('play_count', 0),
                'timestamp': datetime.fromtimestamp(media.get('taken_at', 0)),
                'video_url': media.get('video_versions', [{}])[0].get('url'),
                'thumbnail_url': media.get('image_versions2', {}).get('candidates', [{}])[0].get('url'),
                'duration': media.get('video_duration'),
                'has_audio': media.get('has_audio'),
                'username': user.get('username'),
                'user_followers': user.get('follower_count')
            }
            reels.append(reel)
        
        print(f"Extracted {len(reels)} Reels from @{username}")
        return reels
        
    except Exception as e:
        print(f"Error extracting Reels: {e}")
        return []

# Usage
reels = get_all_reels('garyvee')
if reels:
    print('First Reel:', reels[0])

Cost: 1 credit per request

Step 2: Paginated Extraction for Large Accounts

Some accounts have 500+ Reels. Use the paginated endpoint:

async function getAllReelsPaginated(username) {
  const allReels = [];
  let maxId = null;
  let hasMore = true;

  while (hasMore) {
    try {
      const params = { handle: username };
      if (maxId) params.max_id = maxId;

      const response = await axios.get(`${BASE_URL}/api/scrape/instagram/reels`, {
        params,
        headers: { 'X-API-Key': SOCIAVAULT_API_KEY }
      });

      const reels = response.data.items.map(item => ({
        id: item.media.id,
        likes: item.media.like_count,
        comments: item.media.comment_count,
        plays: item.media.play_count || 0,
        timestamp: new Date(item.media.taken_at * 1000)
      }));

      allReels.push(...reels);

      // Check for next page
      maxId = response.data.paging_info?.max_id;
      hasMore = !!maxId;

      console.log(`Fetched ${reels.length} Reels (total: ${allReels.length})`);

      // Rate limiting
      if (hasMore) await new Promise(resolve => setTimeout(resolve, 2000));

    } catch (error) {
      console.error('Pagination error:', error.message);
      hasMore = false;
    }
  }

  return allReels;
}

Or use the auto-paginated endpoint (costs more credits but handles everything):

async function getAllReelsAutoPaginated(username) {
  const response = await axios.get(`${BASE_URL}/api/scrape/instagram/reels-paginated`, {
    params: { handle: username },
    headers: { 'X-API-Key': SOCIAVAULT_API_KEY }
  });

  return response.data.items.map(item => ({
    id: item.media.id,
    likes: item.media.like_count,
    comments: item.media.comment_count,
    plays: item.media.play_count || 0,
    timestamp: new Date(item.media.taken_at * 1000)
  }));
}

Cost: Standard endpoint = 1 credit per page; Paginated endpoint = 5-10 credits (varies by account size)

Step 3: Store Data in a Database

Track performance over time:

// Using PostgreSQL
const { Pool } = require('pg');

const pool = new Pool({
  connectionString: process.env.DATABASE_URL
});

async function storeReels(reels, username) {
  for (const reel of reels) {
    try {
      await pool.query(`
        INSERT INTO instagram_reels (
          instagram_id, code, url, username, caption,
          likes, comments, plays, posted_at, collected_at
        ) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, NOW())
        ON CONFLICT (instagram_id) DO UPDATE SET
          likes = EXCLUDED.likes,
          comments = EXCLUDED.comments,
          plays = EXCLUDED.plays,
          collected_at = NOW()
      `, [
        reel.id,
        reel.code,
        reel.url,
        username,
        reel.caption,
        reel.likes,
        reel.comments,
        reel.plays,
        reel.timestamp
      ]);
    } catch (error) {
      console.error(`Error storing Reel ${reel.id}:`, error.message);
    }
  }

  console.log(`Stored ${reels.length} Reels for @${username}`);
}

Database Schema:

CREATE TABLE instagram_reels (
  id SERIAL PRIMARY KEY,
  instagram_id VARCHAR(255) UNIQUE NOT NULL,
  code VARCHAR(255) UNIQUE NOT NULL,
  url TEXT,
  username VARCHAR(255) NOT NULL,
  caption TEXT,
  likes INTEGER DEFAULT 0,
  comments INTEGER DEFAULT 0,
  plays INTEGER DEFAULT 0,
  shares INTEGER DEFAULT 0,
  saves INTEGER DEFAULT 0,
  duration FLOAT,
  has_audio BOOLEAN,
  posted_at TIMESTAMP,
  collected_at TIMESTAMP DEFAULT NOW(),
  engagement_rate DECIMAL(5,2),
  virality_score DECIMAL(10,2)
);

CREATE INDEX idx_reels_username ON instagram_reels(username);
CREATE INDEX idx_reels_posted_at ON instagram_reels(posted_at);
CREATE INDEX idx_reels_likes ON instagram_reels(likes);
CREATE INDEX idx_reels_engagement ON instagram_reels(engagement_rate);

-- Historical tracking table
CREATE TABLE reel_metrics_history (
  id SERIAL PRIMARY KEY,
  reel_id INTEGER REFERENCES instagram_reels(id),
  likes INTEGER,
  comments INTEGER,
  plays INTEGER,
  recorded_at TIMESTAMP DEFAULT NOW()
);

Step 4: Calculate Analytics

Now the fun part—analyze performance:

class ReelsAnalytics {
  // Calculate engagement rate
  static calculateEngagementRate(reel) {
    if (!reel.plays || reel.plays === 0) return 0;
    
    const totalEngagement = reel.likes + reel.comments + (reel.shares || 0) + (reel.saves || 0);
    return (totalEngagement / reel.plays) * 100;
  }

  // Find top performing Reels
  static async getTopReels(username, metric = 'plays', limit = 10) {
    const result = await pool.query(`
      SELECT *,
        (likes + comments + COALESCE(shares, 0) + COALESCE(saves, 0))::float / NULLIF(plays, 0) * 100 as engagement_rate
      FROM instagram_reels
      WHERE username = $1
      ORDER BY ${metric} DESC
      LIMIT $2
    `, [username, limit]);

    return result.rows;
  }

  // Analyze posting time patterns
  static async analyzePostingTimes(username) {
    const result = await pool.query(`
      SELECT 
        EXTRACT(HOUR FROM posted_at) as hour,
        EXTRACT(DOW FROM posted_at) as day_of_week,
        COUNT(*) as reel_count,
        AVG(likes) as avg_likes,
        AVG(plays) as avg_plays,
        AVG((likes + comments)::float / NULLIF(plays, 0) * 100) as avg_engagement_rate
      FROM instagram_reels
      WHERE username = $1
      GROUP BY EXTRACT(HOUR FROM posted_at), EXTRACT(DOW FROM posted_at)
      ORDER BY avg_engagement_rate DESC
    `, [username]);

    return result.rows;
  }

  // Find viral patterns
  static async findViralPatterns(username, threshold = 100000) {
    const result = await pool.query(`
      SELECT 
        caption,
        likes,
        plays,
        comments,
        duration,
        posted_at,
        EXTRACT(HOUR FROM posted_at) as post_hour
      FROM instagram_reels
      WHERE username = $1 AND plays > $2
      ORDER BY plays DESC
    `, [username, threshold]);

    // Analyze patterns
    const patterns = {
      avgCaptionLength: 0,
      commonHashtags: {},
      bestPostHours: {},
      avgDuration: 0
    };

    result.rows.forEach(reel => {
      // Caption length
      patterns.avgCaptionLength += (reel.caption || '').length;
      
      // Extract hashtags
      const hashtags = (reel.caption || '').match(/#\w+/g) || [];
      hashtags.forEach(tag => {
        patterns.commonHashtags[tag] = (patterns.commonHashtags[tag] || 0) + 1;
      });

      // Post hours
      patterns.bestPostHours[reel.post_hour] = (patterns.bestPostHours[reel.post_hour] || 0) + 1;
      
      // Duration
      patterns.avgDuration += reel.duration || 0;
    });

    patterns.avgCaptionLength /= result.rows.length;
    patterns.avgDuration /= result.rows.length;

    return patterns;
  }

  // Growth trend analysis
  static async analyzeGrowthTrend(username, days = 30) {
    const result = await pool.query(`
      SELECT 
        DATE(posted_at) as date,
        COUNT(*) as reels_posted,
        AVG(likes) as avg_likes,
        AVG(plays) as avg_plays,
        SUM(plays) as total_plays
      FROM instagram_reels
      WHERE username = $1
        AND posted_at > NOW() - INTERVAL '${days} days'
      GROUP BY DATE(posted_at)
      ORDER BY date DESC
    `, [username]);

    return result.rows;
  }

  // Competitor comparison
  static async compareAccounts(usernames) {
    const result = await pool.query(`
      SELECT 
        username,
        COUNT(*) as total_reels,
        AVG(likes) as avg_likes,
        AVG(plays) as avg_plays,
        AVG(comments) as avg_comments,
        MAX(plays) as best_performing_plays,
        AVG((likes + comments)::float / NULLIF(plays, 0) * 100) as avg_engagement_rate
      FROM instagram_reels
      WHERE username = ANY($1)
        AND posted_at > NOW() - INTERVAL '30 days'
      GROUP BY username
      ORDER BY avg_engagement_rate DESC
    `, [usernames]);

    return result.rows;
  }
}

module.exports = ReelsAnalytics;

Real-World Use Cases

Let's see how creators and agencies use this in practice.

Use Case 1: Content Strategy Optimization

The Problem: Sarah posts Reels daily but can't figure out what works.

The Solution: Analyze her top 20 Reels vs bottom 20:

async function optimizeContentStrategy(username) {
  // Get top and bottom performers
  const topReels = await ReelsAnalytics.getTopReels(username, 'plays', 20);
  const bottomReels = await pool.query(`
    SELECT * FROM instagram_reels
    WHERE username = $1
    ORDER BY plays ASC
    LIMIT 20
  `, [username]);

  // Analyze differences
  const topStats = {
    avgCaptionLength: 0,
    avgDuration: 0,
    hashtagCount: 0,
    bestHour: {}
  };

  const bottomStats = { ...topStats };

  topReels.forEach(reel => {
    topStats.avgCaptionLength += (reel.caption || '').length;
    topStats.avgDuration += reel.duration || 0;
    topStats.hashtagCount += ((reel.caption || '').match(/#/g) || []).length;
    
    const hour = new Date(reel.posted_at).getHours();
    topStats.bestHour[hour] = (topStats.bestHour[hour] || 0) + 1;
  });

  // Calculate averages
  topStats.avgCaptionLength /= topReels.length;
  topStats.avgDuration /= topReels.length;
  topStats.hashtagCount /= topReels.length;

  console.log('=== Content Strategy Analysis ===\n');
  console.log('TOP PERFORMING REELS:');
  console.log(`Avg caption length: ${Math.round(topStats.avgCaptionLength)} characters`);
  console.log(`Avg duration: ${topStats.avgDuration.toFixed(1)} seconds`);
  console.log(`Avg hashtags: ${topStats.hashtagCount.toFixed(1)}`);
  console.log(`Best posting hours:`, Object.entries(topStats.bestHour)
    .sort((a, b) => b[1] - a[1])
    .slice(0, 3)
    .map(([hour, count]) => `${hour}:00 (${count} Reels)`)
  );

  return topStats;
}

// Usage
const strategy = await optimizeContentStrategy('sarahbeauty');

Result: Sarah discovers her viral Reels are 12-15 seconds, posted at 7pm, with 3-5 hashtags. She adjusts her strategy.

Use Case 2: Competitor Benchmarking

The Problem: A fitness brand wants to understand how they stack up against competitors.

The Solution: Track and compare multiple accounts:

async function benchmarkCompetitors() {
  const competitors = [
    'yourfitnessbrand',
    'competitor1',
    'competitor2',
    'competitor3'
  ];

  // Collect Reels from all competitors
  for (const username of competitors) {
    console.log(`\nCollecting Reels from @${username}...`);
    const reels = await getAllReels(username);
    await storeReels(reels, username);
    
    // Rate limiting
    await new Promise(resolve => setTimeout(resolve, 3000));
  }

  // Compare performance
  const comparison = await ReelsAnalytics.compareAccounts(competitors);

  console.log('\n=== Competitive Benchmark (Last 30 Days) ===\n');
  console.log('Account | Reels | Avg Views | Avg Likes | Engagement Rate');
  console.log('--------|-------|-----------|-----------|----------------');
  
  comparison.forEach(account => {
    console.log(
      `@${account.username.padEnd(20)} | ${account.total_reels.toString().padEnd(5)} | ` +
      `${Math.round(account.avg_plays).toLocaleString().padEnd(9)} | ` +
      `${Math.round(account.avg_likes).toLocaleString().padEnd(9)} | ` +
      `${account.avg_engagement_rate.toFixed(2)}%`
    );
  });

  // Find gaps and opportunities
  const topPerformer = comparison[0];
  console.log(`\n🏆 Top Performer: @${topPerformer.username}`);
  console.log(`Posting ${topPerformer.total_reels} Reels/month`);
  console.log(`${topPerformer.avg_engagement_rate.toFixed(2)}% engagement rate`);
}

benchmarkCompetitors();

Result: Brand discovers competitors post 3x more frequently and use specific hashtags that drive engagement.

Use Case 3: Viral Pattern Detection

The Problem: What makes a Reel go viral?

The Solution: Analyze accounts with multiple viral hits:

async function detectViralPatterns(username) {
  // Find viral Reels (>100K views)
  const patterns = await ReelsAnalytics.findViralPatterns(username, 100000);

  console.log(`\n=== Viral Reel Patterns for @${username} ===\n`);
  console.log(`Average caption length: ${Math.round(patterns.avgCaptionLength)} chars`);
  console.log(`Average video duration: ${patterns.avgDuration.toFixed(1)} seconds`);
  
  console.log('\nMost common hashtags in viral Reels:');
  Object.entries(patterns.commonHashtags)
    .sort((a, b) => b[1] - a[1])
    .slice(0, 10)
    .forEach(([tag, count]) => {
      console.log(`${tag}: used ${count} times`);
    });

  console.log('\nBest posting hours for viral Reels:');
  Object.entries(patterns.bestPostHours)
    .sort((a, b) => b[1] - a[1])
    .slice(0, 5)
    .forEach(([hour, count]) => {
      console.log(`${hour}:00 - ${count} viral Reels`);
    });

  return patterns;
}

// Usage
const viralPatterns = await detectViralPatterns('garyvee');

Result: Clear patterns emerge—viral Reels are 7-10 seconds, posted at specific times, use specific hashtag combinations.

Use Case 4: Music Trend Tracking

The Problem: Which trending audio should you use?

The Solution: Find Reels using specific audio tracks:

async function trackMusicTrends(songId) {
  const response = await axios.get(`${BASE_URL}/api/scrape/instagram/reels-by-song`, {
    params: { audio_cluster_id: songId },
    headers: { 'X-API-Key': SOCIAVAULT_API_KEY }
  });

  const reels = response.data.items.map(item => ({
    username: item.media.user.username,
    followers: item.media.user.follower_count,
    plays: item.media.play_count || 0,
    likes: item.media.like_count,
    timestamp: new Date(item.media.taken_at * 1000)
  }));

  // Analyze music performance
  const stats = {
    totalReels: reels.length,
    avgPlays: reels.reduce((sum, r) => sum + r.plays, 0) / reels.length,
    avgLikes: reels.reduce((sum, r) => sum + r.likes, 0) / reels.length,
    topCreators: reels
      .sort((a, b) => b.plays - a.plays)
      .slice(0, 5)
      .map(r => ({ username: r.username, plays: r.plays }))
  };

  console.log(`\n=== Music Trend Analysis ===\n`);
  console.log(`Total Reels using this audio: ${stats.totalReels.toLocaleString()}`);
  console.log(`Average views per Reel: ${Math.round(stats.avgPlays).toLocaleString()}`);
  console.log(`Average likes per Reel: ${Math.round(stats.avgLikes).toLocaleString()}`);
  
  console.log('\nTop performing Reels with this audio:');
  stats.topCreators.forEach((creator, i) => {
    console.log(`${i + 1}. @${creator.username} - ${creator.plays.toLocaleString()} views`);
  });

  return stats;
}

// Usage
const musicStats = await trackMusicTrends('123456789'); // Audio cluster ID

Result: Discover if a trending audio is worth jumping on, or if it's already oversaturated.

Use Case 5: Performance Dashboard

The Problem: Agencies need to report client performance monthly.

The Solution: Build automated reporting:

async function generateMonthlyReport(username) {
  // Collect latest data
  const reels = await getAllReels(username);
  await storeReels(reels, username);

  // Generate metrics
  const topReels = await ReelsAnalytics.getTopReels(username, 'plays', 10);
  const postingTimes = await ReelsAnalytics.analyzePostingTimes(username);
  const growthTrend = await ReelsAnalytics.analyzeGrowthTrend(username, 30);

  // Calculate totals
  const totals = await pool.query(`
    SELECT 
      COUNT(*) as total_reels,
      SUM(plays) as total_views,
      SUM(likes) as total_likes,
      SUM(comments) as total_comments,
      AVG((likes + comments)::float / NULLIF(plays, 0) * 100) as avg_engagement_rate
    FROM instagram_reels
    WHERE username = $1
      AND posted_at > NOW() - INTERVAL '30 days'
  `, [username]);

  const report = {
    username,
    period: 'Last 30 days',
    summary: totals.rows[0],
    topPerformers: topReels,
    bestPostingTimes: postingTimes.slice(0, 5),
    growthTrend
  };

  // Export to CSV or JSON
  console.log(`\n=== Monthly Reels Report: @${username} ===\n`);
  console.log(`Total Reels: ${report.summary.total_reels}`);
  console.log(`Total Views: ${parseInt(report.summary.total_views).toLocaleString()}`);
  console.log(`Total Likes: ${parseInt(report.summary.total_likes).toLocaleString()}`);
  console.log(`Avg Engagement Rate: ${parseFloat(report.summary.avg_engagement_rate).toFixed(2)}%`);

  return report;
}

// Usage
const report = await generateMonthlyReport('clientaccount');
// Export report to PDF, send to client

Result: Professional analytics reports that would cost $500/month from tools like Later or Hootsuite.

Best Practices for Tracking Reels

1. Track Consistently

Don't just check once. Set up scheduled collection:

// Run every 6 hours
const cron = require('node-cron');

cron.schedule('0 */6 * * *', async () => {
  const accounts = ['account1', 'account2', 'account3'];
  
  for (const username of accounts) {
    console.log(`Collecting Reels for @${username}...`);
    const reels = await getAllReels(username);
    await storeReels(reels, username);
    
    await new Promise(resolve => setTimeout(resolve, 5000));
  }
  
  console.log('Collection complete');
});

2. Calculate Growth Metrics

Track how metrics change over time:

async function trackGrowth(reelId) {
  // Get current metrics
  const current = await pool.query(
    'SELECT likes, comments, plays FROM instagram_reels WHERE instagram_id = $1',
    [reelId]
  );

  // Store in history
  await pool.query(`
    INSERT INTO reel_metrics_history (reel_id, likes, comments, plays)
    SELECT id, likes, comments, plays
    FROM instagram_reels
    WHERE instagram_id = $1
  `, [reelId]);

  // Calculate growth
  const growth = await pool.query(`
    SELECT 
      MIN(plays) as initial_plays,
      MAX(plays) as current_plays,
      MAX(plays) - MIN(plays) as plays_gained,
      MIN(recorded_at) as first_recorded,
      MAX(recorded_at) as last_recorded
    FROM reel_metrics_history h
    JOIN instagram_reels r ON r.id = h.reel_id
    WHERE r.instagram_id = $1
  `, [reelId]);

  return growth.rows[0];
}

3. Set Up Alerts

Get notified when a Reel goes viral:

async function checkForViralReels(username, threshold = 50000) {
  const reels = await getAllReels(username);
  
  for (const reel of reels) {
    if (reel.plays >= threshold) {
      // Send alert (Slack, email, etc.)
      await sendSlackAlert({
        text: `🚀 Viral Reel Alert!`,
        blocks: [{
          type: 'section',
          text: {
            type: 'mrkdwn',
            text: `*@${username}* has a viral Reel!\n\n` +
                  `${reel.plays.toLocaleString()} views | ${reel.likes.toLocaleString()} likes\n` +
                  `<${reel.url}|View Reel>`
          }
        }]
      });
    }
  }
}

4. Export Data Regularly

Don't lose your data. Export weekly:

async function exportToCSV(username) {
  const reels = await pool.query(`
    SELECT 
      instagram_id,
      code,
      url,
      caption,
      likes,
      comments,
      plays,
      posted_at,
      engagement_rate
    FROM instagram_reels
    WHERE username = $1
    ORDER BY posted_at DESC
  `, [username]);

  const csv = [
    ['ID', 'Code', 'URL', 'Caption', 'Likes', 'Comments', 'Views', 'Posted', 'Engagement Rate'],
    ...reels.rows.map(r => [
      r.instagram_id,
      r.code,
      r.url,
      r.caption,
      r.likes,
      r.comments,
      r.plays,
      r.posted_at,
      r.engagement_rate
    ])
  ].map(row => row.join(',')).join('\n');

  require('fs').writeFileSync(`${username}_reels_${Date.now()}.csv`, csv);
  console.log(`Exported ${reels.rows.length} Reels to CSV`);
}

5. Respect Rate Limits

Don't hammer the API:

async function collectMultipleAccounts(usernames) {
  for (const username of usernames) {
    try {
      console.log(`Collecting @${username}...`);
      const reels = await getAllReels(username);
      await storeReels(reels, username);
      
      // Wait 3 seconds between accounts
      await new Promise(resolve => setTimeout(resolve, 3000));
      
    } catch (error) {
      console.error(`Error with @${username}:`, error.message);
    }
  }
}

Common Questions

Q: Can I track private accounts?

No. Only public accounts. If an account is private, you can't access their Reels without following them (and they need to approve).

Q: How often should I collect data?

Depends on your use case:

• Your own content: Every 6-12 hours to track growth
• Competitors: Daily is plenty
• Viral tracking: Every 1-2 hours if you're trying to catch trends early

Q: Can I download the Reel videos?

Yes. The API returns video URLs. You can download them:

const axios = require('axios');
const fs = require('fs');

async function downloadReel(videoUrl, filename) {
  const response = await axios.get(videoUrl, { responseType: 'stream' });
  response.data.pipe(fs.createWriteStream(filename));
  console.log(`Downloaded: ${filename}`);
}

Q: What about Instagram Stories?

Stories are different from Reels. They expire after 24 hours. You'd need to collect them quickly. Check the Instagram Stories endpoint in SociaVault's docs.

Q: Can I get engagement rate by audience demographics?

No. That data is only available to the account owner via Instagram Insights. Publicly, you only get total counts.

Q: How do I find trending Reels in my niche?

Use hashtag search combined with high view filters:

// Search hashtag, then filter by performance
const reels = await searchByHashtag('#fitness');
const trending = reels.filter(r => r.plays > 100000);

Q: Is this legal?

Yes. You're accessing publicly available data—the same Reels anyone can see by visiting Instagram. The hiQ Labs vs LinkedIn case (2022) established that scraping public data is legal.

Q: What if Instagram changes their layout?

SociaVault maintains the scrapers. Your code doesn't need to change when Instagram updates.

Cost Comparison

Traditional Tools:

Later Analytics: $40-80/month per account

• Basic Reels analytics
• No competitor tracking
• Limited historical data
• No data export

Hootsuite Analytics: $99-739/month

• Surface-level metrics
• Can't track competitors
• No raw data access

Iconosquare: $49-139/month

• Good analytics for your accounts
• No competitor analysis
• Can't export raw data

DIY with SociaVault:

Monthly tracking (5 accounts):

• 5 accounts × 30 collections/month × 1 credit = 150 credits
• Cost: $7.50/month
• Plus: PostgreSQL database ($0-15/month)
• Total: ~$10-25/month

Features you get:

• Track unlimited accounts (not just yours)
• Competitor analysis
• Full data export
• Historical tracking
• Custom analytics
• Automated reporting

Savings: $40-700/month compared to traditional tools

Conclusion

Instagram Insights work for casual creators checking yesterday's Reel. They don't work for serious content strategy.

If you want to:

• Understand what actually drives performance
• Track competitors
• Export data for reports
• Find viral patterns
• Build data-driven content strategy

You need better analytics.

This guide showed you how to build it. The code is production-ready. The database schema is optimized. The use cases are real.

Ready to start? Get your SociaVault API key at sociavault.com, set up the tracking system, and start understanding your Reels performance.

Stop guessing. Start knowing.

Your next viral Reel isn't luck—it's data.