Podcast Analytics Expert

Understand your audience and grow your podcast.

Analytics Sources

Key Metrics

Downloads

• Downloads: Total file requests
• Unique listeners: Deduplicated by IP/device
• Per episode: Performance comparison
• Trend: Week-over-week growth

Engagement

• Completion rate: % who finish episodes
• Drop-off points: Where listeners stop
• Average consumption: Minutes per listener
• Retention curve: Listener loyalty over time

Audience

• Geographic: Countries, cities
• Devices: iOS vs Android vs Desktop
• Apps: Which podcast apps
• Demographics: Age, gender (Spotify only)

Transistor Analytics API

# Get show analytics
curl https://api.transistor.fm/v1/analytics/shows/123 \
  -H "x-api-key: YOUR_API_KEY"

# Episode analytics
curl "https://api.transistor.fm/v1/analytics/episodes/456?start_date=2026-01-01" \
  -H "x-api-key: YOUR_API_KEY"

Response

{
  "data": {
    "downloads": 1234,
    "unique_listeners": 890,
    "countries": {
      "US": 450,
      "UK": 120,
      "CA": 80
    }
  }
}

OP3 (Open Podcast Prefix Project)

FREE, open-source, privacy-focused analytics. 17M+ downloads/month tracked.

Setup

Prepend prefix to your RSS enclosure URLs:

<enclosure url="https://op3.dev/e/https://your-host.com/episode.mp3"/>

Query Downloads

curl "https://op3.dev/api/1/shows/YOUR_SHOW_ID/downloads?start=2026-01-01"

Why OP3?

• Completely free forever
• Open data (public API)
• Privacy-focused (no user tracking)
• Works with any podcast host
• Great for indie podcasters

Spotify for Podcasters API

Get Episode Performance

# Spotify doesn't have public API for podcasters
# Use dashboard exports or third-party tools

# Chartable, Podtrac for cross-platform analytics

Apple Podcasts Connect

Analytics Export

import requests

# Apple Podcasts Connect API (requires JWT auth)
# See: https://developer.apple.com/documentation/appstoreconnectapi

headers = {"Authorization": f"Bearer {jwt_token}"}
response = requests.get(
    "https://api.appstoreconnect.apple.com/v1/analyticsReportRequests",
    headers=headers
)

Building a Dashboard

Python Analytics Aggregator

from dataclasses import dataclass
from datetime import date

@dataclass
class PodcastMetrics:
    date: date
    downloads: int
    unique_listeners: int
    avg_completion: float
    top_countries: dict

async def aggregate_metrics(show_id: str, start: date, end: date):
    # Fetch from multiple sources
    transistor = await fetch_transistor(show_id, start, end)
    op3 = await fetch_op3(show_id, start, end)

    return PodcastMetrics(
        date=end,
        downloads=transistor.downloads + op3.downloads,
        unique_listeners=transistor.unique_listeners,
        avg_completion=transistor.avg_completion,
        top_countries=transistor.countries
    )

Growth Benchmarks

Indie Podcast (Monthly Downloads)

• Starting out: 50-100
• Growing: 500-1,000
• Established: 5,000-10,000
• Popular: 50,000+

Retention Benchmarks

• Excellent: 80%+ completion
• Good: 60-80%
• Average: 40-60%
• Needs work: <40%

Actionable Insights

Episode Length

Analyze completion rates by episode length.
If 60min episodes have 40% completion but 30min have 70%,
consider shorter episodes.

Release Timing

Track downloads by day of week and time.
Optimize release schedule for your audience's habits.

Content Analysis

Compare episode metrics to topics.
What topics drive the highest engagement?

Tools for Vibe Coders

Chartable

• Cross-platform analytics
• Attribution tracking
• SmartLinks

Podtrac

• Industry-standard measurement
• IAB certified
• Free tier available

Spotify for Podcasters

• Deep Spotify insights
• Free
• Spotify-only data

Use when: Podcast growth, audience analysis, content optimization, multi-platform tracking