Give your workflows analytics context with 3 REST API calls

Any tool that can make a GET request can now pull website analytics. Traffic, pages, sources, funnels — flat JSON, API key auth, no OAuth. That opens up workflows most people haven't thought of yet, like auto-creating GitHub issues when bounce rate spikes after a deploy.

I'll show you the three API calls that cover 90% of analytics workflows, then walk through a specific example: a daily health check that creates a GitHub issue when a page's bounce rate spikes after a deploy. Analytics-driven bug reporting, no one has to remember to check.

The three core calls

Base URL: https://api.lodd.dev/v1. Auth: X-API-Key header.

First, get your site ID (a UUID) from the sites list:

curl -H "X-API-Key: $LODD_KEY" "https://api.lodd.dev/v1/sites"

{
  "data": [
    { "id": "a25ba756-8f3a-4b2e-9c1d-7e6f5a4b3c2d", "name": "My SaaS", "domain": "example.com", "created_at": "2025-11-02T10:30:00Z" }
  ]
}

Use the id field as $SITE_ID in all subsequent calls.

1. Analytics overview:

curl -H "X-API-Key: $LODD_KEY" \
  "https://api.lodd.dev/v1/sites/$SITE_ID/analytics?period=30d"

{
  "data": {
    "total_page_views": 4310,
    "unique_visitors": 1842,
    "unique_countries": 28,
    "average_duration": 47.3,
    "pages_per_visit": 2.14,
    "bounce_rate": 38.2
  }
}

Note: the analytics endpoint returns data for the requested period only. To compare periods (e.g. this month vs last month), make two calls with different period parameters:

# Current period
curl -H "X-API-Key: $LODD_KEY" \
  "https://api.lodd.dev/v1/sites/$SITE_ID/analytics?period=30d"

# Previous period for comparison
curl -H "X-API-Key: $LODD_KEY" \
  "https://api.lodd.dev/v1/sites/$SITE_ID/analytics?period=2026-03-16..2026-04-15"

2. Top pages:

curl -H "X-API-Key: $LODD_KEY" \
  "https://api.lodd.dev/v1/sites/$SITE_ID/pages?period=7d"

{
  "data": [
    { "url": "/pricing", "page_title": "Pricing — My SaaS", "page_views": 430, "unique_visitors": 380, "bounce_rate": 55.2, "avg_duration": 62.4 },
    { "url": "/", "page_title": "My SaaS — Home", "page_views": 1200, "unique_visitors": 890, "bounce_rate": 32.1, "avg_duration": 94.7 }
  ]
}

3. Traffic sources:

curl -H "X-API-Key: $LODD_KEY" \
  "https://api.lodd.dev/v1/sites/$SITE_ID/sources?period=7d"

{
  "data": [
    { "source_name": "Google", "source_type": "search", "page_views": 1580, "unique_visitors": 620, "bounce_rate": 35.1, "avg_duration": 71.2, "utm_source": null, "utm_medium": null, "utm_campaign": null },
    { "source_name": "Reddit", "source_type": "social", "page_views": 890, "unique_visitors": 340, "bounce_rate": 42.3, "avg_duration": 38.9, "utm_source": "reddit", "utm_medium": "social", "utm_campaign": null }
  ]
}

Lodd has 49 REST endpoints total, covering funnels, events, session paths, performance, and more. Full API docs. OpenAPI spec.

Example: auto-create GitHub issues when bounce rate spikes

A daily cron pulls page-level analytics for two periods and compares them. If a high-traffic page has a significant bounce rate increase, it creates a GitHub issue with the data baked in. No one has to remember to check.

When this catches real bugs: a deploy broke the pricing page. Bounce rate jumped from 28% to 55% overnight. The issue lands in the backlog at 9am with the page URL, the before/after numbers, and the timestamp.

When this would be noise: a blog post fluctuates by 3%. The trigger needs a threshold.

The trigger logic

current_pages = GET /v1/sites/:id/pages?period=7d
previous_pages = GET /v1/sites/:id/pages?period=2026-05-04..2026-05-10  # previous 7 days

for each page in current_pages:
  prev = find matching page in previous_pages
  if page.page_views > 50 AND (page.bounce_rate - prev.bounce_rate) > 15:
    create_issue(page, prev)

Two conditions: the page has enough traffic to matter (50+ page views), and the bounce rate jump is significant (15+ percentage points). Tune these to your traffic levels.

Create the issue

gh issue create \
  --title "Bounce rate spike on /pricing (55% vs 28%)" \
  --body "## Analytics alert

**Page:** /pricing
**Period:** last 7 days
**Bounce rate:** 55.2% (was 28.4%)
**Page views:** 430

Possible causes:
- Recent deploy broke layout or functionality
- Load time regression
- Low-intent traffic from a new source

Data source: Lodd REST API · lodd.dev/api"

The issue has enough context to start investigating immediately. No one has to go pull data first.

Wire it up with any tool

A detailed walkthrough for Trigger.dev covers the full setup including multi-site loops, LLM interpretation, and email reporting.

Other workflows worth building

The GitHub issue flow is one pattern. Same API, different outputs:

Two interfaces, one data source

Lodd has 42 MCP tools for interactive agent sessions and this REST API for automation. MCP when your agent needs traffic context mid-conversation. REST when you're building something that runs on a schedule.

Same data, same API key. Get started or read the API docs.