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  1. Runbooks

High-Intent Visitors

Export identified visitors who viewed your pricing or product pages in the last 24 hours

Use Case

  • Daily lead list for sales outreach
  • Identify visitors showing buying signals (pricing pages, demo pages, contact pages)
  • Filter by page URL patterns

Prerequisites

Steps

1. Set Up Your Time Range

Events require a time range in milliseconds (Unix epoch).

# Last 24 hours in milliseconds
END_MS=$(date +%s)000
START_MS=$(($(date +%s) - 86400))000

2. Query for Pricing Page Visitors

curl "https://apiv3.delivr.ai/api/v1/events?pixel_id=YOUR_PIXEL_ID&start_ms=$START_MS&end_ms=$END_MS&filter=resolved:eq:true,event_url:like:%25pricing%25&select=email,first_name,last_name,company_name,job_title,event_url,event_time&limit=100" \
  -H "Authorization: Bearer YOUR_JWT_TOKEN" \
  -H "x-organization-id: YOUR_ORGANIZATION_ID"

3. Query for Product Page Visitors

curl "https://apiv3.delivr.ai/api/v1/events?pixel_id=YOUR_PIXEL_ID&start_ms=$START_MS&end_ms=$END_MS&filter=resolved:eq:true,event_url:like:%25product%25&select=email,first_name,last_name,company_name,job_title,event_url,event_time&limit=100" \
  -H "Authorization: Bearer YOUR_JWT_TOKEN" \
  -H "x-organization-id: YOUR_ORGANIZATION_ID"

Expected Response

{
  "pixel_id": "8a755c42-b2b1-...",
  "start_ms": 1706745600000,
  "end_ms": 1706832000000,
  "limit": 100,
  "offset": 0,
  "rows": [
    {
      "email": "[email protected]",
      "first_name": "John",
      "last_name": "Smith",
      "company_name": "Acme Corp",
      "job_title": "VP of Marketing",
      "event_url": "https://yoursite.com/pricing",
      "event_time": "2026-01-15 14:30:00"
    }
  ],
  "meta": {
    "fields": ["email", "first_name", "last_name", "company_name", "job_title", "event_url", "event_time"]
  },
  "index_name": "resolved_events"
}

Variations

Multiple URL Patterns

Run separate queries for each page pattern:

# Pricing pages
filter=resolved:eq:true,event_url:like:%25pricing%25

# Demo/trial pages
filter=resolved:eq:true,event_url:like:%25demo%25

# Contact pages
filter=resolved:eq:true,event_url:like:%25contact%25

Deduplicate by Person

Get one row per unique person instead of one row per event:

&distinct=hem

Deduplicate by Company

Get one row per unique company:

&distinct=company_domain

Get Visitor Count First

Check how many results before fetching full data:

curl "https://apiv3.delivr.ai/api/v1/event_counts?pixel_id=YOUR_PIXEL_ID&start_ms=$START_MS&end_ms=$END_MS&filter=resolved:eq:true,event_url:like:%25pricing%25" \
  -H "Authorization: Bearer YOUR_JWT_TOKEN" \
  -H "x-organization-id: YOUR_ORGANIZATION_ID"

Response:

{
  "count": 47,
  "meta": {}
}

Python Example

import requests
import time

TOKEN = "your_jwt_token"
ORG_ID = "your_organization_id"
PIXEL_ID = "your_pixel_id"

HEADERS = {
    "Authorization": f"Bearer {TOKEN}",
    "x-organization-id": ORG_ID,
}

# Last 24 hours
end_ms = int(time.time() * 1000)
start_ms = end_ms - (24 * 60 * 60 * 1000)

# Query resolved visitors on pricing pages
response = requests.get(
    "https://apiv3.delivr.ai/api/v1/events",
    headers=HEADERS,
    params={
        "pixel_id": PIXEL_ID,
        "start_ms": start_ms,
        "end_ms": end_ms,
        "filter": "resolved:eq:true,event_url:like:%pricing%",
        "select": "email,first_name,last_name,company_name,job_title",
        "distinct": "hem",
        "limit": 100,
    },
)

data = response.json()
visitors = data.get("rows", [])
print(f"Found {len(visitors)} high-intent visitors")

for v in visitors:
    print(f"  - {v['first_name']} {v['last_name']} ({v['company_name']})")

Notes

  • The Events API has a 25-hour maximum time window per request. For longer ranges, make multiple requests in 24-hour chunks.
  • resolved:eq:true filters for events where the visitor was identified. Without this filter, you'll also get anonymous events.
  • The %25 in curl URLs is the URL-encoded % for the like operator. In Python requests, use % directly -- it handles encoding automatically.

Next Steps

Updated 3 days ago