ecommerceprice-monitoringautomationworkersalerts

Building a Price Monitoring System Without Writing a Single Scraper

Track competitor prices, detect promotions, and alert your team to market changes — all using reusable API workers instead of brittle custom scrapers.

S
Seek API Team
·

Price intelligence is one of the most valuable data sources in ecommerce, travel, SaaS, and B2B. If you know when a competitor drops their price, launches a promo, or quietly raises rates — you can respond.

The traditional path: write a custom scraper. But scrapers break. Every site update, every anti-bot upgrade, every DOM change requires maintenance. And if you need to monitor 50 sites, you need 50 scrapers.

There’s a simpler model.

What price monitoring actually needs

A price monitoring system has four jobs:

  1. Extract the current price from a source URL
  2. Store the result with a timestamp
  3. Compare against the previous value
  4. Alert when something exceeds a threshold

Jobs 2–4 are standard backend logic. Job 1 is where people get stuck — and where workers help.

Using workers for price extraction

Workers are pre-built, maintained extractors. Instead of writing and hosting a scraper for Amazon, a worker for Amazon product pages already exists. You call it with a URL, get structured data back.

curl -X POST https://api.seek-api.com/v1/workers/amazon-product/jobs \
  -H "X-Api-Key: YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{"url": "https://www.amazon.com/dp/B0CHWCC249"}'

Result:

{
  "title": "Apple AirPods Pro (2nd Generation)",
  "price": 189.99,
  "currency": "USD",
  "availability": "In Stock",
  "rating": 4.4,
  "reviewCount": 82341,
  "seller": "Amazon.com",
  "prime": true,
  "originalPrice": 249.00,
  "discount": "24%"
}

No scraper to write. No proxy pool to manage. No Playwright session to debug.

The full pipeline

Here’s a complete price monitoring system in ~50 lines of Node.js:

import Cron from 'node-cron';
import fetch from 'node-fetch';

const TARGETS = [
  { name: "AirPods Pro", worker: "amazon-product", url: "https://amazon.com/dp/B0CHWCC249" },
  { name: "Competitor SaaS", worker: "website-price-extractor", url: "https://competitor.com/pricing" },
];

const HISTORY = {};

async function checkPrice(target) {
  const { job_uuid } = await fetch('https://api.seek-api.com/v1/workers/' + target.worker + '/jobs', {
    method: 'POST',
    headers: { 'X-Api-Key': process.env.SEEKAPI_KEY, 'Content-Type': 'application/json' },
    body: JSON.stringify({ url: target.url }),
  }).then(r => r.json());

  // Wait for result
  let result;
  while (true) {
    const status = await fetch(`https://api.seek-api.com/v1/jobs/${job_uuid}`, {
      headers: { 'X-Api-Key': process.env.SEEKAPI_KEY }
    }).then(r => r.json());

    if (status.status === 'completed') { result = status.result; break; }
    await new Promise(r => setTimeout(r, 3000));
  }

  const prev = HISTORY[target.name];
  const curr = result.price;

  if (prev && prev !== curr) {
    await sendAlert(target.name, prev, curr);
  }

  HISTORY[target.name] = curr;
}

async function sendAlert(name, prev, curr) {
  const direction = curr < prev ? '⬇️ dropped' : '⬆️ raised';
  await fetch(process.env.SLACK_WEBHOOK, {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({
      text: `*${name}* price ${direction}: $${prev} → $${curr}`
    }),
  });
}

// Run every 6 hours
Cron.schedule('0 */6 * * *', () => {
  TARGETS.forEach(checkPrice);
});

Deploy this to any server or cloud function. You now have a live price alert system with Slack notifications.

Scaling to hundreds of products

For large catalogs, batch-submit all jobs, then poll in parallel:

const jobs = await Promise.all(
  PRODUCTS.map(product =>
    submitJob(product.worker, { url: product.url })
      .then(j => ({ ...j, product }))
  )
);

// Poll all job statuses concurrently
const results = await Promise.all(jobs.map(j => pollUntilComplete(j.job_uuid)));

100 product checks completes in seconds rather than minutes because jobs run in parallel.

Use case: SaaS competitor pricing changes

Many SaaS companies update their pricing pages without announcement. A weekly automated check against /pricing pages using a generic text-extractor worker can surface changes to tiers, limits, and prices before they get picked up by industry newsletters.

POST /v1/workers/webpage-extractor/jobs
{ "url": "https://competitor.com/pricing", "fields": ["price", "plan_name", "limits"] }

Use case: Flight price drops

POST /v1/workers/flight-prices/jobs
{ "origin": "CDG", "destination": "JFK", "date": "2026-06-15" }

Run daily, alert when the cheapest fare drops more than 15% vs. last observation.

What you don’t need to build

With this approach, you skip:

  • Proxy management
  • Anti-bot bypass research
  • Playwright / Puppeteer browser sessions
  • CSS selector maintenance
  • Site-specific scraper logic

Workers are maintained by people who specialize in extracting from those sources. When a site changes, the worker gets updated — not your code.

Back to blog