SaaS Competitive Intelligence

Automatically monitor and analyze competitor SaaS websites to extract pricing plans, job openings, team size, tech stack, and social media presence. Enter a list of competitor URLs and get structured competitive intelligence data back in JSON, CSV, or Excel format — no manual research required.

Why Use SaaS Competitive Intelligence?

Manual competitor research is tedious: visiting pricing pages, checking career listings, counting team members, and identifying tech stacks across dozens of sites. This actor does it all in under 2 minutes for 5 competitors, returning clean structured data you can feed into dashboards, spreadsheets, or alerting systems. Schedule it weekly to track changes over time.

Features

• Pricing extraction — automatically finds pricing pages and extracts plan names, prices, billing periods, and feature lists from competitor websites
• Career page analysis — detects job listings, counts open positions, and classifies hiring velocity (none, minimal, moderate, aggressive)
• Team and company intelligence — scrapes about/team pages for estimated team size and company descriptions
• Tech stack detection — identifies 30+ technologies including analytics (Google Analytics, Mixpanel, Amplitude), frameworks (React, Next.js, Vue.js, Angular), support (Intercom, Zendesk, Crisp), marketing (HubSpot, Marketo, Pardot), and infrastructure (Cloudflare, Stripe, Sentry)
• Social media link discovery — extracts links to Twitter/X, LinkedIn, Facebook, Instagram, YouTube, GitHub, and TikTok profiles
• Batch processing — analyze up to 50 competitor websites in a single run with configurable crawl depth per site
• Structured output — returns clean, normalized JSON data per competitor with homepage metadata, pricing details, career data, and detected technologies

How to Use

1. Enter one or more competitor website URLs (e.g., https://notion.so, https://slack.com, https://linear.app)
2. Choose which intelligence to gather: pricing, careers, team info, or all three
3. Click Start and wait for the run to finish (typically under 2 minutes for 5 competitors)
4. Download results from the Dataset tab in JSON, CSV, or Excel format

Input Parameters

Input Examples

Quick competitor comparison — pricing and careers:

{
    "competitorUrls": ["https://notion.so", "https://slack.com", "https://linear.app"],
    "checkPricing": true,
    "checkCareers": true,
    "checkTeam": false
}

Full analysis — all modules enabled:

{
    "competitorUrls": ["https://stripe.com", "https://square.com", "https://paypal.com"],
    "checkPricing": true,
    "checkCareers": true,
    "checkTeam": true,
    "maxPagesPerSite": 15
}

Tech stack audit only — homepage scan:

{
    "competitorUrls": ["https://vercel.com", "https://netlify.com", "https://render.com"],
    "checkPricing": false,
    "checkCareers": false,
    "checkTeam": false,
    "maxPagesPerSite": 1
}

Input Tips

• Even without enabling pricing/careers/team, the homepage scan extracts company name, meta description, social media links, and full tech stack.
• Keep maxPagesPerSite low (3–5) for faster runs. Most useful data comes from homepage + pricing + careers + about.
• URLs without https:// are normalized automatically — notion.so works just as well as https://notion.so.

Output

The actor returns one result object per competitor website:

{
    "url": "https://notion.so",
    "domain": "notion.so",
    "companyName": "Notion",
    "scrapedAt": "2025-11-15T14:32:07.123Z",
    "homepage": {
        "title": "Notion - Your connected workspace for wiki, docs & projects",
        "description": "A new tool that blends your everyday work apps into one.",
        "ogImage": "https://www.notion.so/images/meta/default.png",
        "socialLinks": {
            "twitter": "https://x.com/NotionHQ",
            "linkedin": "https://www.linkedin.com/company/notionhq/",
            "youtube": "https://www.youtube.com/@NotionHQ"
        }
    },
    "pricing": {
        "found": true,
        "pricingUrl": "https://www.notion.so/pricing",
        "plans": [
            {
                "name": "Free",
                "price": "$0",
                "period": "/mo",
                "features": ["Collaborative workspace", "7 day page history"]
            },
            {
                "name": "Plus",
                "price": "$10",
                "period": "/mo",
                "features": ["Unlimited blocks", "30 day page history"]
            }
        ],
        "rawPricingText": null
    },
    "careers": {
        "found": true,
        "careersUrl": "https://www.notion.so/careers",
        "totalOpenings": 42,
        "jobTitles": ["Senior Software Engineer", "Product Designer"],
        "hiringVelocity": "aggressive"
    },
    "team": {
        "found": true,
        "teamUrl": "https://www.notion.so/about",
        "teamSize": 500,
        "companyDescription": "Notion is a connected workspace..."
    },
    "techStack": ["Cloudflare", "Google Analytics", "Intercom", "Next.js", "Stripe"],
    "metadata": {
        "pagesScraped": 4,
        "scrapeDurationMs": 8432
    }
}

Output Fields

Use Cases

• Product managers — track how competitors change pricing tiers and feature bundles over time. Run weekly to spot pricing shifts early.
• Venture capital analysts — gauge growth signals by monitoring hiring velocity and team size across portfolio companies and competitors.
• Marketing teams — understand which analytics, CRM, and marketing tools competitors use to inform tooling decisions.
• Sales teams — prepare for competitive deals by knowing exactly what pricing plans and features rivals offer.
• Startup founders — benchmark pricing against the market and track when competitors expand engineering or sales teams.
• Market researchers — build comprehensive competitive landscape reports with structured data on dozens of SaaS companies.

How to Use the API

Python

import requests
import time

run = requests.post(
    "https://api.apify.com/v2/acts/ryanclinton~saas-competitive-intel/runs",
    params={"token": "YOUR_APIFY_TOKEN"},
    json={
        "competitorUrls": ["https://notion.so", "https://slack.com", "https://linear.app"],
        "checkPricing": True,
        "checkCareers": True,
        "checkTeam": True
    },
    timeout=30,
).json()

run_id = run["data"]["id"]
while True:
    status = requests.get(
        f"https://api.apify.com/v2/actor-runs/{run_id}",
        params={"token": "YOUR_APIFY_TOKEN"},
        timeout=10,
    ).json()
    if status["data"]["status"] in ("SUCCEEDED", "FAILED", "ABORTED"):
        break
    time.sleep(5)

dataset_id = status["data"]["defaultDatasetId"]
items = requests.get(
    f"https://api.apify.com/v2/datasets/{dataset_id}/items",
    params={"token": "YOUR_APIFY_TOKEN"},
    timeout=30,
).json()

for item in items:
    plans = ", ".join(f"{p['name']}: {p['price']}" for p in item["pricing"]["plans"])
    print(f"{item['companyName']}: {plans or 'No pricing found'}")
    print(f"  Hiring: {item['careers']['hiringVelocity']} ({item['careers']['totalOpenings']} openings)")
    print(f"  Tech: {', '.join(item['techStack'][:5])}")

JavaScript

const response = await fetch(
    "https://api.apify.com/v2/acts/ryanclinton~saas-competitive-intel/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN",
    {
        method: "POST",
        headers: { "Content-Type": "application/json" },
        body: JSON.stringify({
            competitorUrls: ["https://notion.so", "https://slack.com"],
            checkPricing: true,
            checkCareers: true,
        }),
    }
);

const results = await response.json();
results.forEach((r) => {
    console.log(`${r.companyName}: ${r.pricing.plans.length} plans, ${r.careers.totalOpenings} openings`);
});

cURL

curl -X POST "https://api.apify.com/v2/acts/ryanclinton~saas-competitive-intel/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "competitorUrls": ["https://notion.so", "https://slack.com"],
    "checkPricing": true,
    "checkCareers": true
  }'

How It Works

Input (competitor URLs, module toggles)
  │
  ▼
┌──────────────────────────────────────────────────┐
│  URL Normalization                               │
│  Add https:// if missing, extract domain         │
│  Initialize result objects per domain            │
└──────────────────────────────────────────────────┘
  │
  ▼
┌──────────────────────────────────────────────────┐
│  CheerioCrawler (concurrency: 5)                 │
│                                                  │
│  ┌─ HOMEPAGE handler ─────────────────────────┐  │
│  │ • Extract <title>, og:*, meta description  │  │
│  │ • Detect company name (og:site_name > title)│  │
│  │ • Extract social media links (7 platforms) │  │
│  │ • Detect tech stack (30+ regex patterns)   │  │
│  │ • Discover pricing/careers/team page links │  │
│  │   via URL patterns + anchor text matching  │  │
│  │ • Queue discovered subpages for crawling   │  │
│  └────────────────────────────────────────────┘  │
│       │                                          │
│       ├── PRICING handler ───────────────────┐   │
│       │   Strategy 1: CSS class selectors    │   │
│       │   [class*="price"], [class*="plan"]  │   │
│       │   → extract plan name, $price,       │   │
│       │   /period, feature lists             │   │
│       │                                      │   │
│       │   Strategy 2: Fallback regex scan    │   │
│       │   Scan all elements for $X.XX        │   │
│       │   patterns + nearby headings         │   │
│       │   Deduplicate by price+name          │   │
│       └──────────────────────────────────────┘   │
│       │                                          │
│       ├── CAREERS handler ───────────────────┐   │
│       │   Strategy 1: Job CSS selectors      │   │
│       │   [class*="job"], a[href*="/jobs/"]   │   │
│       │                                      │   │
│       │   Strategy 2: Role keyword matching  │   │
│       │   engineer, designer, manager, etc.  │   │
│       │                                      │   │
│       │   Strategy 3: Count text patterns    │   │
│       │   "42 open positions"                │   │
│       │                                      │   │
│       │   Hiring velocity classification:    │   │
│       │   0=none, 1-5=minimal,               │   │
│       │   6-20=moderate, 21+=aggressive      │   │
│       └──────────────────────────────────────┘   │
│       │                                          │
│       └── TEAM handler ──────────────────────┐   │
│           Count team member cards via CSS     │   │
│           Fallback: "200+ employees" text    │   │
│           Extract company description from   │   │
│           meta tags or first paragraph       │   │
│           └──────────────────────────────────┘   │
└──────────────────────────────────────────────────┘
  │
  ▼
Dataset (one row per competitor)

Page Discovery

The actor finds subpages by scanning all internal links on the homepage for URL patterns and anchor text:

Only same-domain links are followed.

Tech Stack Detection

The actor identifies 30+ technologies by matching regex patterns against script sources, link hrefs, and raw HTML:

Hiring Velocity Classification

How Much Does It Cost?

This actor uses CheerioCrawler (server-side HTML, no browser rendering), making it extremely lightweight.

The Apify Free plan ($5/month) covers daily monitoring of 10 competitors for an entire month.

Tips

• Start with homepages — even without enabling pricing/careers/team, the homepage scan extracts company name, description, social links, and full tech stack.
• Run on a schedule — set up a weekly or monthly schedule to track competitor changes over time. Connect to Google Sheets or a webhook to build a time-series dashboard.
• Keep maxPagesPerSite low — the default of 10 is generous. Most useful data comes from 3–4 pages. Lower values speed up execution.
• Watch hiring velocity — a competitor shifting from "minimal" to "aggressive" often signals a new product launch, funding round, or market expansion 3–6 months before it becomes public.
• Combine with WHOIS data — pair with domain lookup tools to get registration dates and hosting details alongside competitive intelligence.
• Use rawPricingText for custom parsing — if the auto-extracted pricing plans miss details, the rawPricingText field contains up to 3,000 characters of raw pricing page text you can parse yourself.

Limitations

• Server-rendered HTML only — uses CheerioCrawler, which processes server-side HTML. If a competitor's pricing page relies heavily on client-side JavaScript rendering, pricing plans may not be fully extracted. Most SaaS companies serve pricing content in initial HTML for SEO.
• Pricing extraction is heuristic — the actor looks for $X.XX patterns and CSS classes containing "price", "plan", or "tier". Custom pricing structures, enterprise-only pricing, or heavily abstracted layouts may not be detected.
• Job title quality varies — job listing extraction depends on consistent HTML structure. Some career pages use embedded iframes (Greenhouse, Lever) that CheerioCrawler cannot access.
• Team size is estimated — counted from team member cards or text patterns like "200+ employees". Companies that don't display team info on their website will return null.
• No login/authentication — the actor only accesses publicly visible pages. Gated content behind login walls is not accessible.
• Social media links are from anchor tags only — if social links are rendered via JavaScript or embedded in images, they may not be detected.
• 30+ tech stack patterns, not exhaustive — the detection covers major tools but may miss niche or recently launched technologies.
• One brand name per competitor — the company name is auto-detected from og:site_name or <title>. Multi-brand companies may show the parent brand only.

Responsible Use

• Only scrape publicly available pages — this actor accesses the same pages any visitor would see in a browser.
• Respect robots.txt — the CheerioCrawler respects robots.txt directives by default.
• Use reasonable crawl depths — keep maxPagesPerSite at 10 or below to avoid excessive requests to competitor servers.
• Competitive intelligence, not harassment — use the data for legitimate business analysis, not to spam or attack competitors.
• Comply with applicable laws — for GDPR, CCPA, or jurisdiction-specific questions, consult legal counsel. See Apify's guide on web scraping legality.

FAQ

How does the actor find pricing, career, and team pages? It crawls the competitor's homepage and scans all internal links for URL patterns and anchor text matching keywords like "pricing", "plans", "careers", "jobs", "about", and "team".

Can it extract pricing from JavaScript-rendered pages? This actor uses CheerioCrawler (server-side HTML). If a competitor's pricing relies on client-side JavaScript, plans may not be fully extracted. Most SaaS companies serve pricing in initial HTML for SEO.

What tech stack tools does it detect? 30+ technologies across analytics, marketing, support, payments, error tracking, frameworks, CMS, and infrastructure. See the tech stack detection table above.

How accurate is the hiring velocity classification? Based on the number of open positions found: "none" (0), "minimal" (1–5), "moderate" (6–20), "aggressive" (21+). Reflects what is publicly listed at the time of the scrape.

Can I monitor competitors automatically on a schedule? Yes. Set up a cron schedule on Apify to run daily, weekly, or monthly. Combine with Zapier or webhooks for automated alerts.

Why is team size sometimes null? Team size is estimated from team member cards or text patterns. If the page uses a non-standard layout or doesn't disclose team size, the value will be null.

Can I track more than 50 competitors? Yes, set maxResults up to 200. Larger batches take proportionally longer to complete.

Integrations

• Zapier — trigger alerts when competitors change pricing or post new jobs.
• Make (Integromat) — build multi-step competitive analysis workflows.
• Google Sheets — export competitor data into a tracking spreadsheet.
• Webhooks — receive results at any HTTP endpoint for custom processing.
• Apify API — call programmatically from any language for custom dashboards.
• Slack / Email — configure Apify notifications for run completion alerts.

Related Actors