Coupon Promo Code Intelligence Tracker

Track competitor coupon and promo-code offers with discount value, customer segment, minimum spend, expiry signal, and channel context.

Coupon Promo Code Intelligence Tracker is built for one focused job: turning public source pages or pasted research snippets into usable promo intelligence row records. It does not try to be a generic webpage scraper. The parser, fields, examples, and dataset schema are shaped around this actor's specific business question.

Use it when you already have public pages, listings, announcements, reviews, directories, or copied snippets and want a repeatable way to extract the information that matters without manually filling a spreadsheet.

Who Uses It

Ecommerce operators, affiliate publishers, coupon sites, pricing analysts, and competitor intelligence teams.

What It Finds

The actor looks for signals connected to track competitor coupon and promo-code offers with discount value, customer segment, minimum spend, expiry signal, and channel context. It keeps the output focused on fields a buyer can review, filter, enrich, or send into a CRM, spreadsheet, product backlog, procurement workflow, or research database.

The extraction method is specific to this actor:

Coupon-code regex extraction, discount normalization, expiry detection, segment/minimum-spend parsing, and promotion-position classification.

How It Works

1. The actor accepts public URLs or pasted snippets in couponSources.
2. Public URLs are fetched when possible and converted into visible text.
3. Pasted snippets are processed directly, which is useful for pages that block automated fetching or require manual browsing.
4. Actor-specific parsing logic extracts only the fields listed below.
5. Empty or low-information inputs are skipped safely, with clean logs instead of noisy failed rows.

Input

Use couponSources for the sources you want to process. Each item can be a public URL or a focused text snippet.

{
    "couponSources": [
        "FitGear promo code SUMMER25 gives 25% off for new customers until August 1, 2026. Minimum spend $75.",
        "TravelNest newsletter offers free shipping plus code LUGGAGE15 for loyalty members this weekend.",
        "TaskFlow launch coupon STARTER40 gives 40% off first month for startups on annual plans."
    ],
    "maxResults": 3
}

Output Fields

• brandName - Brand offering the promotion or affiliate program.
• promoCode - Coupon or promo code found in the source.
• discountValue - Discount percentage, amount, or free-shipping offer.
• offerType - Promotion format such as coupon, free shipping, or launch discount.
• eligibleCustomer - Customer segment eligible for the promotion.
• minimumSpend - Minimum order value or spend requirement.
• expirySignal - Expiry date, weekend-only note, or urgency wording.
• channelSignal - Where the offer appears, such as newsletter, loyalty, or public promo.
• competitiveAngle - Why the offer matters for competitive pricing research.
• sourceUrl - Original source URL.

Example Output

{
    "brandName": "FitGear",
    "promoCode": "SUMMER25",
    "discountValue": "25% off",
    "offerType": "discount code",
    "eligibleCustomer": "new customers",
    "minimumSpend": "$75",
    "expirySignal": "August 1, 2026",
    "channelSignal": "public promo",
    "competitiveAngle": "discount-depth monitoring",
    "sourceUrl": "https://example.com/coupon"
}

Best Use Cases

• Build a focused spreadsheet from repeated source pages.
• Review public signals before sales, partnership, product, procurement, or market research work.
• Monitor a category over time using the same output fields.
• Turn copied notes from newsletters, communities, directories, review pages, or search results into a structured dataset.

Tips For Better Results

• Use source pages that visibly contain the signal you want this actor to extract.
• For hard-to-fetch sites, paste the relevant public text snippet directly into the input.
• Keep each input item focused on one page, listing, announcement, review, or profile.
• Review extracted rows before making high-stakes business, legal, procurement, or security decisions.

Limitations

• The actor does not bypass logins, paywalls, private systems, CAPTCHA, or anti-bot walls.
• The actor extracts from visible text and may miss information hidden behind scripts or user interactions.
• Some fields may be empty when the source does not contain that information.
• Output quality depends on source quality, so focused source text produces the strongest rows.