3.6 / 5

Refund Hunter

Scans your email for refund opportunities and drafts requests

Useful

Privacy

The Problem

Refund opportunities exist but require knowledge and effort to claim

Current Solutions (Not Great)

Paribus (sold data), manual tracking (tedious), missing out entirely

Who Needs This

Online shoppers, deal hunters, anyone who feels they've been overcharged

You're owed money you don't know about: price drops after purchase, late deliveries with guaranteed shipping, subscriptions still charging for cancelled services, duplicate charges, failed deliveries. Refund Hunter scans your purchase emails, identifies refund opportunities based on retailer policies, and drafts appropriate refund request emails. For Amazon price drops within the return window, late deliveries with guarantees, or obvious billing errors—it finds money you're leaving on the table and helps you get it back.

Honest Take

Paribus tried this, got acquired by Capital One, then quietly shut down—tells you something about the market. Retailers are getting better at automatic refunds (Amazon especially), which reduces opportunities. The percentage-of-refund business model could work, but you're fighting against improving retailer systems and potential legal/TOS issues with automated claims.

Monetization Ideas

Ways to turn this into revenue

Freemium

Free basic, $5-15/mo for pro

Subscription

$5-29/month or $49-199/year

Features

Key features that make this app valuable

Scan purchase emails for opportunities
Price drop detection (within return window)
Late delivery identification
Duplicate charge detection
Subscription billing anomaly detection
Refund request email drafting
Retailer policy knowledge
Success tracking and follow-up

Build Prompt

Use this prompt with an AI assistant to start building

Build a Chrome extension called 'Refund Hunter' using WebInfer. Manifest V3 with activeTab, storage permissions. Target: Gmail web interface. Opportunity detection: content script scans for purchase/shipping emails. Build purchase database: { orderId, retailer, items, price, purchaseDate, deliveryGuarantee?, deliveredDate?, trackingStatus }. Opportunity analysis using AI: generateObject returns { opportunities: [{ type: 'price-drop'|'late-delivery'|'duplicate-charge'|'subscription-error'|'damaged', orderId: string, amount: number, confidence: number, policy: string, deadline?: string }] }. Price drop detection: for purchases within return window (typically 14-30 days), check current price via background tab. Late delivery: compare deliveryGuarantee to actual deliveredDate. Draft generation: for each opportunity, generate refund request email. Use generateObject: { subject: string, body: string, tone: 'polite-firm', keyPoints: string[], attachmentsNeeded: string[] }. UI popup: opportunity list sorted by amount, click to see draft, edit if needed, one-click send (or copy to clipboard). Track: which requests sent, responses received, money recovered. Dashboard: total money recovered, pending requests, success rate by retailer. Retailer policy database: known refund policies, typical response times, effective language.

Score Breakdown

Pain

Clarity