NicheForge

Mission

Build me a full-stack AI-powered ecommerce intelligence and dropshipping operating system. This is not just a dropshipping store. Build a private AI commerce command center that helps me discover product opportunities, validate niches, launch test landing pages, track performance, and continuously improve weekly/monthly based on real data. The goal: Create a self-improving ecommerce engine that can research global product demand, identify high-potential products, score them, generate product pages, create marketing angles, track ad/testing metrics, and recommend which products to kill, improve, retest, or scale. Important: Do not present this as guaranteed profits. The system should help me make better decisions. The money comes from disciplined testing, offer quality, fulfillment reliability, margin, and customer trust. Business philosophy: Build a commerce intelligence machine. The operating loop should be: Research → Score → Build offer → Launch page → Test traffic → Measure → Kill/Improve/Scale → Report → Repeat The product can change. The machine is the asset. Tech stack: - Next.js - Tailwind CSS - Supabase or PostgreSQL - Stripe integration placeholder - Shopify integration placeholder - OpenAI/LLM integration placeholder - Cron job system for weekly/monthly niche reviews - Admin dashboard - Role-based admin access Design style: Dark, premium, futuristic, founder dashboard energy. Make it feel like a private ecommerce war room. Clean typography. Minimal clutter. Use strong cards, ranking tables, and performance dashboards. Make it feel elite, serious, and high-agency. Core product idea: Build one main ecommerce intelligence system that can test multiple niches and offers. Do not make it cycle through random niches chaotically. Create a system that ranks niches, launches controlled tests, measures results, and improves from data. Prioritize products that are: - High-margin - Lightweight - Globally shippable - Easy to demonstrate visually - Problem-solving - Impulse-friendly - Low liability - Simple to fulfill - Capable of repeat purchase or upsells - Strong emotional buying trigger - Clear before/after or problem/solution angle Avoid products that are: - Illegal - Unsafe - Counterfeit - Medical-claim heavy - Adult - Weapons - Supplements - Restricted - High defect-risk electronics - Products with long shipping times - Products that create customer service nightmares Best niche categories to support: - Home problem-solvers - Beauty tools/accessories - Pet products - Baby/parent convenience products, but avoid safety-risk claims - Travel accessories - Desk/productivity accessories - Fitness accessories, but avoid medical/body transformation claims MVP modules: 1. Admin Dashboard Create a main dashboard showing: - Active niches being tested - Active products - Product scores - Revenue - Profit estimate - Conversion rate - Ad spend - ROAS - Gross margin - Fulfillment status - Weekly recommendations - Products to kill - Products to improve - Products to scale 2. Niche Research Agent Create an AI-assisted niche research module. Each niche should be scored based on: - Search demand - Social trend potential - Pain point intensity - Global buyer reach - Shipping simplicity - Supplier availability - Margin potential - Repeat purchase potential - Impulse-buy potential - Competition level - Content virality potential The agent should output: - Score from 1-100 - Explanation - Main audience - Core pain point - Best product types - Risks - Recommended test strategy 3. Product Scoring System Each product should have: - Product name - Niche - Supplier cost - Suggested selling price - Estimated gross margin - Shipping complexity - Target audience - Primary pain point - Emotional buying trigger - Ad angle - TikTok/Reels hook ideas - Landing page headline - Product score - Risk score - Status Statuses: - research - testing - active - paused - killed - scaled 4. AI Offer Builder For each product, generate: - Product title - 5 headlines - 5 ad hooks - 3 product descriptions - 3 landing page angles - FAQ section - Objection handling - Upsell ideas - Bundle ideas - Email/SMS follow-up copy - Refund/return policy draft The tone should be clear, conversion-focused, premium, and trustworthy. 5. Landing Page Generator Create dynamic product landing pages from the database. Each page should include: - Hero section - Product benefits - Pain/problem section - Product solution section - Social proof placeholder - Before/after style benefit framing - FAQ - Buy button placeholder - Email capture if checkout is not active - Trust section - Shipping/returns section 6. Weekly/Monthly Niche Rotation Engine Build a scheduler where I can choose: - Weekly niche review - Monthly niche review - Manual review At each review, the system should: - Rank active products - Compare performance - Recommend winners and losers - Suggest new niches to test - Archive poor performers - Generate a written founder report - Recommend the next 3 actions 7. Experiment Tracking Each product test should track: - Test start date - Test end date - Traffic source - Ad spend - Impressions - Clicks - CTR - Add-to-cart rate - Conversion rate - Revenue - Refunds - Profit estimate - Notes - Final decision 8. AI Strategy Report Create a report page that generates: - Weekly summary - Best niche - Best product - Worst product - Biggest bottleneck - Recommended next action - Scaling plan - Kill list - New test list - Where money was wasted - What should be improved - What should be tested next 9. AI Decision Engine Add an AI decision engine. The engine should analyze every product experiment and assign one of five decisions: 1. Kill 2. Improve creative 3. Improve landing page 4. Retest with new audience 5. Scale Use these inputs: - CTR - Conversion rate - Revenue - Ad spend - Profit estimate - Refunds - Product score - Risk score - Notes Create a clear decision explanation in plain English. Decision rules: - If product has low CTR, recommend improving creative/hook. - If product has high clicks but low conversions, recommend improving offer or landing page. - If product has poor conversion after meaningful traffic, mark for review or kill. - If product has profitable ROAS and reliable fulfillment, recommend scaling slowly. - If refund rate or support complaints rise, pause immediately. - If shipping is unreliable, do not scale even if sales look promising. 10. Database Tables Create tables for: niches: - id - name - description - demand_score - competition_score - margin_score - virality_score - global_reach_score - final_score - status - created_at products: - id - niche_id - name - supplier_cost - suggested_price - estimated_margin - target_customer - pain_point - buying_trigger - product_score - risk_score - status - created_at experiments: - id - product_id - traffic_source - ad_spend - impressions - clicks - conversions - revenue - refunds - profit_estimate - decision - notes - created_at suppliers: - id - product_id - supplier_name - supplier_url - supplier_cost - shipping_time - reliability_score - notes - created_at landing_pages: - id - product_id - headline - subheadline - product_description - benefits - faq - status - created_at ad_creatives: - id - product_id - hook - angle - platform - script - status - created_at weekly_reviews: - id - review_period - summary - best_product_id - worst_product_id - recommendations - created_at ai_reports: - id - report_type - summary - best_product_id - worst_product_id - recommendations - created_at users: - id - email - role - created_at 11. Example SQL Schema Use this as the starting point: CREATE TABLE niches ( id UUID PRIMARY KEY DEFAULT gen_random_uuid(), name TEXT NOT NULL, description TEXT, demand_score INTEGER, competition_score INTEGER, margin_score INTEGER, virality_score INTEGER, global_reach_score INTEGER, final_score INTEGER, status TEXT DEFAULT 'research', created_at TIMESTAMP DEFAULT NOW() ); CREATE TABLE products ( id UUID PRIMARY KEY DEFAULT gen_random_uuid(), niche_id UUID REFERENCES niches(id), name TEXT NOT NULL, supplier_cost NUMERIC, suggested_price NUMERIC, estimated_margin NUMERIC, target_customer TEXT, pain_point TEXT, buying_trigger TEXT, product_score INTEGER, risk_score INTEGER, status TEXT DEFAULT 'research', created_at TIMESTAMP DEFAULT NOW() ); CREATE TABLE experiments ( id UUID PRIMARY KEY DEFAULT gen_random_uuid(), product_id UUID REFERENCES products(id), traffic_source TEXT, ad_spend NUMERIC DEFAULT 0, impressions INTEGER DEFAULT 0, clicks INTEGER DEFAULT 0, conversions INTEGER DEFAULT 0, revenue NUMERIC DEFAULT 0, refunds NUMERIC DEFAULT 0, profit_estimate NUMERIC DEFAULT 0, decision TEXT, notes TEXT, created_at TIMESTAMP DEFAULT NOW() ); CREATE TABLE suppliers ( id UUID PRIMARY KEY DEFAULT gen_random_uuid(), product_id UUID REFERENCES products(id), supplier_name TEXT, supplier_url TEXT, supplier_cost NUMERIC, shipping_time TEXT, reliability_score INTEGER, notes TEXT, created_at TIMESTAMP DEFAULT NOW() ); CREATE TABLE landing_pages ( id UUID PRIMARY KEY DEFAULT gen_random_uuid(), product_id UUID REFERENCES products(id), headline TEXT, subheadline TEXT, product_description TEXT, benefits TEXT, faq TEXT, status TEXT DEFAULT 'draft', created_at TIMESTAMP DEFAULT NOW() ); CREATE TABLE ad_creatives ( id UUID PRIMARY KEY DEFAULT gen_random_uuid(), product_id UUID REFERENCES products(id), hook TEXT, angle TEXT, platform TEXT, script TEXT, status TEXT DEFAULT 'draft', created_at TIMESTAMP DEFAULT NOW() ); CREATE TABLE weekly_reviews ( id UUID PRIMARY KEY DEFAULT gen_random_uuid(), review_period TEXT, summary TEXT, best_product_id UUID, worst_product_id UUID, recommendations TEXT, created_at TIMESTAMP DEFAULT NOW() ); CREATE TABLE ai_reports ( id UUID PRIMARY KEY DEFAULT gen_random_uuid(), report_type TEXT, summary TEXT, best_product_id UUID, worst_product_id UUID, recommendations TEXT, created_at TIMESTAMP DEFAULT NOW() ); 12. MVP Requirements Build the MVP first. The MVP should include: - Admin dashboard - Niche table - Product table - Product scoring form - AI-generated offer copy - Landing page generator - Experiment tracker - Weekly review report - AI decision engine - Mock integrations for Shopify, Stripe, suppliers, and ad platforms The MVP goal: Within the app, I should be able to manually enter 20 product ideas, score them, generate offer pages, track test results, and get a weekly AI recommendation. 13. Future Roadmap After MVP is complete, create a roadmap for: - Shopify API integration - Supplier API integration - TikTok ad data integration - Meta ad data integration - Google Trends integration - Social listening integration - Automated email flows - Automated creative generation - Customer support chatbot - Profit and cashflow forecasting - Inventory/supplier reliability monitoring - Automated A/B testing - Multi-language landing pages - Multi-currency support - Global shipping rules 14. Founder Report Format Every weekly report should answer: - What worked? - What failed? - What should be killed? - What should be improved? - What should be scaled? - Where was money wasted? - Which niche deserves more focus? - Which product deserves more testing? - What is the highest-leverage action for next week? 15. Final Instruction Build this like a serious founder tool, not a toy app. The system should help me think clearly, move fast, test offers, protect cash, and scale only what the data supports. Start with the MVP. Make the architecture clean. Make the dashboard beautiful. Make the logic practical. Make the product feel like an elite ecommerce war room.