Platform Liberation
Five buyback brands. One codebase. Fair offers enforced at the system level.
Most electronics buyback platforms fail in one of two ways: quote high and deduct aggressively at receipt, or quote conservatively and lose to competitors. We built a platform where fair pricing is a system constraint, not a policy — and scaled it to five brands from a single Next.js codebase.
The Problem
“Quote high online, deduct at receipt. That one pattern kills more buyback businesses than anything else.”
A vertically integrated electronics reseller needed five customer-facing buyback brands targeting different segments — general laptops, MacBooks, gaming laptops, local repair market, iPhones — each with its own SEO identity, pricing rules, and email branding. Building five separate codebases was off the table. The pricing had to be accurate: quote high and deduct later is the fastest way to destroy trust in this category.
What Was Built
Multi-Site Architecture
Next.js 14 + Edge Middleware- —Five domains share one Next.js monorepo — middleware resolves incoming domain to site_id at the edge before any route handler runs
- —Branding, email routing, category filtering, pricing display all driven by site_id — no duplicated code
- —Adding a sixth site is a database and DNS operation — core logic unchanged
- —Per-site category filtering: MacBook site shows only Apple devices, iPhone site shows only phones and tablets
Pricing Engine
Supabase + Hourly Cron- —All prices sync from upstream wholesale database via Supabase-to-Supabase connection — no API polling, no rate limits, no stale cache
- —$0 upstream price = hard DO NOT BUY signal — no fallback pricing, no proxy models, no exceptions
- —Three-layer pricing: base price × condition multiplier − defect deductions, all category-aware
- —Deduction percentages are admin-only — customers see the dollar offer, not the math behind it
Sara AI — Quote Assistant
Claude Haiku + Extraction Pipeline- —Customer types natural language — Sara extracts brand, model, RAM, storage via Haiku before hitting the database
- —Extraction step eliminated the entire class of failures from noisy customer language polluting search queries
- —Exact model match with non-zero price: Sara quotes and links to full quote flow. No match: routes to brand/category page — never dead-ends
- —Order lookup by order number in-chat — customers check status without leaving conversation
Operational Intelligence + Retention
Resend + Supabase + EasyPost- —Every new order triggers admin email: payout, upstream wholesale price, estimated margin, eBay sold comps, parts candidate flag
- —Quote expiry at 14 days with automated sequence: reminder day 3, follow-up day 7, last-chance day 10
- —Win-back cron: expired orders re-engaged with current price — if price increased, customer is told explicitly
- —$20 shipping minimum enforced at library level — runs before EasyPost is called, cannot be bypassed by alternate entry points
Search Performance
LIVEPulled live from Google Search Console API · Jul 31, 2026, 8:14 PM UTC
Top Pages (90 days)
Top Queries (90 days)
Key Lessons
The $0 rule is non-negotiable.
One instance of proxy pricing — quoting based on a similar model because the exact model had a $0 price — resulted in a cancelled order and a customer apology. The rule was hardened: $0 means decline, always.
Extraction before search.
Raw customer language is noisy. A lightweight AI extraction step between customer input and database query dramatically improved match rates without meaningful cost increase.
Safety checks belong in the library, not the route.
The $20 minimum was in the standard label function but missing from the bulk order route. Safety checks live at the lowest possible layer so they cannot be bypassed by alternate entry points.
Ready?