Verintra Feed Optimizer: Product Feed Management SaaS
I'm a performance marketer, so I built the tool I always wished my feeds had, a multi-tenant SaaS that validates, enriches, scores, and syndicates any store's product catalog to every major ad channel. Shipped solo, full-stack.
The problem
If you've ever run Google Shopping or a Meta catalog campaign, you know where the budget quietly leaks: the feed. Broken attributes, rejected products, missing GTINs, generic titles, wrong taxonomy nodes, none of it shows up as a line item, but all of it drags ROAS.
Most merchants find out only when products get disapproved, and the "fix" is a marketer hand-editing a spreadsheet or waiting on an engineer. The data layer between a store and the ad platforms is where performance is won or lost, and almost nobody owns it well. I lived this on the campaign side. So I built the layer.
The approach
One platform that owns the catalog from source to channel, connect → validate → enrich → score → syndicate → measure, with a feedback loop from real revenue.
- Connect any store, Shopify, WooCommerce, Magento, BigCommerce, or any XML/CSV/JSON/Google Sheets URL, with scheduled auto-sync.
- Validate against a 30+ rule health engine that turns raw feed errors into a prioritized, plain-language action list (critical → warning → info).
- Enrich with AI: channel-compliant titles and descriptions, extraction of missing structured attributes, and automatic mapping to the correct Google product-taxonomy node.
- Score every product with Verintra Score, a 0–100, catalog-relative rating that intelligently renormalizes weights when a metric is unmeasurable, so products are never unfairly penalized for missing data.
- Syndicate spec-compliant exports to the major channels and submit straight to Google Merchant Center.
- Measure by reading performance back from GA4, so optimization is driven by revenue, not guesswork.
What I built (solo, full-stack)
- Fix-My-Feed health engine, a 30+ rule validator with prioritized, human-readable output, so a merchant always knows the highest-impact fix next.
- Verintra Score, the weight-renormalizing 0–100 product score across conversion, CTR, revenue, margin, and attribute fill.
- AI optimization (Gemini 2.5 Flash), titles, descriptions, attribute extraction, taxonomy mapping, plus product embeddings, semantic search, and AI "feed readiness" scoring.
- Multi-channel syndication, Google Shopping, Meta/Facebook, Microsoft, TikTok, Pinterest, Criteo, plus European and Turkish price-comparison engines (Idealo, Cimri, and more) from a channel-spec/preset system.
- Rules engine, supplemental feeds & change-sets, bulk-edit thousands of SKUs safely with a preview-then-apply workflow; custom labels, ghost-product detection, product segments.
- Direct integrations, Google Merchant Center (submission + live issue mapping) and GA4 (per-SKU performance), all OAuth tokens encrypted at rest.
- A/B testing engine with statistical-significance calculation, and dual billing, Stripe for international, iyzipay for the Turkish market.
Built for production from day one: multi-tenant data isolation, AES-256-GCM encryption for all OAuth tokens, Zod validation + SSRF protection on every input, per-user/per-IP rate limiting, a repository-pattern data layer with zero any types, and a Vitest test suite, ~12,000 lines of TypeScript across 13 feature areas, 19 API route groups, and a 14-model schema.
Impact
This is a pre-launch product, so the honest headline is capability, not customers:
- End-to-end, shipped solo. Design, frontend, backend, data model, integrations, security, billing, one person, production-grade.
- A real moat for performance marketers. It encodes the feed knowledge most growth teams lack: attribute fill, taxonomy mapping, disapproval triage, where ROAS actually hides.
- Built to sell, not just to demo. Multi-tenant isolation, dual-market billing, and legal pages are in place because the goal is paying customers in 2026.
Tech
What it demonstrates
The full loop most candidates only claim: a performance marketer who understands where ad budget leaks and can build the software that stops it, product thinking, full-stack engineering, and the commercial instinct to ship something people pay for.