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Spare Parts & Manufacturing
Fitment SearchOEM Cross-ReferenceParts Catalog

Desenvolvimento de Sites para Fabricantes de Peças de Reposição

Suas Peças Voltam Porque Compradores Não Encontram o Que Encaixa

40%
Fewer Returns
With fitment verification
<200ms
Search Speed
Across 500K+ SKUs
95+
Lighthouse Score
Performance target
3x
Conversion Lift
vs. generic ecommerce
What Actually Stops Parts Returns — And What Doesn't

A buyer lands on your parts catalog. They enter a year, make, and model. Your fitment engine filters 500,000 SKUs down to the twelve that match their equipment — before they add anything to cart. That's how spare parts manufacturer websites cut return rates from 12% to under 3%. These aren't catalog sites with product filters bolted on. They're compatibility engines. VIN lookup, supersession chains, exploded diagram navigation, OEM cross-reference tables — the entire frontend is built to surface only parts that fit. Your warehouse stops processing wrong-part returns. Your support line stops fielding fitment questions. Your distributors stop calling to verify numbers. The site does the work.

Onde os projetos falham

Parts return rates average 12-15% On low-ticket items, that wipes out your margin entirely — and you're still paying warehouse staff to process every one of those mistakes.
If your site doesn't let buyers search by year, make, and model, they'll find a competitor who does You lose the sale and the repeat customer.
Outdated catalogs sitting in spreadsheets and ERPs cause overselling, backorders, and frustrated dealers Channel trust erodes fast when that happens repeatedly.
Shopify and WooCommerce weren't built for complex part relationships Fitment logic needs more than a plugin — and those plugins break on updates anyway.
When exploded diagrams and technical docs aren't online, customers call your support line for every lookup Those calls cost $5-15 each. They shouldn't need to call at all.
If distributors can't find your OEM cross-references or supersession data, they'll source from whoever surfaces it first That won't be you.

Conformidade

Year/Make/Model Fitment Engine

Multi-level vehicle selection filters your entire catalog down to confirmed-fit parts only. Built on ACES and PIES data standards for automotive aftermarket compatibility.

VIN Decoder Integration

A buyer pastes their VIN and sees exact-match parts for their specific build — trim, engine, everything. No guesswork, and typically 30-50% fewer fitment-related returns.

OEM Cross-Reference Search

We map your part numbers to OEM numbers, competitor numbers, and superseded part numbers. Buyers find your parts regardless of what number they're searching.

Interactive Exploded Diagrams

SVG-based assembly diagrams let buyers click a component and add it straight to cart. It mirrors how technicians actually look up parts — fewer errors, faster orders.

ERP & Inventory Sync

Real-time stock feeds from your ERP or warehouse system prevent overselling. We support SAP, NetSuite, and custom API integrations with sub-minute sync intervals.

Dealer & Distributor Portal

Tiered pricing, bulk ordering, and account-specific catalogs for your B2B channel. Role-based access keeps retail and wholesale experiences completely separate.

O que construímos

Filter half a million SKUs by application, category, brand, price, and live stock in under 200ms

Buyers only see parts that fit their equipment — fewer returns, fewer support calls, less warehouse labor on mistakes

Route discontinued part searches to current replacement numbers with full supersession history visible

Distributors find current part numbers instantly without calling your team to verify supersession chains

Process bulk distributor orders via CSV upload — instant availability check, pricing, and populated cart

High-volume orders get processed in one step instead of line-by-line email back-and-forth

Link installation guides, spec sheets, and safety data sheets directly from product pages with full-text search

Technical documentation becomes discoverable — buyers find torque specs and diagrams without picking up the phone

Route orders to the nearest stocked warehouse and display accurate per-item delivery windows

Split shipments route intelligently — customers see real lead times instead of generic 5-7 day promises

Flag potential fitment mismatches before checkout and prompt buyers to confirm vehicle details

Wrong-part purchases get caught at the verification step — you stop refunding and restocking items that never should have shipped

Nosso processo

01

Data Architecture & Catalog Audit

We start by mapping your product data — part numbers, fitment tables, cross-references, supersessions, and media assets. We define the schema and find the gaps before writing a single line of code.
Week 1-2
02

Fitment Engine & Search Build

Then we build the compatibility database and search infrastructure. Year/make/model filtering, VIN decode integration, and OEM cross-reference logic all get tested against your real catalog data.
Week 3-5
03

Storefront & Portal Development

Frontend development covers both retail and B2B dealer portals — exploded diagrams, product pages, cart logic, and tiered pricing, all wired to the fitment engine and your ERP.
Week 5-8
04

Integration & Data Migration

Next comes integration: ERP inventory feeds, payment processing, shipping calculators, and tax engines. We migrate your existing catalog data with full validation against fitment tables.
Week 8-10
05

Launch & Optimization

We launch in stages with real order testing. Post-launch monitoring catches search dead-ends and fitment gaps. You get 30 days of included support to tune performance and conversion.
Week 10-12
Next.jsSupabaseVercelAlgoliaShopify Storefront APIPostgreSQLCloudinary

Perguntas frequentes

Como funciona a busca por encaixe em um site de peças?

A busca por encaixe funciona em um banco de dados estruturado que mapeia cada peça para veículos ou equipamentos compatíveis por ano, marca, modelo, motor e versão. Quando um comprador seleciona seu veículo, o sistema consulta esse banco de dados e retorna apenas peças com encaixe confirmado. Construímos isso usando padrões ACES/PIES para automotivo ou esquemas customizados para equipamentos industriais.

Vocês conseguem integrar decodificação de VIN no nosso catálogo?

Sim. Integramos APIs de decodificação de VIN de terceiros que extraem ano, marca, modelo, motor, versão e data de produção de um VIN de 17 caracteres. Esses dados decodificados filtram automaticamente seu catálogo para peças com encaixe exato, o que elimina erros de seleção e tipicamente reduz devoluções relacionadas a encaixe em 30-50%.

Como vocês lidam com referência cruzada OEM e números de peças descontinuadas?

Construímos uma tabela de referência cruzada que mapeia seus números de peça internos para números OEM, números de concorrentes e números descontinuados. Busque qualquer um desses e o comprador chega ao seu produto ativo atual. O histórico completo de substituição permanece visível através de cadeias de descontinuação rastreadas.

E se nossos dados de produtos estiverem bagunçados ou espalhados por vários sistemas?

É comum. A primeira fase é uma auditoria de catálogo onde mapeamos suas fontes de dados — exportações de ERP, planilhas, feeds de fornecedores — e construímos um esquema normalizado. Scripts de migração limpam, removem duplicatas e validam seus dados de peças contra tabelas de compatibilidade antes de qualquer coisa entrar em produção. Você acaba com dados mais limpos do que começou.

Vocês construem portais B2B para distribuidoras com preços por nível?

Sim. Portais de distribuidores e revendedores recebem preços contratuais, pedidos em massa baseados em CSV e catálogos específicos por conta. Clientes de varejo veem preços padrão na loja virtual pública. Os dois lados compartilham o mesmo mecanismo de encaixe e dados de inventário por baixo.

Quanto tempo leva para construir um site de peças de reposição?

A maioria dos projetos é lançada em 10-12 semanas. O tamanho do catálogo e a qualidade dos dados são as principais variáveis. Um catálogo limpo de 5.000 SKUs com dados de encaixe estruturados se move rapidamente. Um catálogo de 100.000 SKUs que precisa de normalização pesada leva mais tempo. Definimos o cronograma durante a fase de avaliação.

Spare Parts Websites from $8,000
Fixed-fee. Fitment engine included. 30-day post-launch support.
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