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Spare Parts & Manufacturing
Fitment SearchOEM Cross-ReferenceParts Catalog

スペアパーツメーカー向けウェブサイト開発

買い手が適合する部品を見つけられないため、あなたの部品が返品されている

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.

プロジェクトが失敗する理由

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Outdated catalogs sitting in spreadsheets and ERPs cause overselling, backorders, and frustrated dealers Channel trust erodes fast when that happens repeatedly.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.

コンプライアンス

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.

構築する内容

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

私たちのプロセス

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

よくある質問

パーツウェブサイトの適合検索はどのように動作しますか？

適合検索は、年式、メーカー、モデル、エンジン、トリムで互換性のある車両または機器に対して、あらゆる部品をマッピングする構造化データベース上で動作します。買い手が自分の車両を選択すると、システムはそのデータベースをクエリし、確認済みの適合部品のみを返します。自動車向けはACES/PIES標準を使用し、産業機器向けはカスタムスキーマを構築します。

VIN復号化を部品カタログに統合できますか？

はい、可能です。17文字のVINから年式、メーカー、モデル、エンジン、トリム、製造日を抽出するサードパーティVIN復号化APIを統合します。その復号化されたデータはカタログを正確にマッチさせるため、選択エラーを排除し、通常は適合関連の返品を30～50%削減します。

OEM相互参照と廃止部品番号にどのように対応していますか？

内部部品番号をOEM番号、競合他社番号、廃止部品番号にマッピングする相互参照テーブルを構築します。これらのいずれかを検索すると、買い手は現在のアクティブな製品にたどり着きます。完全な交換履歴は追跡される廃止チェーンを通じて表示されたままです。

製品データがもし散在していたり、複数のシステムに分散していたらどうしますか？

これはよくあります。最初のフェーズはカタログ監査です。ERP出力、スプレッドシート、サプライヤーフィードなどのデータソースをマッピングし、正規化されたスキーマを構築します。移行スクリプトは、本番環境に移行する前に部品データを適合テーブルに照らして清掃、重複排除、検証します。結果として、開始時よりもクリーンなデータが得られます。

段階別価格設定を備えたB2Bディーラーポータルを構築していますか？

はい、構築します。ディーラーおよび流通業者ポータルは、契約価格、CSVベースの一括注文、アカウント固有のカタログを備えています。小売顧客は公開ストアフロントで標準価格を見ます。どちらも同じ適合エンジンと在庫データを共有します。

スペアパーツウェブサイトの構築にはどのくらいの時間がかかりますか？

ほとんどのプロジェクトは10～12週間で立ち上がります。カタログサイズとデータ品質が主な変数です。構造化された適合データを持つクリーンな5,000 SKUカタログは迅速に進みます。大幅な正規化が必要な100,000 SKUカタログにはより長い期間がかかります。評価フェーズ中にタイムラインを確定します。

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