VIN data that's incomplete. Vehicle specs formatted differently across every dealer feed. Parts attributes that don't match any recognised taxonomy. MercuryMinds handles automotive catalog data entry, VIN enrichment and dealer inventory normalisation — built on real production work running hgvtraders.com.
VIN Data Enrichment
The Vehicle Identification Number encodes make, model, year, engine type, transmission, country of manufacture, assembly plant and a unique serial number. Most dealer inventory systems capture the VIN but don't decode it into searchable vehicle attributes — leaving listing data incomplete and unfilterable.
VIN Decode
Decodes VIN numbers against NHTSA, DVLA and international vehicle databases to extract and populate structured vehicle attributes — make, model, year, body style, engine displacement, fuel type, transmission, drivetrain, trim level and GVWR for commercial vehicles. Attributes mapped to your listing platform's field schema.
Data Normalisation
Dealer inventory data arrives in different formats from different sources — DMS exports, auction feeds, manufacturer feeds, manual spreadsheets. MercuryMinds normalises all incoming formats into a single consistent vehicle data schema before uploading to the marketplace or portal, eliminating the spec inconsistencies that make inventory unsearchable.
HGV / Commercial
HGV and commercial vehicle listings require specialist data fields not present in standard car listing schemas — GVWR, payload, axle configuration, body type (curtainsider, flatbed, box van, tipper), engine hours for plant machinery, MOT/service history status and category of operator licence required. Built on production work for hgvtraders.com.
Dealer Inventory
Bulk upload of dealer inventory to marketplace portals, classified sites and dealer websites — handling sold/available status updates, price change propagation and new arrivals. Supports both batch upload workflows (daily/weekly DMS export) and real-time API sync for platforms that support it.
Parts
Parts listing creation with fitment data — make/model/year compatibility tables, OEM part numbers, aftermarket part numbers, interchange data and supersession chains. Formatted for Amazon's automotive parts category, eBay Motors parts fitment and dedicated parts marketplace schemas. Supports ACES/PIES data standards.
Imagery
Batch processing of dealer photography for marketplace use — consistent naming conventions, resizing to platform specifications, background standardisation for studio shots and metadata tagging. Handles 360° image sequences for platforms that support walk-around photography.
Production Proof
hgvtraders.com is a commercial vehicle and HGV marketplace that MercuryMinds built and operates. The platform lists trucks, vans, plant machinery and commercial trailers — vehicle types with highly complex data requirements and specialist data fields that don't exist in standard ecommerce schemas.
The automotive catalog expertise comes from this production work — VIN decoding, HGV-specific attribute schemas, dealer inventory normalisation and commercial vehicle photography standards are all live operational knowledge, not theoretical capability.
Automotive Marketplace Services →Project reference · hgvtraders.com
A commercial vehicle and HGV marketplace — a platform MercuryMinds built and manages. Covers trucks, vans, plant machinery, trailers and commercial vehicle parts across the UK and European markets.
What the build proved
HGV and commercial vehicle data has a completely different attribute schema to passenger cars. GVWR, axle configuration, payload, body type, engine hours — these fields don't exist in generic automotive platforms. MercuryMinds built the data model, the VIN enrichment pipeline and the dealer feed normalisation from scratch.
What it transfers to your project
VIN decoding, dealer feed normalisation, commercial vehicle attribute schemas and parts fitment data management — all operational knowledge from a live marketplace, not documentation from an automotive data standard.
Yes. VIN data enrichment is a core automotive catalog service — decoding VIN numbers against NHTSA, DVLA and international databases to extract structured vehicle attributes. A standard 17-character VIN encodes the country of origin, manufacturer, vehicle type, engine, model year, assembly plant and serial number. MercuryMinds decodes this into searchable listing attributes (make, model, year, engine, transmission, drivetrain, trim) and maps them to your platform's field schema. HGV and commercial vehicle VINs are handled separately with the additional fields relevant to commercial vehicles — GVWR, body type, axle configuration, payload capacity.
Yes. MercuryMinds handles dealer inventory data entry and upload in bulk — accepting DMS exports, auction feed files, manufacturer CSV feeds and manual spreadsheets. All incoming formats are normalised into a consistent vehicle data schema before upload. Ongoing sync is available for dealers with daily or weekly inventory updates — new arrivals added, sold vehicles removed, prices updated. Both passenger car and commercial vehicle inventory are handled, with specialist fields for HGV, plant machinery, trailers and commercial vehicles.
Vehicle specification normalisation uses a combination of VIN decoding, lookup table matching against known make/model/trim combinations, and rule-based standardisation for free-text fields. The most common problems are inconsistent naming ("Ford Transit" vs "FORD TRANSIT" vs "Transit Ford"), missing fields that can be derived from the VIN, conflicting data between the VIN decode and the dealer's manual entry, and non-standard field values (engine size entered as "2.0" vs "2000cc" vs "2.0L"). MercuryMinds builds a normalisation pipeline specific to your data sources and target schema — the rules are written for your specific inconsistency patterns, not applied from a generic automotive data standard.
Yes. Auto parts data entry includes fitment data — the make/model/year/trim compatibility tables that allow buyers to search by their vehicle and confirm the part fits. MercuryMinds handles OEM part number entry, aftermarket cross-reference numbers, interchange data and supersession chains. Parts data is formatted for Amazon's automotive parts category (which uses ACES/PIES standard fitment data), eBay Motors parts listings and dedicated parts marketplace schemas. Industrial parts and plant machinery components with non-standard classification are handled separately from passenger vehicle parts.
Related Services
Ready to Fix Your Vehicle Data?
Tell us how many vehicles or parts are in your inventory, what vehicle types are involved (passenger cars, HGV, commercial, plant, parts), what format your source data is in and what the most critical data quality problem is. We'll come back with the right approach.