Deduplication · Catalog consolidation

Ecommerce Product Data Matching Services

Your product catalog is full of duplicates, near-duplicates, and mismatched records from multiple data sources. The same product appears under different names, different suppliers list identical items with conflicting specifications, and your inventory counts are unreliable because the same SKU exists in three different forms. Acelerar’s data matching specialists clean, match, and consolidate your product records into a single source of truth.

Product data matching interface showing duplicate product records being identified, compared, and merged into a single clean record
500+
Teams Deployed
99.5%
Accuracy SLA
70%
Avg Cost Savings
7-Day
Team Deployment
4.9 out of 5·from 120+ verified reviews
Clutch (4.9)Google (4.8)GoodFirms (5)

Why duplicate and mismatched data costs you money

Duplicate product records inflate your catalog, confuse customers, and split sales history across multiple listings. When the same product exists under different names or SKUs, you cannot accurately track inventory, your analytics are unreliable, and customers may buy from a poorly optimized duplicate instead of your best listing. Mismatched data from different suppliers creates conflicting specifications that erode trust. Product data matching identifies duplicate and near-duplicate records, matches products across data sources, and consolidates them into clean, authoritative records that you can trust for inventory management, pricing decisions, and marketplace listings.

The e-commerce outsourcing market

E-commerce operations outsourcing is growing as online retail scales globally.

$854.6B
Global BPO market size in 2025
Grand View Research, 2024
83%
Of executives leverage AI in outsourced services
Deloitte, 2024
$87K
Average per-employee savings from outsourcing
IAOP, 2023

In-house data matching analyst vs. Acelerar

In-House (US)

$48K/yr

per year / per person

Salary, benefits, training, and equipment for one full-time US-based data matching analyst with deduplication, UPC reconciliation, and catalog consolidation skills

With Acelerar

$15K/yr

per year / per person

Fully loaded rate includes salary, infrastructure, matching algorithms, QA, and dedicated account manager for product data matching and deduplication

Why brands trust Acelerar for product data matching

Duplicate Detection & Resolution

We identify exact and near-duplicate product records using multi-attribute matching: product names, SKUs, UPCs, images, dimensions, and descriptions. Duplicates are flagged, reviewed, and merged into a single authoritative record with the best data from each source.

Cross-Marketplace Matching

Selling the same products on Amazon, eBay, Shopify, and Walmart? We match your product records across all platforms so you have a unified view of each product, consistent data across channels, and accurate cross-channel inventory tracking.

Supplier Data Reconciliation

Multiple suppliers often provide conflicting data for the same product. We reconcile supplier records, identify the most accurate specifications, resolve naming inconsistencies, and create a golden record that reflects the truth about each product.

UPC & Identifier Matching

We use UPC, EAN, GTIN, MPN, and ASIN identifiers to match products with high confidence. When identifiers are missing or inconsistent, we use attribute-based matching algorithms that compare product names, descriptions, and specifications.

Catalog Consolidation

After a merger, acquisition, or multi-supplier integration, product catalogs need to be consolidated. We merge overlapping catalogs into a single unified catalog with no duplicates, consistent formatting, and clean hierarchy.

Match Confidence Scoring

Not every match is certain. We provide confidence scores for each match so you can auto-approve high-confidence matches, review medium-confidence matches, and investigate low-confidence candidates. This gives you control over the matching accuracy.

From messy data to a clean catalog in 4 steps

1

Ingest

We import your product data from all sources: e-commerce platforms, supplier feeds, PIM systems, spreadsheets, and legacy databases. Every data source is normalized into a common format for comparison.

2

Match

Our matching process compares products across multiple attributes: identifiers, names, descriptions, images, and specifications. Each potential match receives a confidence score based on the strength of the match.

3

Merge

Confirmed matches are merged into golden records. We select the best data from each source: the most complete description, the most accurate specifications, and the highest quality images. Conflicts are flagged for your review.

4

Deliver

The clean, deduplicated catalog is delivered in your preferred format and synced back to your platforms. You receive a matching report showing all merges, conflict resolutions, and remaining candidates for review.

We work with your e-commerce platforms

Our teams are trained on the platforms you already use.

What our e-commerce clients say

Acelerar handled our entire catalog migration (50,000+ SKUs) without a single missed deadline.

The Acelerar team is a self-sustaining machine. They've become an extension of our own team.

We needed reliable, fast data entry at scale. Acelerar delivered consistent quality from day one, no ramp-up time needed.

Where e-commerce outsourcing is heading

E-commerce operations are increasingly handled by specialized outsourcing teams with AI capabilities.

2025
$854.6B
Global BPO market size
Grand View Research, 2024
2030
$1.22T
Projected global BPO market at 8.6% CAGR
Grand View Research, 2024
2030
66%
Of tasks still need human skills or human+AI combo
McKinsey, 2023
ISO 27001 Certified
ISO 9001:2015
NDA for Every Team Member
Encrypted Data Transfer

Product Data Matching FAQs

Product data matching is the process of identifying when two or more product records in your catalog represent the same physical product. This includes exact duplicates with identical data, near-duplicates with slightly different names or descriptions, and cross-source matches where the same product appears in data from different suppliers or platforms. Matching enables deduplication, catalog consolidation, and unified inventory management.
When universal product identifiers are not available, we use attribute-based matching that compares multiple product characteristics: brand name, product title, model number, dimensions, weight, material, color, and other specifications. We also use image comparison and description analysis to identify matches. Each match receives a confidence score so uncertain matches can be reviewed manually.
Our matching accuracy depends on the data quality but typically exceeds 95 percent for high-confidence matches. We use a tiered approach: high-confidence matches based on identifier matching are auto-approved, medium-confidence matches based on attribute similarity are flagged for review, and low-confidence candidates are presented separately. This ensures you never merge products incorrectly.
Yes. We handle multilingual product matching by using universal identifiers like UPC and GTIN when available, and by using translated attribute comparison for attribute-based matching. This is common when matching products between domestic and international supplier catalogs or when consolidating catalogs from different regional marketplaces.
Timeline depends on catalog size and data quality. A 5,000-product catalog typically takes 1 to 2 weeks. A 50,000-product catalog takes 3 to 6 weeks. Very large catalogs with over 100,000 products or poor data quality may take 6 to 10 weeks. We provide a detailed timeline estimate during the assessment phase based on your specific data.

Ready to clean up your product catalog?

Get a free data quality assessment and custom quote for your product data matching project.

No commitment required. We respond within 24 hours.