99.5% accuracy · Catalog quality experts

Ecommerce Product Data Cleaning Services

Product data across your catalog is inconsistent - duplicate entries, wrong categories, missing attributes, and conflicting specifications are silently killing your conversion rates and search rankings. Acelerar’s data cleaning specialists audit, fix, and standardize your entire product catalog so every listing is accurate, complete, and ready to sell.

Product catalog data cleaning dashboard showing before and after views of product data with duplicates removed and attributes standardized
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)

What is ecommerce product data cleaning?

Ecommerce product data cleaning is the systematic process of identifying and correcting errors, inconsistencies, and gaps in your product catalog data. This includes removing duplicate product entries, standardizing attribute values (sizes listed as S/Small/Sm all unified to one format), filling missing fields like weight, dimensions, or material, correcting category assignments, fixing broken image links, and normalizing pricing across channels. Dirty product data degrades search filtering, creates a poor shopping experience, inflates inventory counts, and undermines customer trust. Cleaning your catalog is not a one-time task - it is an ongoing discipline that directly impacts conversion rates and revenue.

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 cleaning specialist vs. Acelerar

In-House (US)

$42K/yr

per year / per person

Salary, benefits, training, and equipment for one full-time US-based product data cleaning specialist with deduplication and attribute standardization skills

With Acelerar

$13K/yr

per year / per person

Fully loaded rate includes salary, infrastructure, validation tools, QA, and dedicated account manager for catalog data cleaning and normalization

Why product data cleaning drives ecommerce revenue

Higher Conversion Rates

Shoppers abandon products with incomplete or contradictory data. When specifications are accurate, images match descriptions, and attributes are consistent, customers buy with confidence. Clean data typically increases conversion rates by 10-25%.

Better Search & Filtering

Product filters only work when attribute data is standardized. If size values include S, Small, Sm, and small, your filters break. We normalize every attribute so shoppers find products through faceted search and category filters reliably.

Accurate Inventory Counts

Duplicate product entries create phantom inventory. You think you have 50 units of a product when you actually have 25 spread across two duplicate records. We identify and merge duplicates so your inventory numbers reflect reality.

Improved SEO Rankings

Duplicate product pages compete against each other in search results, diluting your ranking potential. Missing meta data and incomplete product descriptions signal low quality to search engines. Clean data means stronger, consolidated product pages.

Multi-Channel Consistency

Selling on your website, Amazon, eBay, and Walmart? Inconsistent data across channels confuses customers and violates marketplace policies. We standardize your product data so it is consistent everywhere it appears.

Reduced Return Rates

Incorrect product specifications are the number one cause of preventable returns. When weight, dimensions, material, and compatibility information are accurate, customers get what they expect and return rates drop.

From messy catalog to clean product data in 4 steps

1

Audit

We export and analyze your entire product catalog: identifying duplicates, inconsistent attributes, missing fields, broken images, and categorization errors. You receive a detailed quality report.

2

Clean

Our specialists fix every issue: merge duplicates, standardize attribute values, fill missing fields from manufacturer data, correct categories, and update broken links.

3

Validate

QA team verifies corrections against source data with automated validation rules and manual spot checks. Every cleaned record meets the 99.5% accuracy standard.

4

Deliver

Clean data is imported back into your platform or delivered in your preferred format. We provide a cleaning summary with metrics: records cleaned, duplicates removed, and fields filled.

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 Cleaning FAQs

Ecommerce product data cleaning is the process of auditing your entire product catalog to identify and fix data quality issues. This includes removing duplicate product entries, standardizing attribute values, filling missing fields, correcting category assignments, fixing image links, normalizing pricing data, and ensuring consistency across all sales channels. The goal is a catalog where every product record is accurate, complete, and formatted consistently.
Product data quality directly impacts revenue. Inaccurate data causes customers to leave product pages (lower conversion), creates misleading search filter results (frustrated shoppers), generates preventable returns (wrong specifications), inflates or deflates inventory counts (overselling or missed sales), and weakens SEO rankings (duplicate pages, missing metadata). Studies show that poor product data quality costs ecommerce businesses 10-20% in lost revenue annually.
We fix every common product data issue: duplicate product entries and SKUs, inconsistent attribute values (mixed size/color formats), missing product specifications (weight, dimensions, material), incorrect category assignments, broken or missing product images, incomplete meta titles and descriptions, conflicting pricing across channels, orphaned variant records, HTML formatting errors in descriptions, and special character encoding issues.
We use a combination of automated matching algorithms and manual review to identify duplicates. Products are matched on SKU, UPC/EAN, product title similarity, and image fingerprinting. Once duplicates are confirmed, we merge records by keeping the most complete data from each version, consolidate reviews and sales history, and redirect any duplicate URLs. You approve the merge strategy before we execute.
Yes. Attribute standardization is a core part of our cleaning process. We create a master attribute taxonomy for your catalog, then normalize values across every platform: size S/Small/Sm becomes one consistent value, color names are standardized, material descriptions follow a consistent format, and measurement units are unified. This ensures your filters and faceted search work correctly on every channel.
Timeline depends on catalog size and data quality. A catalog of 1,000-5,000 products typically takes 1-2 weeks for a full cleaning. Catalogs of 10,000-50,000 products take 3-6 weeks. Very large catalogs (100,000+) are scoped with phased timelines. We provide a specific estimate after the initial audit of your data quality.
We clean product data for Shopify, Amazon Seller Central, Magento, WooCommerce, BigCommerce, eBay, Walmart Marketplace, Etsy, PrestaShop, and custom ecommerce platforms. We work directly within your platform’s admin or via exported data files, depending on what’s most efficient for your catalog size.
Pricing depends on catalog size and data complexity. Small catalogs (under 2,000 products) start at $1,500-$3,000 for a full cleaning. Mid-size catalogs (5,000-20,000 products) typically cost $3,000-$8,000. Large catalogs are quoted based on the audit findings. Ongoing monthly data maintenance retainers start at $1,000. Contact us with your catalog details for a precise quote.
Yes. One-time cleaning is valuable, but product data degrades continuously as new products are added, suppliers update specifications, and pricing changes. We offer monthly maintenance retainers that include regular quality audits, new product data validation, attribute standardization for new additions, and ongoing duplicate detection. This prevents data quality from degrading between major cleaning projects.
Clean product data improves conversion in several measurable ways: accurate specifications reduce buyer hesitation, consistent attributes make search filters work correctly, complete product information answers questions that otherwise cause page abandonment, deduplicated listings consolidate reviews and social proof, and correct categorization ensures products appear in the right search results. Merchants typically see 10-25% conversion rate improvement after a comprehensive catalog cleaning.

Catalog data holding you back?

Get a free data quality audit and cleaning quote for your product catalog in under 48 hours.

No commitment required. We respond within 24 hours.