How Data Validation Transforms eCommerce Businesses
In 2025, approximately 2.77 billion people—or about 33% of the world’s population—are expected to shop online, and global eCommerce sales are projected to reach between $6.8 and $7.4 trillion.
As the industry generates massive volumes of information, data validation becomes a crucial aspect of managing product content. It ensures that product data, consumer reviews, and contact details are accurate, verified, and ready for omnichannel distribution.
Let’s review the procedure for validating data, types of validation, its benefits for businesses, and some tips for increasing the quality of information.
What Is Data Validation?
Types Of Data Validation
Every piece of information undergoes multiple checks in the process of validation. Here is a list of all the common data validation types:
- Data type check. The first is the field type check, which ensures that, for example, letters are not inserted in a field for numbers only. Another constituent of this check is input validation — making sure that the input is error-free and does not have logical mistakes.
- Code check. This includes checks for required fields (ensuring that all the mandatory fields are filled) and attribute validation (verifying information against a list of attributes and seeing if the required attributes match).
- Range check. Also known as an attributes range check, this ensures that attributes stay within a certain range of values.
- Format check. This type of check ensures that inputted records precisely fit the predefined format. For example, an international phone number has a fixed format: + country code – (area code) – 3-digit prefix – 4-digit subscriber number. Any deviations, like the absence of a country code, are considered errors.
- Consistency check. This involves verifying data against a list of values that contain formatting rules and seeing if specified properties match. This check confirms that the input is logically consistent.
- Uniqueness check. This includes checking the uniqueness of specific attributes, such as brands, serial numbers, or MPN (Manufacturer Part Number), and making sure they are not entered into a database more than once.
Data validation tools perform essential quality reviews that ensure correct information processing.
Impact of Data Validation on Your eCommerce Business
The eCommerce industry widely incorporates automated systems that gather information with minimal to no human involvement. But errors are not unheard of, and they interfere with providing quality services to customers.
Let’s review ways in which data validation benefits business operations.
#1. Cost Impact
Clean records help reduce unnecessary expenses in two major ways. The first way is by improving last-mile delivery — getting orders to the customer’s doorstep, which is the final stage of the supply chain. A courier service might deliver goods to the wrong destination if a customer’s contact details are inputted incorrectly and not verified.
Moreover, efficient product data validation helps prevent cases of fraud by checking the authenticity of a client’s ID, email address, and phone number. This procedure ensures that one customer doesn’t get another customer’s package or intentionally claim the loss of a delivered package. KYC and AML checks, now integrated into most eCommerce platforms via automated identity verification APIs, add a critical layer of protection against payment fraud.
#2. Increased Earnings
The data validation process can increase the revenue of an eCommerce business in several ways. It improves the effectiveness of email and promotional campaigns by reducing the number of wrongly addressed or poorly targeted advertisements. It also leads to a higher return per dollar invested (ROI) — a financial indicator showing how well market initiatives impact a company’s revenue.
Another way to increase eCommerce business revenue is audience segmentation. This is simply dividing people into subgroups as per predefined criteria: age, preferences, location, etc. This can be done as part of product data validation. As a rule of thumb, consumers respond better to more customized offers. Segmenting the audience will improve outcomes for targeted marketing campaigns.
#3. Customer Satisfaction
Implementing data validation techniques is a great way to improve customer satisfaction. One such technique is managing holistic customer profiles. These profiles contain relevant information about a customer’s interactions with your business, from the placement of the first order to service incidents. Ensuring the accuracy of personal information contributes to the effectiveness of advanced analytics, such as determining the customer’s behavioral patterns or tracking changes in preferences. As a result, it helps you generate better marketing offers, improving your service.
Why Product-Data Validation Matters in 2025
In today’s dynamic eCommerce environment, product-data validation is no longer just a back-office hygiene task — it’s a direct driver of conversion, customer trust, and operational scalability. With the proliferation of sales channels and the rise of AI-generated content, poor data quality can quickly cascade into lost revenue, product delistings, or customer churn.
In 2025, 87% of online shoppers say that the accuracy of product information is the single most important factor in their purchasing decision. Furthermore, 53% of U.S. consumers abandon a shopping cart when product descriptions lack essential details such as images, specifications, or dimensions. These figures underline how a single missing attribute — like a size chart or materials list — can halt the buyer journey entirely.
For B2B companies, the challenge is even greater. A McKinsey study highlights that 72% of B2B firms still struggle with fragmented or outdated product data, which leads to decisions based on stale information, duplicated entries, and inconsistent records across platforms. This is especially critical when product assortments are syndicated across hundreds of marketplaces and retailer websites, each with their own formatting and taxonomy requirements.
Add to this the rise of AI-generated product listings — and the need for strong, automated validation becomes even more apparent. Without validation, AI can propagate incorrect information at scale, damaging brand reputation.
That’s why modern brands rely on eCommerce data validation monitoring systems that continuously track data accuracy and flag anomalies in real time. Validation isn’t a one-time action — it’s an always-on process woven into every stage of your digital shelf lifecycle.
eCommerce Data Validation Strategy 2025
As the complexity of eCommerce ecosystems grows in 2025, businesses need more than basic field validation — they need structured, layered, and automated strategies to handle data at scale. Here’s a five-step approach to building a future-ready data validation system:
1. Map Your Data Supply Chain. Identify every data ingestion point: supplier feeds, manual CSV uploads, AI-generated content, API connectors. Document ownership and responsibility across your teams. This transparency is the foundation of scalable validation.
2. Implement a Layered Rules Model. Validation should happen in three distinct layers:
- Layer 0 – Technical Syntax:
Validate file formats (CSV, XML, JSON), GTIN formats, and schema compliance via tools like GDSN integration. - Layer 1 – Business Rules:
Apply rules that ensure critical fields are populated, product categories are correctly assigned, and values fall within defined ranges (e.g., price or size limits). - Layer 2 – Channel-Specific Rules:
Align product data with marketplace requirements: eBay item specifics, Amazon Seller Solution Hub standards, or TikTok Shop formats.
3. Shift Left — Validate Early. Embed validation directly into supplier portals or self-service interfaces to prevent bad data from entering your system. This “shift-left” approach saves time and reduces manual cleanup downstream.
4. Instrument the Validation Process. Streamline performance monitoring by emitting validation events into your PIM dashboards. This enables real-time ecommerce data validation monitoring across thousands of SKUs and attributes.
5. Automate Remediation with AI. Use AI to auto-suggest fixes for missing fields, image errors, or formatting issues. Escalate complex cases to product content managers via Slack or Jira for human-in-the-loop resolution.
Validation is not a one-off task. It’s a living system that scales with your product catalog, distribution network, and customer expectations. Brands using advanced strategies like this reduce time-to-market, lower return rates, and improve conversion.
eCommerce Data Validation Metrics To Track
You can’t improve what you don’t measure — and that’s especially true for product data quality. In 2025, successful eCommerce businesses rely on a set of clearly defined data-validation metrics to monitor progress, reduce manual intervention, and drive automation.
Below are the key metrics every retailer or brand should track to ensure that their product content meets both internal and external standards.
| Metric | Target | Why it matters / how to calculate |
| Accuracy | ≥ 99% | % of attributes matching an authoritative source (e.g., GS1, manufacturer spec). |
| Completeness | 100% required fields | % of mandatory fields populated before status is marked “Ready for Publication.” |
| Consistency | Zero conflicts | Number of SKUs where variant-level data contradicts the parent product data. |
| Timeliness / Freshness | ≤ 24 h lag | Difference between the last source update and the current PIM timestamp. |
| Validity | 100% | % of fields that pass formatting/enum rules (e.g., ISO-2 country codes, accepted date formats). |
| Duplication Rate | < 0.1% | Number of duplicate SKUs per 10k listings using hash or fuzzy-match algorithms. |
| First-Time Pass Rate (FTPR) | ≥ 95% | % of SKUs approved without manual rework — a leading indicator of supplier data quality. |
| Business-Impact Lag | ↓ trend | Time between validation fail and fix applied — shows velocity of your remediation workflow. |
How To Use These Metrics
Accuracy and completeness directly impact search visibility and listing acceptance across major channels.
FTPR and duplication rate help you assess supplier performance and internal data hygiene.
Business-impact lag is critical for spotting bottlenecks in your content operations.
These KPIs can be integrated into your PIM dashboards and reviewed weekly to flag issues, track trends, and align teams. For growing companies, building out an internal scorecard of these metrics fosters accountability across teams — from data onboarding to content syndication.
By using solutions such as the Gepard PIM Freemium plan, brands can monitor and act on these metrics in real-time, scaling data quality alongside growth.
7 Best Tips For Validating Product Data
Customers tend to guide their purchase decisions based on the completeness of item information. That’s why it’s essential to validate item descriptions so that they are accurate and comprehensive. Complete product details also help draw more attention to your business and rank your online store higher in search engine results.
1. Search for and prioritize additional data sources
Perform constant checks of new sources while verifying the completeness of product information. For this purpose, search for external sources of data in addition to the supplier’s specifications. These may include descriptions of similar goods that you already have and even websites of other online stores.
2. Take format into consideration
It’s common for websites to post product information in PDF or image formats. They are inconvenient for the user and difficult to scan. Make sure your web resources contain data in text formats such as HTML or XML.
3. Optimize data feeds
Product descriptions must be easily scannable for internet search engines, as their accuracy impacts the number of visits to your online store. You should provide proper data feeds to achieve the best rankings in search engines. Data feeds are simply CSV or XML files that contain information about your products or services updated in real-time. It is shown in search engines to tell readers what you offer. How to validate data of this type? You may use Google Merchant Center to learn more about the appearance of your data feeds and how you can optimize them.
4. Define search-relevant product attributes and ensure their presence in data feeds
While searching for a product, customers may look for a specific weight, size, color, etc. Data validation techniques check for specific product attributes in your online store’s data feeds.
5. Use common product designations
In some cases, your products may not have a self-explanatory designation. For example, a supplier may state that a product is a gaming control device, while it is more commonly known as a game controller. Using more relevant names will help you get more customers. You may use software to generate the most common designations automatically to validate data in this way.
6. Standardize attributes
Standardizing and maintaining the consistency of attributes throughout the entire range of products is also essential. The goods in your online store should be standardized according to a single size system: US, UK, or EU. All shades should be carefully attributed to their basic colors, and all measurements should be consistent with a single system.
7. Employ enhancement and optimization software solutions
If you have difficulty with optimizing data feeds, you should use product information management (PIM) software that automatically extracts data. It can seamlessly integrate with all possible sources like manufacturing sites, online stores, and databases, and provides you with the most accurate product information gathered in a single catalog. You can use it to create both product descriptions and corresponding data feeds.
PIM solutions effectively address issues of data optimization and syndication. They reduce errors, enhance information management, and ensure continuous monitoring of quality across sales channels and your online store.
Product Data Validation Is The Lifeblood Of PIM
What’s even more important in 2025 is that modern PIM tools enable real-time validation workflows, AI-powered error detection, and continuous ecommerce data validation monitoring across all sales channels. This helps businesses meet the “single source of truth” (SSOT) standard faster and more accurately. This framework is focused on keeping data sources across all channels up to date and relevant.
Other benefits of PIM-assisted data cleansing are the following:
- Real-time data validation ensures accuracy and quality throughout the checkout process — from login to payment.
- AI-powered validation reduces delivery errors by catching invalid shipping data before publication.
- Better customer experience through hyper-personalized, accurate content.
- Cross-channel standardization enables unified analytics and reporting.
- Behavioral & contextual insights are unlocked via structured and enriched product records.
- Adaptive database structures ensure data models evolve with your business.
Customized database management. Your database management responds to your company’s needs and fits your business model.
How Gepard PIM Powers Automated Product Data Validation
In an era where data flows from dozens of suppliers, content teams, and channels simultaneously, manual validation simply doesn’t scale. That’s why leading eCommerce brands turn to Gepard PIM — a flexible, API-driven platform that automates product data validation at every step of the content lifecycle.
With Gepard PIM, businesses can:
- Automatically validate incoming data from supplier feeds, ERP systems, or CSV imports against custom business rules, GS1 standards, or marketplace requirements.
- Receive real-time error alerts when attributes are missing, incorrectly formatted, or inconsistent across product variants.
- Visualize validation KPIs through dashboards and reports — from completeness scores to FTPR metrics.
- Leverage AI-suggested fixes for common data issues like missing image sizes, unstructured titles, or broken taxonomy paths.
- Integrate validation workflows directly into your content enrichment, translation, and syndication processes — eliminating rework and delays.
Whether you’re onboarding 100 products or 100,000 SKUs across multiple regions, Gepard PIM ensures your catalog stays clean, compliant, and conversion-ready.
You can get started with the Gepard PIM Freemium plan to experience automated validation, monitoring, and enrichment without upfront costs — ideal for scaling teams and growing businesses.
Data Validation FAQ
What Is The Difference Between Data Verification And Data Validation?
Validating data means ensuring the correctness and completeness of data based on a set of requirements. This means either checking compliance with predefined, valid measures (like if it’s the age, it shouldn’t be negative) or checking the accuracy of data against stored, previously validated records.
Data verification has a different goal. Verification checks if the data is consistent, correct, and matches the source.
Why Is Data Quality Important?
The clarity, accuracy, and integrity of product information directly influence customer satisfaction from purchasing goods via your online store. Higher data quality typically results in greater sales.
What Is Data Enhancement?
Data enhancement means enriching supplier-provided data with authoritative third-party sources, AI-generated product tags, and user-generated content. In 2025, it’s increasingly powered by machine learning systems that automatically detect gaps and suggest improvements.
What Should You Make Of Data Validation?
Validating data in a business environment is an essential practice that ensures better service quality. Managing and verifying data manually is challenging and ineffective. It distracts the business from its strategic goals, leads to various errors in records, and causes a business slowdown.
Gepard is an eCommerce platform that offers to streamline and automate your data workflow. Our software solutions can perform constant data validation, verify data reliability, and enhance data. This will improve your customers’ experience, generating more sales and increasing your company’s operating profit.
Request a personalized demo and Gepard will provide your business with top-level assistance.
