What High-Quality Data Really Looks Like in eCommerce
Everyone talks about data. Far fewer talk about what makes it usable. For Stratalis, the answer is simple: data is only valuable if it’s complete, consistent, and ready to use the moment it’s delivered. With Decodo, that level of quality comes as part of the setup.Skaler.app built a powerful ad intelligence and creative automation platform using AI tools and Decodo’s web data.
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Client
Stratalis, a web scraping and data collection company delivering high-quality datasets across multiple industries.
Industry
Web scraping and data intelligence.
Use case
Delivering decision-ready datasets with near-perfect completeness and consistency.
Challenge
Ensuring reliable data access and eliminating gaps, inconsistencies, and inaccuracies at scale.
Result
Highly complete, consistent datasets that clients can trust and use instantly.
Defining data quality (and why most datasets fall short)
Stratalis, a provider of high-quality web data solutions across industries, approaches data quality with rigorous standards. It’s not about volume or speed, it’s about usability.
As Julien Demoor, CEO of Stratalis, explains:
"A dataset is only truly usable if it can be directly consumed without any additional processing."
This definition sets a high bar. It requires:
- Near 100% completeness
- Strict internal QA standards
- Full alignment with client-specific use cases
In practice, this often means delivering everything, not just a subset of fields.
Where does the data quality break?
Most data quality issues don’t start in dashboards or analytics layers. They start much earlier, during data collection.
Before working with Decodo, Stratalis faced persistent challenges that made quality difficult to guarantee:
- IP blocks and CAPTCHA interruptions
- Invisible anti-bot mechanisms
- Content that changed depending on how it was accessed
The result was data full of gaps and uncertainty, which created continuous problems:
- Datasets with hidden missing data or inconsistencies
- Reprocessing and duplicate extraction
- Delays in delivering insights
In eCommerce, where data changes constantly, these challenges make it difficult to compete with others and make informed decisions.
Why geographic accuracy is non-negotiable
Another critical dimension of data quality is location. The same eCommerce platform can display completely different information depending on where the user is browsing from. That includes:
- Pricing variations
- Product availability
- Search rankings and visibility
Without accurate geo-targeting, datasets may appear complete but still fail to reflect reality. For Stratalis, this makes geographic precision essential:
"Geographic accuracy is not optional: it is fundamental to delivering meaningful insights."
In this context, completeness isn’t enough – contextual accuracy is what defines high-quality data.
Fixing data quality at the source with Decodo
To solve these challenges, Stratalis focused on the root cause – data access.
By integrating Decodo’s residential, ISP, and datacenter proxies, the company was able to stabilize how data is collected across regions and platforms. This directly improved data quality, not just infrastructure performance.
Or, in Stratalis’ own words:
"This has significantly reduced access-related failures and made our data pipelines more predictable at scale."
Instead of fixing problems downstream, Stratalis now ensures quality from the very first step.
Data quality in the age of AI
As AI becomes more embedded in eCommerce analytics, the importance of data quality is increasing, not decreasing.
Stratalis has already seen this firsthand.
AI is powerful, but it depends entirely on the data it receives. Poor-quality inputs lead to unreliable outputs, including hallucinations and misleading insights. High-quality data, on the other hand, unlocks AI’s full potential.
Looking ahead, the standard for data will change:
- Completeness and consistency will need to approach perfection
- Data quality will become non-negotiable
Human oversight will remain essential
Stratalis’ approach remains unchanged: deliver faster, scale further, but never compromise on data quality.
Make Data Quality Your Advantage
Ensure complete, consistent, and decision-ready datasets with Decodo’s reliable proxy infrastructure. Build data pipelines you can trust from the source.
14-day money-back option