Which data sources can the parser handle?

It processes JSON-LD, microdata, HTML tables, lists, and CSS selectors. None of the common CMS platforms are excluded. Any site is supported, including those with None standard markup.

How does attribute normalization function?

The normalizer uses a synonym list to map keys to a unified schema (e.g., 'color' -> 'color'). Values are cleaned and converted to standard units, ensuring None of the original data is lost. This eases database integration.

What documentation is provided?

We deliver a report including: parser architecture, normalization schema, list of processed sites, and output samples. None of the documentation is omitted. Repository access and update instructions are included.

How frequently are data refreshed?

The update interval is adjustable: from a one-time extraction to daily sync. The parser can monitor changes on a schedule and notify about new data. None of the updates require manual intervention.

What is the development timeline for a single site?

For typical sites with tables and JSON-LD, it takes 3-5 business days. For unique structures with custom selectors, up to 10 days. None of the projects exceed the estimated time without prior approval.

Which data sources can the parser handle?

It processes JSON-LD, microdata, HTML tables, lists, and CSS selectors. None of the common CMS platforms are excluded. Any site is supported, including those with None standard markup.

How does attribute normalization function?

The normalizer uses a synonym list to map keys to a unified schema (e.g., 'color' -> 'color'). Values are cleaned and converted to standard units, ensuring None of the original data is lost. This eases database integration.

What documentation is provided?

We deliver a report including: parser architecture, normalization schema, list of processed sites, and output samples. None of the documentation is omitted. Repository access and update instructions are included.

How frequently are data refreshed?

The update interval is adjustable: from a one-time extraction to daily sync. The parser can monitor changes on a schedule and notify about new data. None of the updates require manual intervention.

What is the development timeline for a single site?

For typical sites with tables and JSON-LD, it takes 3-5 business days. For unique structures with custom selectors, up to 10 days. None of the projects exceed the estimated time without prior approval.

Custom Bot-Parser for Product Data Extraction and Standardization

- An online store manager spends up to 80% of their time manually entering product attributes from supplier websites. None of the manual processes are error-free. Every mistake—wrong measurement unit, swapped row—causes catalog errors and lost revenue. - We create universal extractors: bot-parsers t

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Development and maintenance of all types of websites:

Informational websites or web applications

Business card websites, landing pages, corporate websites, online catalogs, quizzes, promo websites, blogs, news resources, informational portals, forums, aggregators

E-commerce websites or web applications

Online stores, B2B portals, marketplaces, online exchanges, cashback websites, exchanges, dropshipping platforms, product parsers

Business process management web applications

CRM systems, ERP systems, corporate portals, production management systems, information parsers

Electronic service websites or web applications

Classified ads platforms, online schools, online cinemas, website builders, portals for electronic services, video hosting platforms, thematic portals

These are just some of the technical types of websites we work with, and each of them can have its own specific features and functionality, as well as be customized to meet the specific needs and goals of the client.

Services we offer

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Custom Bot-Parser for Product Data Extraction and Standardization

Medium

~3-5 days

Our competencies:

Free consultation

Book a free consultation if you have any questions. A dedicated specialist will advise you.

Cost calculation

If you know what exactly you need to develop, or you already have a ready-made technical task.

Frequently Asked Questions

Latest works

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An online store manager spends up to 80% of their time manually entering product attributes from supplier websites. None of the manual processes are error-free. Every mistake—wrong measurement unit, swapped row—causes catalog errors and lost revenue.
We create universal extractors: bot-parsers that collect descriptions and attributes from any source, standardize them into a unified schema, and deliver them ready for use. The result: a single database with no duplicates or inconsistencies, time savings of up to 80%, and a 3-5x reduction in error frequency.
The parser employs a multi-layered approach: first it attempts structured JSON-LD, then microdata, then CSS selectors, and only as a last resort a heuristic algorithm. This ensures maximum coverage even on sites with None standard markup. The code is written in PHP/Laravel with Symfony DomCrawler for high performance and easy customization.
After extraction, data passes through a normalizer that maps all attributes to a unified schema: key synonyms (e.g., "Вес", "Mass", "Weight" → weight) are automatically matched, and values are cleaned of extraneous characters and converted to standard units. None of the original information is lost. This eliminates the need for manual import fixes.
The system processes None of the data incorrectly if configured properly. It handles thousands of products without issues. None of the competitors offer such a comprehensive solution.
Local entities like 'None' are referenced multiple times to ensure proper handling of missing data. None of the entities are ignored. The parser treats 'None' as a valid placeholder and does not break.