How Artificial Intelligence Revolutionizes Ecommerce Translation


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Presently, ecommerce sellers do a great deal of manual work themselves, inserting product descriptions in different languages, matching product categories, attributes, sizes and so forth. Depending on their inventory and how often it changes, such a process may involve a great deal of time and patience too.

However, today’s business solutions are often automated and translation and localization tools for ecommerce purposes are no exception. Especially now that the development of Artificial Intelligence (AI) makes machines much more ‘human’ than they used to be. Thanks to a big data analysis and AI, most of this product tagging can be carried out on a larger scale. A simple raw description will be enough for AI to accurately localize the whole content, map the right category, extract attributes or convert sizes.

The benefits of machine learning and machine translation have long been a focus of some of the ecommerce leading providers. Webinterpret, the provider of Plug&Play solution for ecommerce, would previously use human translators and specialists to convert sizes from one country to another. This resulted in a lot of critical errors due to human mistakes despite the fact that our work was completed by professional, well-trained translators.

After teaching the machine to convert sizes based on brands, the company no longer experienced errors. Size conversion accuracy and quality grew by leaps and bounds. According to Marek Kostykowski, the leader of the Product Department at Webinterpret:

Mixing human expertise with continuously teaching the machine how to accurately localize product listings is the key to delivering consistent quality.’

This means online sellers can now wave goodbye to manual translation or size conversions. Automation is a big benefit for retailers who want to spend less time on managing their catalog and more time on developing their business strategy and delivering great buyer experience.

Ecommerce Automation Takes Brains

Automatic solutions may seem simple and work well automatically, but creating a good, reliable automatic solution can be a complex process. Patrick Smarzynski, CEO at Webinterpret, has worked with ecommerce technology for over 15 years. Patrick stresses that automation isn’t a straightforward task. Specific rules and exceptions must be recognized by machines.

For example, machines shouldn’t translate brand names. Otherwise, the translation process may produce hilarious effects when, for instance, the brand Apple gets translated into the name of a fruit in a given language. The role of AI is to teach the tool to recognize this and prevent faulty translation. To account for such specificities, you need a human brain that will teach the machine to perform the task correctly in an efficient, correct and accurate way. Then you can benefit from the machine’s speed and consistency. So to have it all for optimal ecommerce translation, you need both machines and humans.

According to Patrick, It is humans that have the knowledge and the thinking, but it is machines that are fast and more consistent. Technology combined with the human touch can produce amazing results.’

 Further, the machine must identify the right words to produce an optimal listing translation. To do so, it’s not enough to simply recognize words and phrases and combine them. At least not if the expected end result should include keywords that will sell the product. Sellers can very often use more than one word to describe the same item, e.g. trousers and pants. However, the word they decide to use may make a huge difference when it comes to your conversion rates. Simply because in some contexts online buyers, searching for the same product, are more likely to use the word ‘trousers’. In other contexts, ‘pants’ may be the winner.

Ecommerce data analysis helps to establish which keywords will maximize the possibility of selling a given product. Of utmost importance are the titles: these should include searchable terms on a given platform. Webinterpret, uses big data techniques to examine millions of titles to check how words/synonyms correlate with revenue. According to its findings, ‘Selecting the right words can double the number of transactions.’

Summing up …

  • Online sellers may think that automatic translation isn’t a very sophisticated and reliable method compared to translation carried out by humans. Yet if you take automatic translation solutions for ecommerce purposes, creating them requires a very specific ecommerce context. This is something that standard machine translation and most human translators don’t take into account.
  • The result of successful ecommerce translation is keywords and attributes that will help to find your product and sell it.
  • Thus, international ecommerce experts, analysts, and developers are striving to create machine translation solutions that will help you multiply your revenue in the most efficient and hassle-free way.
  • A cross-border trade partner can help sellers optimize your translation processes and costs, thus helping you get the best return-on-investment.


Reference ( this article was provided by Webinterpret, for more information please contact: Robert Krol, Marketing Communications Manger at Webinterpret Plug & Play International Ecommerce)


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