Lizeo Group
Data Blog by Lizeo
In a context where products need to be continuously fed with effective marketing descriptions to fit into a good SEO strategy, Artificial Intelligence with Natural Language Generation (NLG) technology appears to be an ideal solution to automatically generate quality and quantity content. This rapidly growing technology has become common in many industries and can become a real ally for your data-driven content marketing strategy.

NLG to automate content generation

NLG stands for Natural Language Generation and is one of the two branches of Natural Language Processing.
Its purpose is simple, it uses Artificial Intelligence to transform structured data into huge amounts of high quality text, no different from human writing, in a matter of seconds.
Thanks to this technology, it is possible to automate the writing of content, such as marketing descriptions on an e-commerce site, but also financial reports, weather reports, sports reports, etc. We've probably all read content written by NLG technology without even realising it.

Why generate content automatically?

Quantity and quality of content to boost SEO

With NLG, it is possible to generate content in quantity and continuously, which makes it possible to develop the editorial content and therefore the referencing of a website (note that for the texts to be of quality, it is necessary to have quality data).

The Natural Language Generation technology allows texts to be structured in such a way that the content is adapted to the desired text formats while highlighting specific keywords, in order to offer relevant content adapted to your targets.

Read also : All you should know about Data Preparation

In this context, it is important to control the similarity between texts published on a website, known as the "Duplicate Content" rate. Indeed, search engines have set up a tool to track identical content and sanction pages judged by this tool as being copied because they are too similar.

By using specific algorithms, such as Simhash which is used by Lizeo, it is possible to control the similarity between texts and therefore drastically reduce the rate of Duplicate Content between contents.


There are many articles on the subject of calculating similarity between texts, here are a few:

To save time

Writing quality, unique, multilingual content on a large number of products is a time-consuming task. Moreover, it is difficult to provide marketing descriptions for all the products on a site using human writing alone, which is why some players decide to provide marketing content only for the most popular/sold products.

The NLG makes it possible to solve this problem, because from the data of each product, the technology will be able to create a description (marketing, technical...) for each of them in a few seconds.

To get up-to-date content in real time

As part of a good SEO strategy, updating and feeding content is a key element, as the more recent it is, the more relevant search engines will consider it.

This is why editorial work is necessary on new products that appear on your website. This is a task that the NLG tool can perfectly handle, making it possible to automatically generate content as soon as the product appears on your website.  

Updating large quantities of product sheets is also extremely fast. It only takes a few settings to change an element (text structure, word change, etc.) on thousands of descriptions.

To have homogenised content

In order to have a coherence between the published contents and to optimize the consumer path on its website, it is necessary to have homogeneous product descriptions, with the same writing tones. The settings made on the NLG tool will offer descriptions with the same structure.

For example, it is possible to generate for each product :

  • A short description of the product
  • A detailed description, with the technologies and performances of the product
  • The 3 key points of the product

NLG: which use cases?

As long as there is structured data and a need for content editing, this technology is adaptable to all industries. It is mainly used in the following areas:
  • E-commerce players: feeding all products with high performance content is one of the keys to not only attracting visitors but also to increasing the conversion rate. 
  • Chatbots: for example, they can alert consumers to delivery delays with a personalised message depending on the time, place of delivery, etc.
  • The example of the Washington Post with its NLG technology called Heliograf is one of the most telling, with hundreds of automatically generated articles, such as on American football matches.
  • Finance: the drafting of periodic financial reports and financial news is often fully automated.
There are a multitude of use cases, as Natural Language Generation is adaptable to all sectors of activity.
The NLG is a technology that meets the needs of a large number of e-commerce players, sometimes without them even being aware of it. Whether you are an e-commerce player, a manufacturer with a large distribution network or one that wants to feed its PIM, the NLG tool can greatly help you in the development of your content marketing strategy.
Do you want to get unique and powerful product descriptions from data?