Frequently Asked Questions

Natural Language Generation (NLG) refers to the automated generation of natural language by a machine. As a part of computational linguistics, the generation of content is a special form of artificial intelligence. Natural language generation is used in many sectors and for many purposes, such as e-commerce, financial services, and pharmacy sector. It is seen to be most effective to automate repetitive and time-intensive writing tasks like product descriptions, reports or personalized content. Learn more about Natural Language Generation (NLG).

Automated content generation with AX Semantics works with the help of Natural Language Generation (NLG) - a technology that generates high-quality and unique content on the basis of structured data that is
indistinguishable from manually written content. Text automation is used for generating product descriptions, category content, financial and sport reports or content for search engines websites. In a nutshell, it is used for all kinds of content that require large quantities and have a similar basic structure.

With the help of automated content generation, you can save up to 80% of the time used for repetitive writing tasks. By automating the repetitive bits of the content creation, human productivity will increase significantly. As a result, it is possible to create unique and customized content of large quantities - in 110 languages. In this way, new content formats are created and the days of duplicated content or content of low quality are over. Take a look at the succes stories of our customers!

An article generator is an AI-powered program that automatically creates content. If it is a GPT tool, it is often a free article generator tool that relies on deep learning to create relevant text. This content creation software can mimic human writing through a style transfer system.
On the other hand, some platforms are Data-to-Text NLG. They take information from a database and turn it into readable text. These tools can cover just about any topic, and you can customize the software to include specific details. Read more about the differences between Data-to-Text and GPT.

GPT stands for Generative Pre-trained Transformer and is a model that uses deep learning to produce human-like language. The NLP (natural language processing) architecture was developed by OpenAI. GPT uses a large corpus of data to generate human-like language representations. It is a language model that learns from existing text and can provide different ways to end a sentence. It has been trained on hundreds of billions of words, representing a significant portion of the Internet - including the entire corpus of the English Wikipedia, countless books, and a dizzying number of web pages.

Data-to-Text refers to the automated generation of natural language text based on structured data. Structured data are attributes that are available, for example, in the form of tables. The users have full control over the text result, as they can intervene in the text generation process at any time and make updates or adjustments. This control ensures text consistency, meaningfulness and quality. Texts are also customizable and scalable. This means that hundreds of texts on products with variable details can be created in a matter of moments.

In short, data-to-text is used in e-commerce, the financial and pharmaceutical sector, in media, and publishing.
GPT-3 can be helpful for brainstorming and finding inspiration, for example when the user is suffering from writer's block. Using GPT-3 in chatbots to answer recurring customer queries is also very useful, as having humans generate the text output is inefficient and impractical. For more in-depth information, download our one-pager on Data-to-Text vs. (Chat)GPT.

ChatGPT is an AI chatbot that generates natural and human-like conversational responses in real time, and can also output the text in different languages. ChatGPT is derived from the GPT 3.5 language model and is described by software company OpenAI as a fine-tuned" version of it. The purpose of ChatGPT is to provide users with fast, accurate, and helpful answers to their questions. However, now and then there are errors and misinformation.

Among others, the software uses neurolinguistic programming (NLP) in form of machine learning tools for the language and grammar components. The initial configuration of rules, phrases, tonality etc. is entirely done by the editors. So content and style are shaped according to the software users wishes and requirements.

API (Application Programming Interface) is a program interface which allows you to access the functions of an app. This includes data import, content generation or the integration of automated content onto your own website. All functions of AX Semantics NLG Cloud are available via our REST API and each action can easily be automated.

Numerous clients of AX Semantics have achieved great results, showing that automated content is worthwhile in terms of SEO. As the example of the e-commerce company MYTHERESA demonstrates. The fashion retailer increased its visibility by 80% for relevant keywords within 6 months after
introducing automated content to their online shop. Learn more in the Mytheresa Case Study. The company KitchenAdvisor is another example for improved SEO results. Their Sistrix visibility index increased from 0.7 to 1 within 3 months thanks to automated content generation.

AX Semantics' software is configured to produce thousands of unique pieces of content. Most users publish this generated content on their website with the goal to improve their visibility on Google and other search engines. Therefore, there are various functions in the AX tool (sentence variants, synonyms, triggers, sentence sequences, etc.) to ensure text variance and uniqueness. 

This is how it basically works: After an initial configuration, you can use the software to generate unique and high-quality content based on structured data. Once only, you create logics, content blocks and variances for all possible "events" as needed. This way, evaluations, assessments and conclusions can be done directly in the content. Based on this and the information it finds in the data, the software forms content based on natural language. Then, each time content is regenerated, the software assembles the components into a new unique content, following the predefined rules. 

You want to know how it works? Then take a look at the 13-minute demo webinar.

Our software is run by editors, which allows us to create texts based on structured
data that are identical to content written by humans. This is called hybrid editing. In other
words, editors use our tool to automate repetitive writing tasks that would require too
much time and effort to be created manually. As a user, you create logics and content
blocks for all sorts of "events" only once. On this basis and from pieces of information found in the data, the software then generates natural language content. This setup also allows evaluations, assessments and conclusions to be made in the content. The configuration of rules, statements and tonality is entirely in the hands of the editors. This ensures a high quality of the content.

Yes, we have published some case studies, including some examples, that were created with automated content generation on our website. However, sample texts are only to some extent representative, because: The user is solely responsable for content design, and thus content quality, as it is also the case in manual writing. If you still want to get an insight into what other companies have achieved with AX Semantics, then have a look at our case studies.

E-commerce has a significant need for content: For many producers and retailers, it is not possible to create individual product descriptions for their product range and category websites. Due to the fact that the manual effort is extremely time-consuming, it is common to use the manufacturer's description, or in some cases, to use no description at all. Automated product descriptions and automated category texts can increase the visibility in search engines and, as a result, increase the conversion rate in the online shop. This is because the webpage can be found more easily and users can receive purchase-decisive information through high-quality content. Moreover, structured product data is often provided in the e-commerce sector, for instance from PIM systems. In this way, the data base for content automation is already available. Do you want to know more? Then read everything about e-commerce automation.

The use of content automation is always worthwhile when:
1. High quantities of similar content is needed (such as thousands of product
descriptions, hotel descriptions, destination descriptions, etc.) or
2. Similar content is required on a regular basis (e.g. financial reports, soccer
reports, reports/forecasts, etc.).

However, there is no standard answer to the question of when content automation is
worthwhile. Most of our customers need at least 1,000 content pieces, and the
possibilities are endless. Some of them generate more than one million texts per year. Due to our different license plans, we find a suitable package for each customer.

AI text tools are based on either GPT or data-to-text technology. With data-to-text software, you need structured data to create high-quality, relevant content. Your data is converted into text, ensuring consistency and quality. You can structure the text according to your preferences. AI writing tools based on GPT are trained on hundreds of billions of words, representing a significant portion of the Internet. GPT tools are best used as idea generators and tools for creating single pieces of text, such as blog posts.

You can use AI content generators for various purposes, including creating of product descriptions, chatbots, customer service, and content automation.

The best content generator is the one that quickly writes original content without errors and inaccuracies. In this case, data-to-text programs are better than GPT platforms. But if you want a tool that gives you exciting content ideas, you should try an article generator based on GPT. Once it has generated an article, you can scan it to detect any errors and make the necessary corrections.

How much time it takes to generate your first texts depends on various
factors, such as:
• What kind of content should be generated?
• Is there a database?
• How extensive and varied are the texts supposed to be?

Our recommendation is to follow an iterative approach, i.e., to start with minimal
content and to continuously extend and improve the project. This way, many of our
users already publish a first version of the texts after a couple of days. Regeneration of
content is included in the license fee, so previously published content can be
updated at all times. Anyway, regular updating of texts is advisable from an SEO point of view with regard to content freshness. For e-commerce companies with a very diverse and large product range, it can also be helpful to proceed product category by product category.

No, users do not require programming skills in order to use AX Semantics. More
important is that they have domain knowledge about their topic and a good sense of
language and good content, as content quality is in the hands of the user. This
is why most of our users are not programmers.

Below are a few real customer testimonials submitted to G2.com on how to use the software:
„It is intuitive to use and if you bring a good data structure and some feeling for language, you'll soon watch it producing all the texts you need.“
"Interface is very clear and logical. One intuitively understands where to find the
needed features, even without having much experience with the tool."

AX Semantics masters the grammar of over 110 languages. In other words, it is
possible to generate grammatically correct content in all of these languages and
to benefit from the advantages of automation. However, AX Semantics is not a translation tool. So a native speaker is needed to formulate the linguistic building blocks. For multilingual projects, the rules and logics can be taken from the source language, so that additional languages can be implemented even faster. Our customer SkatePro has successfully done this in 17 languages - learn more in the SkatePro case study.

Structured data is data that adheres to a pre-defined data model. Therefore, it is easy to analyze. They conform to a well designed pattern, for example a table with connections between the different rows and columns. Common examples of structured data are Excel files or SQL databases. Structured data is an important basis for automated content generation. For product descriptions in e-commerce, for example, they are often made available in a shop system, product information system (PIM) or in the online shop. Find out more about the importance of structured data in this whitepaper!

We will be happy to advise you on how to generate structured data and, if necessary, have suitable partners who are glad to help you. Even without structured data, it is possible to use our software, for example to supplement existing product descriptions with personalized content. With the help of our "Metrics" service, you are able to track the user behavior of your website visitors. This gained user data is the basis for our personalization solution, as it converts them into personalized content that is tailored to the user interest. The personalized content is automatically displayed on your product pages.

Yes, data import is possible with various store systems. We provide plugins for the most common store systems, enabling a direct data import into our platform. For additional store systems, we offer a Direct API (Application Programming Interface). This programming interface allows data to be imported and exported automatically.

When starting out with the software, AX Semantics offers all users an onboarding. In other words, every customer is assigned a personal Customer Success Agent who answers all questions and provides assistance for the first steps in content automation. Furthermore, every user can contact our excellent support at any time if they have any questions. At the beginning of our customer's content automation journey, the most important functions are also explained in an interactive e-learning seminar.

Yes, you can watch a demo in which our Customer Success Agent Peter introduces he tool in 13 minutes. He explains how the software works and for which use cases it is suitable. Just watch the demo.
Additionally, you have the opportunity to try out the tool yourself - completely free of charge. In a small interactive tour, we guide you through the AX platform so that you can get a first impression. Just register for free and get started!

Personalized product pages individually address customer interests and generate more conversions. The AX Semantics "Personalized Commerce" uses real-time user data to create individually targeted purchase incentives for each visitor of the website - be it a regular customer or a first-time visitor.

AX Semantics' feature "Personalized Commerce" offers a hyper-personalized customer approach that increases conversions. As a feature of our tool, it is linked to our automated content generation software. It designs, tests, and optimizes the content of your product pages to best address and convert each individual customer. Learn more and read everything about "Personalized Commerce".

Content adjustments according to day times or even seasons can be done effortlessly.
The major advantage, compared to manual content creation, is that you configure these aspects, which are dependent on the season or time of day, only once within the project. Then they are rolled out to all the desired content. For instance, product descriptions for large cooking pots can include recipe tips for the
holiday menu just before Christmas.