How To Automate Business Processes In An Enterprise Using Natural Language Generation?

Natural Language Generation for Business Automation.

Automation started with the Industrial Revolution, but with the Internet and AI it has reached new levels.

Today, Natural Language Generation (NLG) influences how companies present themselves in naturally generated texts and interact with their customers and prospects. Its methods are used to turn raw data into insights written in plain English.

Below are some examples of how NLG benefits the business process.

How To Automate Business Processes In An Enterprise Using Natural Language Generation?

NLG for Ecommerce: Beautiful product texts

Products in online shops presented in a user-friendly way sell significantly better. After all, a customer can imagine his future window cleaning device, the new bicycle saddle, or the taste of a fruit tea much better with the appropriate description.

The automation of processes in e-commerce is continuously advancing and does not stop at the text creation process with the right software; thousands of diverse product texts can be created at the click of a mouse.

This is no magic. The tools for the “text robots” come from computational linguistics, bears the name “Natural Language Generation” (NLG), roughly translated as “natural text generation / automatic text creation,” and is a unique form of artificial intelligence (AI).

Companies such as Contentyze or Arria from Great Britain, Ax Semantics or Retresco from Germany have long since made text production with NLG their business model.

Some sources have provided extensive information about the basics and functionality of copywriting software. A lot has happened in this field since then.

This kind of software is even easier to use. There are new helpful features. For example, existing data can be used more precisely — and above all, other practical data has been transformed into fresh texts.

Products have many metadata that describe shape, size, color, brand, price range, function, handling, etc. With Natural Language Generation, metadata can be converted into convincing texts and customized for specific target groups, occasions, regions, even times of day or weather conditions.

They can then be automatically imported into your online shop or the newsletter. In this way, appealing product texts are created from extensive Excel tables or large amounts of data in the Product Information Management System.

On the other hand, would you like to automatically generate descriptive texts for the images in your digital asset management system?

Natural Language Generation can write hundreds or thousands of text in an informative, understandable, error-free, and search-engine-optimized manner — requirements that can no longer be met by editorial teams at this scale.

NLG in Banks and Insurance

Financial companies today are under enormous pressure to be efficient. Automatic text generation offers several saving solutions in this space.

A great example is automated reports on customer assets: stocks, indices, and portfolios which change every second. To be up to date and to report reasonably up-to-date on developments has so far required a lot of editorial work or was simply impossible.

Natural Language Generation makes it possible to automate this area and even personalize reports and enrich them with context-based analysis results (BI, statistics, big data, etc.).

But consulting documentation, statement of accounts, or product comparisons can always be converted into text on websites with appealing content, or into a PDF or a brochure, based on structured data.

Banks, in particular, are increasingly relying on automated reporting due to new regulations. The Mifid II directive introduced at the beginning of the year specifies that investors have to pay analyst reports explicitly. You can no longer recover the costs of writing bond and stock market analyzes through transaction fees and therefore have to consolidate and rely on cost-saving solutions (that is, Natural Language Generation).

Contentyze is an easy-to-integrate NLG tool

NLG in Tourism, real estate, destination marketing

Whether country, region, hotel, room, bar, restaurant or beach: there is metadata for every destination, every place, which can be transformed into descriptive, human-written texts at the push of a button.

Whether a chain with hundreds of hotels or a country with several regions and cities: websites, flyers, or digital displays can be automatically updated with relevant content without great effort and always up to date.

Larger real estate companies and portals are already transforming metadata about the property and its surroundings that have already been entered by customers into fully formulated reports with a click.

NLG in other industries

There are plenty of other industries that can benefit from NLG.

For example, in the field of human resources, HR departments spend a lot of time creating job descriptions, job references, job profiles, and the like. Natural Language Generation can generate appealing texts from structured data, which are automatically and appropriately published in all channels (e.g., external job portals).

There are also many advantages in organizations with many units that want to present themselves individually. This can be insurance agents, travel agencies, restaurants, and the like.

Here, the local managers usually have little time and different degrees of textual competence. Natural Language Generation can generate consistently good texts based on centrally available metadata for display on hundreds of microsites or landing pages.

Finally, it can be useful for companies that regularly write dozens of press releases. For example, it can write about the latest market developments (local property prices, regional consumer trends, bestseller lists, etc.) in several markets and create them in several languages.

It can also send a quote for a customer every day that “Nobody likes doing that,” but they can’t outsource it because it has business-critical effects, and we need 100% accuracy in this content

With Natural Language Generation, you can automate similar press releases based on structured market data. Then, you embed them in the existing workflow for content approval and publish them through various channels, resulting in individual, hand-written press releases.

Opportunities for using NLG in your business are endless.

Want to learn more about NLG? Visit us at Contentyze.

Written by

CEO Contentyze, the text editor 2.0, PhD in maths, Forbes 30 under 30 — → Sign up for free at

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