Content at Scale: Definition and Implementation

1. What is Content at Scale?
2. What are the benefits of Content at Scale?
3. This is how Content at Scale differs from other large language models (Large Language Models: LLMs)
4. This is how you successfully implement Content at Scale
5. These software solutions support you with Content at Scale
6. Conclusion: What are you waiting for? Start with the demo right away!

Disclaimer: If you were looking for the AI tool called "Content at Scale", you can find all the information about it on the website of Content at Scale.

A successful and scalable online presence requires numerous content in different formats: blog articles, whitepapers, videos, podcasts, newsletters and more. For the creation of this much content, content-, marketing-, sales- and creative-teams really have to put a lot of effort in.

Content at Scale can be a great enrichment for your team in content creation. You can find out what is behind this term and how to successfully implement Content at Scale in your company in this article.

Who Content at Scale helps (Source: PointVisible)

What is Content at Scale?

Content at Scale enables you a fast content-production, where quality has top priority. Generative AI technologies design your Content Creation, content-optimization and -publication more efficient considering your company values. The secret lies in the combination of data-based and dynamic content-generation: User* set, which texts should be created with structured or unstructured data. With Content at Scale text modules are being produced once, that users* can then test and release. Content-Tools can automatically access the released text modules.

What are the benefits of Content at Scale?

Due to the combination of modern end-to-end technologies and data-base text creation, Content at Scale offers the crucial benefits:

1. Once-Setup due to 1:N-Approach: With such technologies, usually the 1:1 approach is standard, this is different with Content at Scale: User* set the content-process up once and can use high-quality and correct texts anytime across different formats. The costs therefore don't rise proportional to content-creation.
2. Control by Users*: Users* decide which texts are being created data-based or dynamically. They check the quality of the texts and can make changes anytime.
3. Organisation-wide processes: Scaling of content becomes easier and more effective. Companies can introduce centralised processes across the organisation.
4. High-quality Content: Companies can use the high-quality, correct and unique text modules cross-channel while adhering to country-specific SEO and compliance standards.
5. Content-Diversity: Content at Scale is suitable for large, international content projects and supports the generation of product-descriptions, SEO-texts, landing pages, marketplace-information, FAQs, Points of Interest (POI) and destination content.
6. Fast Implementation: data-based text models and integrated end-to-end technologies enable a fast project-implementation and accelerated go-to-market strategies for all relevant content types and projects.
7. Company-wide automation: Thanks to automation through Content at Scale, more content can be produced and company-wide processes as well as complete workflows can be automated.
8. High Conversion Rates and high cost-efficiency: Content-processes become more efficient through the generation of channel- and target group-specific content, personalisation and text variants with Content at Scale.
9. Easy scalability: No other technology enables such a fast, high-quality and multilingual content-production like Content at Scale.
10. Time for Creativity and Personalisation: Users* have more time for creativity. The generative AI is being used sensibly, so they can extensively deal with the creation of unique and creative content that fits their target group perfectly.

This is how Content at Scale differs from other large language models (Large Language Models: LLMs)

Comparison Content at Scale vs. Jasper (Source: JohnEEngle)

AI-based content-tools such as OpenAI ChatGPT and Jasper have turned the content-world upside down. We are still at the beginning. But the more data is being collected and the more computing power is available, the better the results will be. At the publishing date of ChatGPT at the end of 2022, the AI had reached a million users* - more than almost any other product in such a short time (for comparison: 5 days ChatGPT corresponds to 2,5 months Instagram and 3,5 years Netflix). It is now clear: the technology fundamentally changes content-creation of companies.

CPT models (LLMs) are template-based text modules, which require a human quality- and fact-check (1:1 approach). The integration of generative AI and machine learning technologies with Content at Scale allows users* to decide themselves about the method of content-generation. Thanks to dynamic templates the text-creation is based on unstructured data to a large extent. AI models create templates and text variants (e.g. text categories and formats), while users* can make all changes themselves if required. Individual promptings are supported. The text-prompting goes beyond the simple processing of inputs with GPT inputs: GPT-generated, static templates are validated and quality-assured by generating correct texts and creating all possible text variants. Users* can suggest additional text variants for existing text variations. Once the process is set up, text modules can be used as often as needed (1:N approach).

This is how you successfully implement Content at Scale

The AI specialist Retresco Textengine is a pioneer in the field of Content at scale and has combined a data-based approach to automated text generation with the advantages of large language models with Large Scale Content Automation (LSCA). You can generate texts that are content-wise, grammatically, and legally impeccable on a large scale. You can individually determine the tonality and wording of your texts and act specific to channel and brand. Human input is possible at any time ("Human-in-the-Loop").

Content at Scale is based on an initial set-up. Given data and rules guarantee a continuous text creation in consistently high quality, variety and topicality.

Use Cases for Content at Scale

Content at Scale can enrich almost any content team. We will go into detail about the most important use cases.

Content at Scale for online product descriptions (or hotel descriptions) and print product catalogues

E-commerce companies need a massive amount of product descriptions – for customers and search engines. With Hybrid NLG the advantages of each individual product are prepared in target group oriented language. The advantage in time for creating the unique SEO-content is enormous. Also print catalogues are updated within a few seconds.

Content at Scale for marketplace product descriptions (or hotel descriptions)

Marketplaces like Amazon and Ebay have individual content guidelines, which companies have to adhere to when creating their product descriptions. Hybrid NLG and textengine.ioprecisely address the requirements of the respective marketplace, through which companies can produce high-quality content scalably with Content at Scale.

Content at Scale for FAQs

FAQs provide short and exact answers to the most important user questions. LSCA generates valuable answer texts, which positively affect your SEO.

Content at Scale for product comparisons (or hotel comparisons)

Many users* don't just buy any product, they compare first. The writing of special product characteristics helps them in making a decision. With Content Automation this is done quickly.

Content at Scale for category-pages

Category-pages have to explain to search engines what a website is about. Therefore, e-commerce companies need detailed texts, which are usually placed as far down as possible. Due to the high number of category- and subcategory-pages automation makes sense.

Content at Scale for Ads

With Ads (advertisements) E-commerce companies lure their target group to websites and landing pages. Most Ads are displayed in Google, Bing, Amazon, Facebook and Instagram. These companies can create them in a fraction of the manual creation time with identical text quality.

Content at Scale for Meta Title and Meta Description

Product-pages need SEO-texts in addition to high-quality product descriptions. This includes the Meta Title and the Meta Description. They tell the search engine what's on the page, so it indexes the page correctly. A manual creation of the meta-data considering the most important keywords is not required.

Content at Scale for Picture Descriptions

Picture descriptions are also part of the SEO-texts of a product page. They ensure a good ranking in image search and navigate users* to your online shop.

Content at Scale for Destination Content (POI)

Destination content refers to the representation of structured tourist offers. This is supposed to help users* find their dream trip and make sure that users* find the corresponding website in Google. Automation minimises this cost factor.

Actual examples for Content at Scale

Many use cases lead to many examples. These are four companies, which successfully implement Content at Scale with the AI specialist Retresco in their content production:

Example 1: Multilingual texts at Lyreco

The majority of Lyreco texts are automatically created by the content-automation-platform: 70 % of their online shop texts and 87 % of their catalogue texts. Currently, textengine.io generates product descriptions in German, English, French, and Italian from the provided data. The automation significantly shortens the time for text creation and reduces translation costs. Lyreco has recently expanded its partnership with Retresco at a global level.

Example 2: Product descriptions of the MediaMarktSaturn Group

More than 300.000 automatically generated product descriptions are permanently available in the online shops of MediaMarkt and Saturn. Since 2019 the online shops of the company have been using the scalable text generation of textengine.io, which accesses more than 200 data-based text models. The huge advantage for the content team: only one person is in operation. This means minimal resource usage with maximum output.

Example 3: Increase of visitor numbers of a global travel agency

A globally operating travel agency helps customers find cheap flights. It was able to increase the number of website visitors by 23 % in just four weeks using Content at Scale. For this, it used templates created with Hybrid NLG. The travel agency tested and collected data from the United Kingdom, the USA, France, Spain, and Brazil: texts were automatically used in the respective national language for each country.

Example 4: Large-scale content production at OBO Bettermann

The manufacturer of electrical installation and connection technology makes special demands: All texts - both specifications and product descriptions - must be uniformly structured. They are translated into 26 languages. For scaling of texts 250 data-based text models are used, on the basis of which OBO Bettermann produces more than 25.000 texts per year.

These software solutions support you with Content at Scale

Different tools make Content at Scale possible. With the textengine.io from Retresco scalable content strategies can be implemented simply and efficiently with Hybrid NLG. Users* can combine their creativity with a virtually unlimited content scaling to improve their Time-to-Market (TTM) and automate their content output. With textengine.io, Retresco user* can use unstructured data, preconfigured text types and individual prompts. Marketing-, content- and SEO-teams just frame their content and define their content workflow. Retresco also strengthens your Corporate Language with textengine.io: You align your content processing and tonality according to your brand guidelines.

Since 2008, Retresco has been supporting companies all over the world in automating their language-based business processes. Unlike many companies and startups in today's NLG business, Retresco is not just a service provider or dealer. Retresco is a team of experts in computer linguistics, machine learning and software development.

Companies can analyse their success with Retresco using the following KPIs:

• Cost savings: How big is the price difference between the fully automated and scalable content-set up and the manual content production? By how many percent does their Time-to-Content shorten? How does the automation affect the Go-to-Market strategy?
• Conversion Rate: How much does the conversion rate increase due to high-quality texts on product websites and other channels?
• Organic Traffic: By how many percent does the organic traffic on websites and other channels increase due to search engine optimised content? How much impact does the tool have on visibility?
• Return rates: To what extent is the number of returns reduced due to correct and up-to-date product information? What effects does the provision of correct service information have?

Numerous AI text generators you can find on the software comparison platform OMR Reviews. Check it out and compare Retresco textengine and other popular tools using authentic and verified user reviews:

neuroflash

OpenAI ChatGPT

Creaitor

Jasper

Conversionmaker.ai

Conclusion: What are you waiting for? Start with the demo right away!

Content at Scale is a combination of generative AI, machine learning technologies and data based content creation, which can extremely speed up content creation and management. Anyone who generates large amounts of content and is looking for an automation solution should definitely check out our tool recommendations Retresco & Co.