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How AI helps create quality content for digital commerce

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How AI helps create quality content for digital commerce

Advanced content with generative AI, PIM, and automated text generation

Generative AI has made automated text generation easier than ever with ChatGPT, GPT-4, and others. At the same time, the use of such language technologies poses challenges for many companies since the texts must be not only high-quality and correct but also legally compliant. In addition, it must be possible to generate large volumes of text for a wide variety of text types such as product descriptions, FAQs, SEO tags, or meta elements. This is where generative AI such as ChatGPT or GPT-4 reaches its limits.

An alternative, however, is the integration of generative AI and automated text generation – with a powerful product information management (PIM) system. With an integrated solution, the creative possibilities of ChatGPT, GPT-4, and others can be leveraged while scaling text automation easily and effectively, saving time and resources. In this blog post, you will learn how generative AI, automated text generation, and PIM systems can work together and what benefits they bring to digital commerce.

Unique and compelling content with product data and generative AI

Structured and high-quality product data is crucial. A PIM system helps companies bundle and harmonize all relevant sales and technical product information to deliver offers and services easily and consistently across channels to the right target group. Automated text generation based on central data supports companies in optimizing business processes in a targeted manner, setting up content workflows, and generating target group-specific content.

As soon as a company has decided on a suitable PIM system, the path is clear for automated text generation from a single source. Data forms the basis for these AI-based content solutions. This means that not only can the creation of product descriptions be automated, but it can also be implemented on a large scale and in all desired languages. The more comprehensive and complete the product data, the higher the quality and originality of the result of automated text generation. Thus, the quality of the created texts directly depends on the quality of the existing data. If the data is incomplete or incorrect, the quality of the automatically generated texts also suffers.

However, in the field of automated text generation, there are already new approaches that help companies process and use unstructured data provided via generative AI such as ChatGPT. By combining GPT-4 or comparable models and data-based text automation, text models and variant suggestions can be generated and launched at scale with content automation. So, this combines the available general knowledge as well as structured data to create tens or hundreds of thousands of web, product, and SEO texts.

The use of data-based text models is crucial for greater efficiency and thus for scalable success in digital commerce. Companies can thus save time and resources and be confident that their texts are correct in terms of content and legal compliance. These text models are based on an initial setup of data and rules, which ensures continuous text automation of consistently high quality, variance, and timeliness. At the same time, companies can adapt the tone and wording of their texts in an individual and customized way and vary them to suit their brand. Compared to ChatGPT, GPT-4, and others, human intervention is always possible (“human-in-the-loop”).

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The combination of generative AI, automated text generation, and PIM systems offers companies five distinct advantages:

  1. Accelerated time-to-market
    By implementing a data-driven strategy in text automation, companies can significantly accelerate their time-to-market. New offers and services can be described and published easily, effectively, and quickly. All text types can be adapted at any time and reach different target groups faster and in a more personalized way – without time-consuming coordination processes or cost-intensive coordination with external service providers. The high quality and variance of the different text types improve the ranking of the content on Google and other search engines. As a result, automated text generation brings valuable traffic to your websites, which ultimately leads to a significant increase in conversion rates.

  2. Large-scale content automation
    Large-scale content automation (“LSCA”) refers to the use of generative AI to scale content automation at the company level and across multiple languages and channels. Compared to manual processes, LSCA enables faster and more efficient creation of texts without increasing costs in proportion to the quantity of content. In addition to high-quality and varied content, even with large amounts of text, this ensures higher conversion rates and better cost efficiency.

  3. More efficiency and quality
    By leveraging generative AI and structured data from PIM systems, companies can quickly and easily create high-quality text. The integration of solutions such as Retresco’s content automation platform textengine.io into a PIM system enables the automated creation of relevant content, such as product descriptions, FAQs as well as similar text types, and their publication in the relevant channels and languages.

  4. Consistent brand identity
    Having a unique corporate language is becoming increasingly important, especially now with ChatGPT, GPT-4, etc. Finally, it is crucial that automated texts are not only created efficiently but also meet a brand’s high-quality standards and tone of voice. Through automated text generation, varied and high-quality content can be created at any time according to individual brand guidelines. Automation is based on the company’s own brand strategy specifications in order to create all relevant text types in a uniform way and with the desired wording. Companies benefit from addressing their customers consistently across all channels and touchpoints.

  5. Simple integration
    Common systems in the field of automated text generation are designed to tick every box in terms of text scaling. This makes it possible for content teams to efficiently set up content projects and achieve long-lasting performance upgrades without requiring programming skills. Structured product information can be easily obtained from the Product Information Management system. The integration of such systems is extremely straightforward and can be done internally without the help of developers. Once the data is uploaded, the platform creates language-specific text models, keeping the uniquely defined data points consistent across all languages. In this way, once a text model has been set up, it can be used for any desired language without any additional effort.

Data-based text automation with potential

The combination of generative AI, automated text generation, and a PIM system enables digital commerce companies to create high-quality, legally compliant text at scale. Retresco and Contentserv have seamlessly integrated their text automation and Contentserv Product Experience Cloud to ensure centralized product information management and to enable the automated generation of a wide variety of text types for all major channels and languages.

With the right strategy for data-driven text automation and the use of high-quality data, companies can increase their efficiency while saving time and resources – now with the help of GPT-4 or comparable models. Thanks to large-scale content automation, companies can consolidate their text automation and roll it out on a national and international scale. This leads to more online visibility, higher conversion rates, and ultimately more success in digital commerce.



Jan Saponara-Teotonico

Partner Sales Manager, Retresco

Since 2022, Jan Saponara-Teotonico has been Partner Sales Manager at Retresco, the leading provider of AI-based content automation, responsible for partner management, partner recruitment, and partner organization. His background is in the telecommunications industry, and he has extensive experience in cloud solutions. Among other things, he was responsible for partner management in the Microsoft Cloud segment as Business Development Manager at Ingram Micro, with a focus on Microsoft Cloud security and compliance products.

Is your Product Information Management effective?

Take the quiz to find out if you are well-equipped to face digitalization challenges.