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Rellify White Papers
Why ChatGPT alone is not enough
The Large Language Model ChatGPT in direct comparison with the Rellify Custom Language Model Relliverse™: Which model makes content strategy and topic selection easier?
Over the past year, ChatGPT has made an incredible breakthrough in marketing, with thousands of marketers using the tool for a wide range of tasks. Text creation is certainly at the forefront of this, but we are hearing more and more from customers and prospects that ChatGPT is also good for content strategy and topic generation.
Customers who are already doing this are naturally wondering why they need a custom language model like Relliverse™. Since ChatGPT is practically free, a legitimate question is: Can Relliverse™ identify relevant topics and needed content better than ChatGPT?
To demonstrate the advantages of a custom language model like Relliverse™ over ChatGPT, we put it to the test using our customer Best Egg, who uses a Relliverse™.
See for yourself what weaknesses ChatGPT has when it comes to developing a content strategy and identifying topics, and why a company-specific, proprietary custom language model like the Relliverse™ gives you a massive advantage over your competitors when it comes to topic identification!
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Whitepaper: "Supercharged AI" for the next generation of content intelligence
AI for the entire content value chain: company-specific AI models linked to general AI models like ChatGPT
In the area of content marketing, we are currently seeing an increasing use of generative AI like ChatGPT. Essentially, AI is used to quickly generate content based on a few prompts. This is resulting in a massive production of synthetic content that is usually good writing but not differentiated and authentic in the sense of being branded content.
It is therefore becoming increasingly important to differentiate your content, which requires a data-driven approach to identifying relevant topics and trends. Typically, this involves a manual process supported by tools such as Google Trends or SEMRUSH. However, these methods of topic discovery and planning do not use intelligent deep learning. As a result, they lack the solid understanding of the data in neural networks that is needed to produce content that stands out from the competition.
The Relliverse™ is a completely new approach to the systematic use of AI in the idea and topic generation phase: The Relliverse™ shows at a glance what is worth writing about and why the resulting content will be strategically important or essential. This saves a lot of time in developing the topic architecture and content strategy.
Learn in this white paper from Prof. Dr. Peter Gentsch how companies can “improve” existing large language models, adapt them to their specific business requirements, and outperform their competitors by using their own proprietary language models.
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Study: Human versus machine: Who writes the better content?
Machines write better than agencies and people. This is the result of a new study by the Institute for Conversational Business at Aalen University. In the study, landing pages, blog posts and social media posts from international top brands were compared with AI-generated alternatives.
Aalen / Cologne, 28.09.2022 – Artificial intelligence writes better marketing texts than humans in agencies – this is the result of a study by Aalen University under the direction of AI expert Prof. Dr. Peter Gentsch. “Both according to the subjective evaluations of our test group of over 100 people and according to the objective results of the Flesch metric, the variants of the compared marketing content written by artificial intelligence are better than their originals,” says AI researcher and pioneer Prof. Dr. Peter Gentsch.
As part of the study “Human or machine: who writes better content”, Gentsch selected and analyzed landing pages, blog posts and social media posts from Telekom, Vodafone, Garnier, L'Oreal, M&Ms and Starbucks at the Institute for Conversational Business at Aalen University. The AI content platform from MarTech start-up rellify was then used to find the relevant topics and keywords for this content. Based on the results of this AI analysis, the AI writing platform GPT-3 from OpenAI was then used to produce new content on the topics and keywords of the original content.
“We then submitted the AI texts and the originals to 100 randomly selected people for evaluation,” says Gentsch about the study design: ”At the same time, we classified the original texts and the AI versions according to the scientifically recognized Flesch metric.”
The results of both evaluations were just as clear as they were incredible, according to AI expert Gentsch: “Both the subjective and objective evaluations showed that the AI-generated texts were slightly to significantly better. From the test subjects‘ point of view, the AI texts were not only easier to read and more appealing, but also, surprisingly, more ’personal',” says Gentsch, summarizing the survey results. But the AI-generated content also scored better in terms of the Flesch index, the scientist said: “In terms of objective readability, the typewritten texts are consistently better, sometimes significantly so.”
Despite these results, however, Gentsch emphasizes that AI is not yet a better author than a professional copywriter or an agency per se: ”It's not possible yet without human input.” On the one hand, the machine-generated input from the AI ideation phase has to be checked and possibly “filtered” or cleaned up by hand. On the other hand, fine-tuning the prompts and parameterizing the GPT-3 platform is absolutely critical to success. “Only a fact check can ensure that any factual errors made by the writing AI are detected and corrected,” says the professor.
Gentsch therefore also qualifies the thesis postulated at the beginning that machines would write better texts than humans. The human factor is still crucial for the quality of the results of AI-supported content creation, he concludes: “Human expertise is still needed to set up the AI, but above all for quality assurance and fact checking. At the same time, however, the study also shows that with this support, better results can be produced in less time – and so at lower cost. My prediction is therefore that the tasks involved in content creation will shift – in the future, people will be needed less for the actual writing of texts, but more to focus on strategic aspects, the storyline and, always, the quality assurance of the intelligent machines.”
Whitepaper: Next Generation AI & the Relliverse™
The revolution of enterprise marketing
In his current whitepaper “Next Generation AI & the Relliverse™ – The Revolution of Enterprise Marketing”, Prof. Dr. Peter Gentsch provocatively argues that companies must use the algorithms of the AI superpowers Google & Co. for themselves in order to survive in the long term.
You can see a brief insight into the theses developed by Prof. Gentsch in the white paper here:
- The AI used by Google & Co. no longer leads only to automation and process optimization – as in marketing automation, for example – but increasingly also to creative innovative processes
- The combination of intelligent algorithms and data becomes the key success factor for the operational and creative use of AI in marketing
- Businesses must try to understand and harness Google’s algorithms to survive
- For consumers, the influence of AI in search results means an increase in convenience and quality of results. For companies, it means pressure to increasingly produce content that fits the new visibility and relevance logic.
- For content to be successful on Google in the future and to prevail over all other content, it must comprehensively address a specific topic and offer real added value – i.e. be truly relevant to that topic
- Companies need to understand, as far as possible in real time, what the relevant trends and topics are, what customers are looking for, what content is particularly well received and how competitors are positioning themselves
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How can you use data to boost your marketing performance?
In this clip, we’ll show you the key factors for using data the right way to boost their content marketing success.
- KPIs: Clear key figures for measuring success
- Insights vs Noise: Distinguish between important data for content marketing and the data that can simply be ignored.
- Competition: tips to determine benchmarks and gain competitive advantage.
- X Factor: Learn what the X-factor is and what most companies neglect so far
Our Whitepaper: „How AI-Assisted Writing is Revolutionizing Content Creation.“
- How can you use AI to produce relevant content?
- What impact does AI have on Google rankings?
- What roles does AI play in search engines?
AI is already being applied in many industries and fields, and marketing is no exception. In terms of influencing Google rankings and the amount of data that needs to be processed, only AI can deliver fast and successful results.
In this whitepaper, marketing expert Prof. Dr. Peter Gentsch explains why content production with AI support is a long-term and worthwhile investment.
Companies should assign content relevance, not SEO, top marketing priority. In doing so, resources will go into constantly monitoring and optimizing content relevance.
