Table of contents:
- What is Generative AI?
- The battle for AI dominance
- Uses of AI in Ad Tech
- Generative AI limitations and ethical concerns
- Conclusion
AI has been a part of the advertising industry for quite some time. With its remarkable ability to process vast volumes of data and leverage predictive modelling, AI has already facilitated programmatic advertising and real-time optimizations. However, one particular advancement is capturing the attention of marketers worldwide: Generative AI. Unlike the usual AI approaches, Generative AI goes beyond processing existing data; it possesses the extraordinary capability to generate original content, opening up new paths of creativity and personalization. In this article, we delve into the transformative role of AI in advertising, with a specific focus on Generative AI and the opportunities it presents for brands and marketers alike.
What is Generative AI?
Generative AI is a type of artificial intelligence that generates content based on the data it has been trained on and the input parameters provided.
Generative AI can create content such as:
- Text: provide detailed answers to specific questions, write articles, ad copy, scripts, translations, etc.
- Images: create new images based on existing ones, and create images based on descriptions.
- Audio: generate new tracks, sound effects, and replicate voices.
- Video: produce an entire video based on one prompt using text-to-video functions, including transitions, effects, and voiceovers.
The capability of generating such diverse content based on prompts gives this technology the power to be a real disruptor across the advertising world and not only. It has the potential to change the way we create and consume content.
The battle for AI dominance
Chat GPT - Revolutionizing Advertising
The most popular AI tool used by marketers is Chat GPT (Generative Pre-trained Transformer), launched in November 2022 by Open.ai. Since its launch, it has generated immense interest and broken records with over 100 million users in just two months.
It is an AI chatbot that is trained to interact with users in a dialog format. Based on large amounts of data and computing techniques, ChatGPT has the capability of stringing words together to deliver meaningful outputs. Users can ask questions, and give detailed instructions and from these prompts, ChapGPT will provide responses, write copy, draft emails, hold a conversation, and explain code in different programming languages.
ChatGPT can remember past conversations and can use the data that it has been previously fed to form answers in new conversations in a similar way to a human.
To showcase the extent of the ChatGPT capabilities, Ryan Reynolds used the chatbot to create an ad copy for an ad for his Mint Mobile company. He summarized the result as: “That is mildly terrifying but compelling.”
Google's answer to ChatGPT - Bard AI
Bard AI is Google's flagship generative AI chatbot that simulates human conversations, launched in March 2023. Bard AI can provide information, write code, translate content, analyze images, and, in addition to text responses, it can also provide visual responses.
A major benefit of Bard AI comes from its data set, compared to Chat GPT. While the latter uses data available up to September 2022, Bard is connected to the internet, meaning that it can provide up-to-date information. Moreover, it can summarize web pages when it is being fed links.
The tool can augment Google search and can be integrated into websites or applications to give responses based on natural language processing and machine learning a more realistic feel. So the integration between Google Search and Bard would mean that users can get more conversational search results.
Further integrations with other Google services, such as Gmail or Google Docs, have also been announced and are eagerly awaited.
Uses of AI in Ad Tech
AI targeting and personalization
Generative AI holds immense potential for targeted advertising, allowing advertisers to dynamically target and segment their audience. By leveraging the analytical power of AI, vast amounts of data can be processed to identify unique patterns and trends related to customer behavior, transactional history, demographics, and more. This in-depth understanding of individual preferences and interests empowers advertisers to tailor their messaging to resonate deeply with each targeted audience segment.
Through generative AI, advertisers can deliver highly personalized and compelling content that speaks directly to the needs, desires, and motivations of their customers. This level of precision targeting not only improves campaign effectiveness but also fosters a more engaging and meaningful connection between brands and consumers.
Generative AI for Ad Creatives
Generative AI has caught the attention of tech giants who recognize its potential in creating highly engaging ad experiences for users and boosting ad return on investment (ROI). Using AI, ad platforms could tailor the perfect ad for every impression, leveraging a library of pre-uploaded components like images, videos, texts, audio, etc.
This means that instead of delivering a one-size-fits-all ad, the AI algorithms will dynamically assemble the most relevant and impactful combination of components to match the specific context and preferences of each user and ultimately convert the user.
This approach allows advertisers to maximize the effectiveness of their ads, delivering more compelling messages that resonate with individual users. Therefore, AI has the potential to take the optimization of ad creatives to a whole new level.
Campaign testing with AI
The first step in testing with the help of generative AI is to train the models on specific advertising data. This will allow the AI to learn the patterns and characteristics of advertising materials and generate relevant new variations.
Based on the training data, AI will then generate different variations or even entirely new concepts, which will be tested and evaluated. The end goal is to use the results to refine the input to get the best-performing outputs.
Generate new ideas
Have you had a brainstorming session with Chat GPT yet? Generative AI is a great source of ideas and suggestions; however, the output does sometimes require a human touch. It can be used for ad titles, ad copy, CTAs, drafting emails, writing product descriptions, etc.
You can feed it your campaign’s performance data and ask for ideas for the next steps or improvements. Although this will require some human input, too, it could help solve many performance issues.
Generative AI limitations and ethical concerns
As powerful as AI algorithms may be, they lack the nuances of human judgment and empathy. It is essential to remember that AI is a tool, not a replacement for human creativity and ethical decision-making. Human oversight is crucial to ensure that situations such as the ones below are avoided:
- Generative AI creates content based on the information it is trained on; therefore, there is a serious risk of copyright infringement. The content created is likely to resemble something that already exists.
- The ease with which voices and images can be duplicated and the collection and analysis of personal data can pose a severe privacy and security threat if not handled properly or if it is used for malicious purposes.
- This technology can be used to spread fake content and proliferate misinformation.
- Due to the data sets that the AI has been trained on, there can be biased, toxic, and harmful outputs which can sometimes be discriminatory.
Conclusion
To summarize, the integration of generative AI in advertising has the potential to revolutionize the ad tech industry. With its ability to analyze vast amounts of data, generate compelling content, and optimize campaigns in real-time, AI offers marketers new avenues for reaching their target audiences with personalized and engaging messages. By using generative AI, marketers can tap into the creative power of algorithms to generate variations, test campaigns, and uncover insights that can fuel campaign success. However, it is crucial to remember that AI is not a standalone solution but rather a tool that should be combined with human expertise and strategic thinking.