The BENEFITS of AI Audience Targeting
This is part 1 of 3 in this article series about Artificial Intelligence for Audience Targeting.
As artificial intelligence (AI) becomes ubiquitous, it is adopted in marketing for multiple functions, including audience targeting. Even people that are already using AI regularly tend to focus on the benefits without giving a second thought to its challenges, limitations and concerns. This article series will discuss the pros and cons of using AI for audience targeting specifically, yet many of those reflections are valid for other fields too.
In the first part, the discussion begins with understanding what AI Audience Targeting is, how it is different from traditional audience targeting, and what are the benefits for companies and for the consumer. Next, we will dive into the challenges, limitations and concerns of AI Audience Targeting. To conclude, I’ll recommend good practices for AI Audience Targeting.
How AI and marketing got together
‘Artificial intelligence’ is the name given to computational technologies that simulate tasks typically associated with human intelligence, like learning, solving problems, perceiving patterns, processing natural language, and making decisions. Despite the fact that AI has been around as an academic discipline since the 1950s, the release of ChatGPT in 2022 is what made advanced artificial intelligence more accessible to the general public, and encouraged the development and popularization of other similar technologies.
When it comes to marketing technologies, AI is the buzzword of the moment. In a similar way, the 2010s popularized the term ‘machine learning’, amidst the increase of data-driven decisioning in businesses from all sorts of domains, mainly due to significant improvements in data infrastructure in that decade (higher speed internet, cheaper storage, and better processing power). Because of that, AI adoption is currently imperative for marketing companies: it will soon not be a mark of being in the forefront of innovation anymore, but a requirement to avoid lagging behind.
How AI can be used for audience targeting
Audience targeting is a marketing strategy, especially powerful for digital media, that segments a broad audience into groups based on demographics, location, interests and behaviours. By analysing and understanding these segments, marketers can reach out to people with more relevant and personalized content, reducing inefficient ad spends and improving conversion and return of investments (ROI). This practice has been around since at least the days of print & radio in the early 20th century, but it became a more precise activity with the popularization of the internet in the 1990s and 2000s. With browser cookies, companies were able to target ads based on browsing history and behaviour. Search engines allowed targeting based on keywords. And the rise of social media and programmatic digital advertising enabled advanced and automated buying and placing of ads using very granular data about each group of people.
Applying artificial intelligence to audience targeting has the potential to improve all steps of the process, as indicated in the comparison below:
The use cases of AI for audience targeting include, but are not limited to:
Media insights. The possibility to analyse massive datasets and provide real-time monitoring across media platforms enhances the capability of media professionals to deliver actionable insights. It can help monitor brand mentions, identify relevant emerging narratives in social media, and fine tune cross-channel strategies.
Cultural insights. AI enables more granular and dynamic information about consumers’ motivations and mindset, rituals, behaviours, beliefs and values, aesthetic codes, symbols and icons, and communities. It improves the potential of brands to respond to fast-changing cultural trends, making them resonate more with what is currently most engaging to consumers.
Passion points. The combination of data sources scraped by AI goes beyond interests that are traditionally mapped on consumer surveys, and dives deeper into the nuances of consumers’ passions. This allows brands to understand and interact with their audiences in a deeper and more nuanced way.
Occasions. When and why consumers choose certain products doesn’t have to be an assumption or a predetermined list of data points in a survey. Real-time monitoring, sentiment analysis and trends detection done by AI can help brands uncover previously unknown demand spaces, and further understand the occasions already known.
Product innovation. By identifying the audience’s preferences, passions and needs, AI can help brands unlock opportunities for product innovation and improvements that wouldn’t otherwise be picked out.
Creatives development. Experimenting with variations of ad creatives became easier with AI. Testing them with synthetic AI audiences and even A/B testing them in production to find what appeals mode with the target audience makes AI useful for developing and refining effective creatives.
Content development. Similarly to ad creatives, content can be developed and tested using AI, especially for highly personalized audience targeting. Artificial Intelligence can automate different tasks that used to be time consuming, such as writing articles and posts, and editing videos in relatively high quality.
Tactical planning. There are many ways in which AI can help simplify workflows and automate tasks for media planning. Most media platforms are already adopting AI resources to optimize campaign execution, shifting from manual adjustments to real-time automated tweaks.
How COMPANIES can benefit from AI audience targeting
Some of the use cases mentioned already hinted at the benefits to companies, but taking a closer look into it helps take the leap of embracing AI capabilities on audience targeting.
Most of it boils down to saving time and being more cost efficient. AI elevates the decision process, with less preliminary research needed, integrating more data sources, filling previous gaps in the data, adapting and optimizing in real time, and improving predictions. Quicker insights, quicker strategies, and faster iterations lead to workflow efficiency and scalability. Less impactful creatives and strategies can be tested beforehand and not produced or executed, saving resources. The team benefits from it with more time for creative strategies, and the democratization of insights. AI powered audience targeting makes it easier to achieve both global reach and local relevance, by taking into account regional nuances (behaviours, preferences).
All those benefits are still a competitive advantage, but using AI for audience targeting is soon becoming an industry standard.
With artificial intelligence, it is possible to get insights beyond the data that was initially available. AI can bridge some of these knowledge gaps. However, when allowing AI to make assumptions and requesting insights beyond the databases available and trusted, there’s less guarantees of how trustworthy the information is. The answers from the AI may get ‘hallucinations’, unreliable sources and misguided information. It’s a blessing and a trap that will be addressed further in the second and third articles of this series.
How CONSUMERS may benefit from AI audience targeting
Even consumers benefit from the application of artificial intelligence technology to audience segmentation.
Consumers targeted by ads refined by AI may be shown more relevant content, with less intrusive spam ads, and more interesting personalized experiences and tailored recommendations. AI audience targeting simplifies product discovery. Moreover, it improves accessibility and inclusivity, with automated content translation and transcriptions.
Addressing the pitfalls to seize the benefits
It is clear that there are many benefits for companies and consumers in using AI for audience segmentation. However, embracing this technology without awareness of its pitfalls can be damaging to both too. The second article of this series will dive into the challenges, limitations and concerns of AI Audience Targeting, and the last part of this article series will bring recommendations of good practices to seize the benefits while minimizing the risks.