AI is transforming the world of advertising by enabling brands to deliver more personalized, engaging, and efficient campaigns. From fine-tuning audience targeting to utilizing AI to supplement creativity, AI is showing up in a variety of ways for agencies and brands.
These examples showcase how brands are using AI to reach consumers and engage them in unique ways that leave a lasting impact. For Kiosk, the key lies in identifying ways in which these tools can be best used to enhance our client campaigns and drive results in a rapidly evolving digital world.
Enhanced Audience Targeting and Personalization
One of AI’s most valuable contributions is its ability to process vast amounts of data to gain consumer behavior insights. AI-driven algorithms analyze browsing habits, purchase history, demographics, and other consumer touchpoints to create detailed audience profiles. At Kiosk, we use AI-driven audience segments on platforms like Facebook to reach niche audiences, improving ad relevance and engagement. TikTok’s AI-based ad delivery system similarly tailors ads based on real-time interactions, predicting which content is most likely to engage specific users. AI-driven targeting has led to impressive results for Kiosk clients, with TikTok having higher engagement rates – typically CTRs 2x the average on Facebook – and improved ROI as ads are delivered to users who are most likely to respond positively.
Creative Content Generation and Visual Innovation
AI is now enabling brands to create high-impact visuals, making it an attractive tool for brands in the luxury and fashion sectors, who are increasingly using it to produce captivating, on-brand imagery.
Using advanced generative models, AI can produce images that fit a brand’s aesthetic while exploring new, often surreal, creative directions. High-fashion brands like Jacquemus, Loewe, and Louis Vuitton have incorporated AI-generated images into their ad campaigns, merging human artistry with machine creativity.
Louis Vuitton worked with David King Rubn, an artist who used AI tools to create surreal visuals for its Spring/Summer 2023 campaign. This approach reduced the reliance on traditional production processes, as AI generated virtual models, elaborate sets, and lighting effects, creating a futuristic and immersive narrative while showcasing the collection.
The AI-generated characters added a layer of intrigue and visual impact to the campaigns. Louis Vuitton has similarly adopted AI to experiment with abstract or imaginative elements, creating ads that capture the intrigue and innovation of their collections and brandscapes of their buildings.
These AI-generated visuals not only resonate with audiences seeking novelty, but also streamline the creative process, providing an agile way for brands to rapidly generate and test new aesthetic explorations.
Interactive Customer Engagements
Brands are utilizing AI to create dynamic, immersive customer experiences through interactive tools like virtual assistants, chatbots, and augmented reality. These interactions make the consumer experience more engaging and give brands valuable insights into their customers’ preferences and behaviors. Virtual influencers, powered by AI, are also making waves, appearing in digital campaigns to represent brands in unique ways that can adapt in real-time to audience responses.
L’Oréal’s ModiFace, a virtual try-on tool, leverages AI to allow customers to “try on” different makeup shades and products. This creates a unique, tailored shopping experience where consumers can experiment with different looks in real-time. For L’Oréal, this boosted online engagement and translated into higher conversion rates, as customers felt more confident in their purchases after trying products virtually.
Such interactive experiences are fast becoming a cornerstone of e-commerce, reducing the hesitancy that often comes with online shopping.
Predictive Analytics for Better Decision-Making
Predictive analytics leverages AI’s ability to detect patterns and make forecasts based on past data. This enables brands and agencies to anticipate consumer behavior, demand patterns, and emerging trends.
Predictive analytics has become particularly useful for identifying the best times to launch campaigns, assessing potential returns on investment, and understanding seasonal demand spikes or wanes. Brands can also optimize budget allocation and make quick adjustments to maximize their ad effectiveness based on real-time feedback.
BMW applied predictive analytics in their advertising strategy by analyzing data to identify peak times for specific car model promotions. Using AI-driven insights, they determined which times of the year, and even which hours of the day, were ideal for marketing specific models. By focusing on these high-impact windows, BMW maximized its ad spend and boosted the likelihood of conversions. Predictive analytics helped BMW anticipate consumer interest and adapt their strategies swiftly, ensuring they reached audiences when engagement was highest.
Automation in Ad Campaign Management
AI-driven automation is a game-changer for ad management, handling everything from audience segmentation to A/B testing and real-time budget optimization. Automated platforms use machine learning to continually assess ad performance and make adjustments, ensuring that ad spend is optimized and that the right audiences are being targeted. This level of automation has made it easier for brands to scale their campaigns while still ensuring that ads remain relevant and effective.
Google’s AI capabilities for SEM have revolutionized campaign management for agencies like Kiosk. With tools like Performance Max, Google uses machine learning to optimize bids, placements, and targeting across its platforms.
Kiosk’s media buyers utilize Google’s algorithms to adjust ad placements in real-time based on performance, automatically allocating more budget to high-performing ad sets. This automation enables our team to reach new audiences, optimize campaign efficiency, and boost ROI without needing to micromanage every detail.