Advertising's AI Revolution: Unleashing the Power of Intelligent Marketing
The benefits of artificial intelligence are only expected to grow over time, with generative AI adoption outpacing that of smartphone and tablets in the U.S. While AI has been a buzzword for years, only now are marketers grasping the reality of what it can offer.
Alongside growing adoption, we've seen an influx of players across the advertising ecosystem turn to AI to adapt to changing consumer behavior as well as to address data privacy regulations and the eventual removal of third-party signals.
With these changes, marketers must lean into the technology to optimize their consumer touchpoints and campaigns. Here’s why.
Create Conversational Dialogs With More Effective Ads
Increased competition among marketers will fuel innovation aligned with what consumers are looking for — and how they look for it.
We’ve seen an uptick in brands and retailers adding chatbots alongside on-site search, suggesting changing consumer standards for product discovery and with that, advertising opportunity like sponsored product placements.
To ensure success, brands need to acquire data about consumer engagements. A brand's conventional engagement data, from sources like shopping behaviors and search terms, can now be complemented by new sources such as prompts and conversations with emerging shopping assistants. This private data can be used to refine large language models (LLMs), enabling the delivery of more tailored consumer shopping experiences and enhancing performance advertising.
LLMs can function as an interactive conversational layer alongside existing AI-powered product recommendation engines. This combination has the potential to enhance consumer satisfaction by merging consumer education and support with anticipation of product needs.
Redefine Targeting in a Privacy-Focused Era
Brands are beginning to redefine targeting strategies that leverage AI private models on smaller, consumer consented brand data sets, and larger public models like Google PALM and ChatGPT. The transformation of how we think about targeting is made possible by these public models, which are trained on massive common-sense knowledge from the web. This intelligence enables LLMs to predict user interests and anticipate their responses to advertising. By coupling public models with private data in privacy protecting ways, brands can achieve better predictive accuracy without compromising consumer privacy.
As a result, brands can craft more personalized messaging than ever before and explore the potential for truly interactive advertising experiences.
Optimize Retail Media for Enhanced Customer Engagement
New generative communication modes are also transforming retail media through personalized product suggestions directly on retailer sites.
Through the ability to automatically generate unique experiences for consumers based on their conversational interactions, prior behaviors and purchasing history, advertisers can increase their opportunities to capture consumer attention and drive product interest, sales and loyalty. Retailers can also optimize targeting, bidding, and ad placement, meaning they can allocate advertiser resources more efficiently.
Several industry players making first-mover advancements serve as case studies for retailers looking to enter the space. For example, Walmart uses natural language tools to provide smart substitution suggestions and answer customer queries. Similarly, Instacart introduced the AI-powered “Ask Instacart” feature, which allows users to ask questions in their natural language to receive relevant product recommendations and information related to product details, food prep, and more. These examples suggest generative AI is and will be a crucial component of the customer shopping experience.
The ad industry’s future will depend on its ability to harness the potential of AI to establish meaningful connections, drive business growth, and provide exceptional user experiences. By embracing AI, advertisers will reshape their communication strategies and forge stronger connections with their audiences.
Todd Parsons joined Criteo as chief product officer in August 2020. He is responsible for product strategy and new product innovation to diversify and transform Criteo's platform offerings.
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Todd Parsons joined Criteo as Chief Product Officer in August 2020. He is responsible for product strategy and new product innovation to diversify and transform Criteo's platform offerings. For over a decade Todd has built marketing solutions at the intersection of consumer identity and data. Prior to Criteo, his team established OpenX as the first people-based programmatic marketplace. As CPO of SocialCode, Todd developed products to activate and measure first-party audiences across Facebook, Amazon, YouTube and other platforms. Earlier, Todd led Acxiom's Marketing Services business and founded two venture-backed startups; Aditive, acquired by Acxiom in 2014, and BuzzLogic, the first SaaS for social media measurement and analytics.