SAS’s Jonathan Moran explores how AI transforms MarTech—from hyper-personalized search and immersive UX to data-rich retail media networks.
The marketing technology (MarTech) landscape is in a state of dynamic evolution, driven by the relentless advancement of artificial intelligence (AI), the increasing importance of data, and the ever-changing dynamics of consumer behavior. Jonathan Moran, Head of MarTech Solutions Marketing at SAS, offers valuable insights into this transformation. His expertise sheds light on the key priorities for businesses navigating the AI-powered search disruption, the revolutionary impact of AI on product creation, and the expanding influence of retail media networks.
Search in 2025: AI-Driven Personalization and the Voice Revolution
The future of search is about delivering hyper-personalized experiences with unprecedented speed, seamlessness, and voice-enabled functionality. As consumers increasingly expect instant and highly relevant results, traditional search methods are being augmented by AI-powered solutions. According to Moran, Natural Language Processing (NLP) is the linchpin in this evolution.
“The ability for businesses to localize (according to region or dialect) and optimize (according to indexed content, past interactions, other individualized information) search results using Natural Language Processing will be key to delivering an ideal search experience – particularly as AI-enabled chat and search interfaces emerge,” Moran states.
Businesses must invest in systems that can quickly ingest, process, reply to, and contextualize consumer input within visually intuitive interfaces. The convergence of NLP, Natural Language Understanding (NLU), and Natural Language Generation (NLG) will be crucial for brands that foster consumer loyalty and trust. The emphasis is on creating a search experience that is efficient and anticipates individual needs and preferences. This will be heavily driven by AI’s ability to understand and interpret user intent, moving beyond simple keyword matching to grasp the nuances of human language. The rise of voice search, driven by the proliferation of smart speakers and mobile assistants, further necessitates the adoption of NLP to process and respond to spoken queries accurately.
Also Read: Why Marketers Need a Data Diet in the Age of AI Overload
AI’s Transformative Impact on UX/UI: The Rise of Immersive Experiences
Artificial intelligence, particularly generative AI, is not just improving UX/UI; it’s fundamentally reshaping it. By automating design processes, generating creative content, and personalizing user interactions, AI is enabling the creation of more engaging and intuitive digital experiences. Moran draws on a recent SAS and Coleman Parkes research study to illustrate how generative AI is being integrated into MarTech:
- Foundational Use Cases: A majority of marketers (around 45%) are leveraging generative AI to enhance core software features, including chatbots for customer service, text and image generation for content creation, and basic recommendation/classification for personalized content delivery.
- Enhanced Use Cases: A smaller segment (15-20%) is utilizing generative AI for more sophisticated applications, such as creating new audience groups based on AI-driven insights, generating video and interactive content for richer engagement, performing audience targeting with greater precision, and designing/optimizing customer journeys for maximum impact.
- Immersive Use Cases: While still nascent, the vision of operating software entirely through conversational AI is gaining traction. Twenty percent of respondents believe that within three to five years, we will see widespread adoption of truly immersive, chat-based software interactions, where users can interact with applications in a natural, intuitive way.
Moran concludes, “We are going to see generative AI enable the movement of UX/UI design from having the ability to address foundational and enhanced uses to operating software from a truly immersive experience in the near future.” This signals a move towards software that is not just user-friendly, but also user-centric, adapting to individual communication styles and preferences. This shift has the potential to democratize access to technology, making complex systems more accessible to a wider audience.
Retail Media Networks: Balancing Opportunities and Challenges in a Data-Driven Ecosystem
Retail Media Networks (RMNs) are rapidly gaining prominence in advertising, offering brand advertisers increased control and ownership of valuable data. These digital platforms, operated by retailers, allow brands to advertise their products directly to consumers at the point of sale. Moran explains the symbiotic relationship between retailers and advertisers within these networks:
“Retail Media Networks provide brand advertisers more control and ownership from a 0-2 party data perspective. As big retail brands offer their digital channels to third-party businesses and manufacturers for advertising purposes at the point of sale, the big retail brand receives tons of data around consumer behaviors and preferences…and the third-party business or manufacturer receives comprehensive insights (to inform new product development, packaging, assortment ranging, and campaign effectiveness).”
RMNs empower retail brands to leverage consumer data for more precise audience segmentation and ad ROI measurement. By understanding consumer behavior within their digital ecosystems, retailers can offer highly targeted advertising opportunities. Simultaneously, third-party businesses gain actionable insights to refine product development, packaging, and campaign strategies, leading to more effective marketing campaigns and increased sales.
Also Read: Is the Future of Marketing Shaped by Ethical Algorithms?
However, Moran cautions that the growth of RMNs has its challenges. Key issues that need to be addressed include:
- Ad data and campaign fragmentation and silos: The proliferation of RMNs can lead to fragmented data and difficulties in measuring campaign effectiveness across different platforms.
- Data and communication transparency: Ensuring data collection and usage transparency is crucial for building trust between retailers, advertisers, and consumers.
- Increasing competition among RMNs: As more retailers launch their own RMNs, increased competition could drive up advertising costs and create challenges for advertisers in managing their campaigns.
Overcoming these obstacles will be essential for businesses to fully capitalize on the potential of RMNs and create a more cohesive and effective advertising ecosystem.
