Adieu, Adieu, Trillium, Adieu!

After a thrilling term of marketing poetry, it is time for Fakespeare to hang up his Trillium and wander absentmindedly back into the wilderness of time. The business-minded bard passed along this website to me, and I shall aim to bring this blog to worthy completion.

I have a tendency to find my way into rabbit holes. That means sometimes I spend far too much time on tangents. But sometimes, I learn important ideas from those rabbit holes that add complexity to my understanding of concepts and help me extrapolate how digital marketing today might evolve in years to come. For my final post, I am going to discuss five future-focused takeaways that grew from digging out of rabbit holes.

Understanding how AI “thinks”

Share of Model (SOM) is a new metric for the AI era that measures how often, prominently, and favorably a brand is surfaced by Large Language Models (LLMs) in response to consumer prompts (Dubois et al., 2025). Unlike traditional “share of search,” which reflects human intent, SOM emulates how an AI “thinks” about and recommends a brand.

Companies are learning quickly to adjust their SEO tactics to better connect with AI search. If a brand discovers they are missing from certain AI recommendations, they can shift their strategy from keyword-heavy content to problem-solving content, helping build stronger conceptual AI associations with their brand.

As search gets more complex, it will become more difficult to game the search ranking through keyword trickery. Becoming integrated with a share of an LLM will become the new “above the fold”.

The Virtual User Mind

Modern search engines prioritize user-focused metrics, which means that Search Engine Optimization (SEO) and User Experience (UX) Design have converged into a single synergy (Wang, 2023). A successful website must be both findable (SEO) and usable (UX); properly respecting search engine algorithms while fulfilling the needs of users.

Because AI crawlers assess sites with increasing complexity, marketers must treat UX as if it is SEO. Keywords alone are adequate; rather, they can guide the development of intuitive navigation and content that answers specific user queries. AI search now considers sites in their entirety and rewards pages that provide a superior browsing experience.

As AI progresses in speed, complexity, and ubiquity, search engines will essentially grow into virtual user minds—customized to model the psychology of individuals like you and me (Blackman, 2026). What will our experience be like on the future internet? Will we relax into our boat and let an AI skipper navigate for us? Will we turn on our devices and say “Google, what do I want to search for today?” And then, how will we know the difference between our own decisions and those of our always-on agent?

AI-Driven Hyper-Personalization

Hyper-personalization uses the predictive power of AI to anticipate individual customer preferences based on their behavior, allowing brands to craft experiences that make customers feel seen and valued (Russell, 2026). It transcends traditional demographics to provide real-time, data-informed personalized interactions at scale.

As technology progresses, we can imagine the emergence of personalized virtual influencers. Each of us will get customized editorial content from an AI influencer that speaks just to us, in the way we like about the things we like—our own little echo chamber.

Services today like chatbots may grow into complex ecommerce companions, providing superior customer service and personalized shopping guidance. While any user of Spotify or Netflix will testify that the technology is not quite there yet in terms of modeling individual tastes, rapid advancements are on the horizon.

Predictive Analytics

Already, predictive lead scoring uses machine learning and historical data to rank potential customers based on the likelihood that they will engage, convert, or otherwise complete an action (“How AI is Impacting Digital Marketing”, 2025). Models can be built using social media engagement, webpage interactions, or participation in brand events, combined with demographic and psychographic data to create scoring systems that respond to changing consumer behavior and tendencies. This precision allows businesses to prioritize high-value leads in online campaigns and generate highly optimized engagement strategies for them, rather than wasting resources and ad spend on uninterested prospects.

As predictive analytics continues to improve, leveraging deep learning models, we could extrapolate that digital marketing will become increasingly efficient to the point that consumers are looking to their own predictive model to understand what they like and dislike, at which point the snake is just eating its own tail.

The Omnichannel Everywhere All at Once Strategy

An omnichannel approach is a lead-nurturing strategy where a business provides a seamless, integrated customer experience across all available channels, platforms, and devices (Stokes, 2018). It ensures that whether a customer is shopping on a mobile app, browsing a desktop website, or walking into a physical store, the brand message and service level remain consistent.

But are we moving toward a world like in Minority Report? Will behavior tracking and marketing messages follow us literally everywhere we go, using biometrics to trigger the perfect message just for us?

Wrapping Up

Internet marketing is fabulous fun and experiencing the improvements in outcomes from improvements in the technology we get to use is in many ways exciting.

But considering the trajectory of so many marketing technologies towards ubiquity, autonomy, and omniscience, I pose this question to both marketers and customers: is this the world we want to live in?

References

Blackman, A. (2026, March 22). AI is rewriting the old rules of Google search and SEO. The Wall Street Journal. https://www.wsj.com/tech/ai/google-search-seo-ai-tactics-5efb9f99

How AI is impacting digital marketing. School of Professional Studies at Wake Forest University. (2025, October 19). https://sps.wfu.edu/articles/how-ai-impacts-digital-marketing/

Dubois, D., Dawson, J., & Jaiswal, A. (2025). Forget what you know about search. Optimize your brand for LLMs. Harvard Business Review Digital Articles, 1–15. https://hbr.org/2025/06/forget-what-you-know-about-seo-heres-how-to-optimize-your-brand-for-llms

Russell, M. (2026, March 6). AI will shape the future of marketing. Professional & Executive Development | Harvard DCE. https://professional.dce.harvard.edu/blog/ai-will-shape-the-future-of-marketing/#Meet-Our-Expert

Stokes, R. (2018). eMarketing: The essential guide to marketing in a digital world (7th ed.). Red & Yellow Creative School of Business. https://www.redandyellow.co.za/textbook/

Wang, X. (2023). Conceptualizing synergies between SEO practices and UX design for enhanced website usability and engagement. Journal of Digitainability, Realism & Mastery (DREAM), 2(5), Article 105. https://dreamjournal.my/index.php/DREAM/article/view/105