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Darden Note Maps Four-Strategy Framework for AI Search Marketing

Darden professors propose a four-strategy ISM framework as AI search hands consumers single answers, collapsing the AIDA funnel and sidelining traditional SEO spend.

  • Whitler and Pettiette propose the Information Search Marketing (ISM) framework with four strategies: Generative Engine Marketing, Generative Engine Optimization, Search Engine Marketing and SEO.
  • A real-life test cited in the note: the query "best queen mattress for back sleepers for less than $2000" returned a single, obscure mattress recommendation from an AI platform versus pages of options from traditional search.
  • Whitler states AI algorithms disregard traditional search marketing spend: "The new AI-based algorithms don't care how much you spent on traditional search marketing."

A new technical note from the University of Virginia's Darden School of Business argues that AI search platforms are collapsing the traditional marketing funnel by handing consumers a single answer instead of pages of options — and it proposes a four-strategy framework for brands to stay visible.

The note, titled "AI-Based Search: Information Search Marketing and Generative Engine Optimization," is written by Kimberly A. Whitler, the Frank M. Sands Sr. Associate Professor at Darden, and Michael Pettiette, former CEO of High Give Marketing Partners. It frames the shift from link-based results to AI-generated answers as a structural break in how consumers move from Awareness to Action.

"When consumers performed a traditional Google search, they were basically looking for a solution to a problem, and Google would help narrow the thousands or millions of solutions," Whitler said. "AI platforms are shifting the consumer search process; increasingly, they are shifting from simply providing thousands of options to actually making decisions directly for consumers."

The funnel collapses to a single answer

For most of the 21st century, search results fit the AIDA framework — Awareness, Interest, Desire, Action — by presenting consumers with a set of options they filter themselves. A searcher comparing tennis racquets, dermatologists or Paris hotels would meet a bevy of well-known brands while sifting links. AI platforms change that dynamic. Consumers now ask detailed, context-rich questions, and the platform may return one solution rather than a list — sometimes with the option to purchase directly inside the platform, skipping straight to the final A in AIDA.

The authors cite a real-life example from the case: a query for the "best queen mattress for back sleepers for less than $2000." A traditional search engine returns endless pages of possibility, and the shopper travels the funnel encountering established brands. The same query entered into an AI-based platform produced a single recommendation — a fairly obscure mattress with a fervent fan base.

Two factors drive this outcome, according to the note. First, AI simply does not deliver the quantity of solutions that traditional search does. Second, while consumers have long searched for "the best" product, AI now supplies a specific, direct answer. A past query for the best hair dryer surfaced articles ranking the Top 10 hair dryers; the consumer did the sifting to move from Awareness to Interest. Now, Whitler says, AI pushes consumers directly to Desire and even Action.

She compares the experience to walking into a grocery store for shampoo and browsing the full assortment versus visiting a hypothetical AI-enabled retailer that presents only one option — one seemingly tailored to your stated needs.

"For the consumer, this can be good if the basis of the recommendation is legitimate, authentic, and accurate," Whitler said. "For the marketer, this changes everything. They went from being in the consideration set to being excluded from it."

That exclusion carries direct financial consequences for firms that have built their visibility through SEO and paid search. "The new AI-based algorithms don't care how much you spent on traditional search marketing," Whitler said. "It can be measuring something different."

Whitler likens the magnitude of the change for traditionally trained marketers to the move from the Yellow Pages to Search 1.0. Savvy marketers are aware of the shift and moving fast, she says, while those ignoring it invite significant risk.

The Information Search Marketing framework

Because adoption of AI-focused practices varies dramatically across the industry and no common language has yet settled, Whitler and Pettiette propose an approach they call the Information Search Marketing (ISM) framework. It integrates paid versus organic influence across traditional versus AI-driven search, producing four complementary strategies that marketing leaders should manage together:

  • Generative Engine Marketing — the paid efforts within or alongside AI responses
  • Generative Engine Optimization — the organic efforts to structure content optimized for AI responses
  • Search Engine Marketing — the paid efforts to increase visibility in traditional search engine results
  • Search Engine Optimization — the organic efforts to structure content optimized for traditional search engine results

The framework does not retire traditional search tactics, which the authors call still critical. Instead, it pushes marketers to commit resources to a new channel in a landscape many do not yet fully understand.

"This is less a shift from traditional to new search and more an expansion of the repertoire," Whitler said.

The note also pushes back on the assumption that younger, digital-native marketers hold an inside track in the new search environment. Channel usage does not make one a channel strategist, Whitler argues, and winning strategies exist for marketers of any background willing to become expert in the new landscape.

"Just because somebody consumes a lot of TV or social media or spends nine hours a day on their phone, it does not make them a superior strategist that can strengthen consumer-brand experiences and generate demand," she said. "My mother was a world-class shopper. She could provide terrific feedback on her shopping experience. But this is quite different than being able to create and execute strategies that drive consumer preference."

What to watch

The organizations that stay ahead, the authors write, will treat new search as a key strategic priority — committing to understanding the landscape and running test-and-learn programs to determine how the pieces of traditional and AI-driven search fit together. Marketers who do nothing, or who cling exclusively to traditional search tactics, risk falling out of sync in a digital world increasingly shaped by AI capabilities.

"You have to learn the tools," Whitler said. "AI is either going to be an advantage for you and your organization or a disadvantage."

The full technical note, including the Five A's of Search Success, is available through Darden Business Publishing.

via store.darden.virginia.edu (Original)

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Staff writer covering business strategy at SERP Journal.

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