What happens to brand growth when consumers increasingly turn to AI assistants instead of relying on familiar brands or traditional search results? As generative AI becomes a more influential part of product discovery and purchasing decisions, marketers face new questions about how brands gain visibility, enter consumers' consideration sets and compete for attention. In MSI Working Paper, Tri-System Brand Growth: The AI Mediation Layer, researcher Pablo Ulpiano González Castro introduces a framework that adds AI availability to the established concepts of mental and physical availability. Drawing on brand-growth theory, an experiment and cross-category measurement research, the paper examines how AI-generated recommendations may reinforce existing brand advantages or create new opportunities for competing brands, and what these changes mean for marketing strategy and brand measurement.
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News aggregators can exert substantial influence through the algorithms that determine which stories and sources receive prominent placement. An analysis of Russia’s Yandex News found that top-five homepage referrals drove large increases in outlet traffic, while an algorithm change that reduced exposure for independent outlets did not lead consumers to abandon the platform. Affected outlets subsequently changed how they wrote and packaged their news, showing that distribution algorithms can shape production as well as consumption.
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Generative search may help consumers move from broadly stated needs to more focused shopping decisions. In a field experiment involving more than 6.4 million users of Meituan—a Chinese e-commerce platform, consumers given AI-generated responses placed more orders and generated greater transaction value than those using a conventional keyword search. They also spent less time browsing and concentrated their attention on fewer, more relevant categories and merchants.
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Every two years, the Marketing Science Institute (MSI) asks every member company Trustee to provide input to help set priorities for the research that will guide our activities for the next few years.
These priorities enable MSI to engage in its most critical mission: moving the needle on important marketing problems.
One of the priorities focuses on the need to develop new approaches that enable firms to gain insights from multiple approaches, to synthesize, to bring together disparate methods to drive action. There is also a sense that the old methods aren’t working as well, and that some of the traditional indicators and metrics are less effective.
Here are some topics that illustrate where significant research is needed in this area:
- How to bring multiple sources and types of information together to gain insight and to make better decisions (e.g., big data meets unstructured data; data scientist meets anthropologist). Can such synthesis be automated?
- Integrating behavioral theory and marketing frameworks into big data marketing
- How can firms speed up the process by which they collect data, synthesize, identify insights, take action, get feedback, and do any necessary course correction? Is this process different for B2B and B2C?
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