A new metric paradigm
First and foremost, marketers should brace for a complete overhaul of traditional metrics. The keyword-centric approach that has long been the cornerstone of SEO and paid search strategies is becoming obsolete. AI-driven search systems, often not supported by traditional ads, render keyword targeting less effective. Moreover, conversational AI captures nuances and interests that keyword analysis simply can’t match. As a result, the classic analytics marketers have relied on will likely decline in relevance and effectiveness.
Redefining on-site experiences
As traditional search metrics decline, the importance of on-site engagement will skyrocket. Every interaction on a brand’s digital properties becomes critical. Marketers need to prepare for a future where visitors expect an AI-driven experience on par with their favorite AI assistants. This means moving beyond traditional navigation structures like drop-down menus and developing intuitive, conversational interfaces that can instantly guide users to the information they need.
Privacy takes center stage
The rise of AI in search is set to catalyze more stringent data privacy regulations. Marketers should expect a significant push for comprehensive data privacy laws that protect consumers’ interactions with AI systems. This shift will necessitate a new approach to data collection and usage. Marketers must pivot toward zero-party data interactions, focusing on turning these into meaningful, trust-based first-party relationships with clear consent. The ability to navigate this new privacy landscape will be crucial for maintaining consumer trust and compliance.
The trust factor
With AI mediating many consumer interactions, brands that can establish themselves as reliable, accurate sources of information will have a significant advantage. This means not just being present across various platforms but ensuring that the information provided is consistently accurate, up-to-date, and valuable to the user.
Adapting to conversational search
Content strategies will need to evolve to answer complex, multifaceted questions—rather than simply targeting specific keywords—and require a deep understanding of user intent and the ability to provide contextually relevant information. While challenging, this transition also offers exciting opportunities for brands to connect with their audiences in more meaningful and impactful ways.
Businesses must adopt a structured data approach within their organizations. This means bringing together typically siloed data stores that host the knowledge necessary to power AI experiences for customers. We’re talking about entities like your business locations, facts about your products, information about services you provide, open job positions, frequently asked questions about your business, and specific details like allergens and ingredients in your menus—all hosted in a knowledge graph.