Traditionally, customer discovery is a top-of-funnel, hard-to-measure activity. However, as consumers use conversational AI to find products and solutions, these interactions will become the next major performance marketing channel with clear metrics for driving outcomes.
Structuring marketing teams in channel-specific silos forces them to optimize for internal structures rather than the fluid, non-linear path customers actually take. This creates a fragmented view of performance, leading to wasted effort and missed opportunities.
Traditional marketing reacts to expressed intent, like a search query. AI-powered conversational interfaces allow brands to engage consumers during their open-ended discovery phase, helping to shape and create demand before a specific product is even considered.
To avoid debates over misleading metrics like ROAS, marketing technology should be configured to optimize directly toward the client's own "source of truth." This could be Google Analytics, Adobe Analytics, or a complex marketing mix model, ensuring total alignment on what constitutes success.
As consumers increasingly use AI assistants for discovery, the key to success will be strategically blending paid placements and organic, helpful information within these multi-turn conversations. This convergence is an emerging opportunity that few are discussing.