Rewiring Growth: Why Signal Engineering and Comparative Content Are Essential for the AI-Driven Customer Journey

The world of growth marketing is undergoing a seismic shift, driven by platform automation and the rise of Large Language Models (LLMs). A recent discussion, “Rewiring Growth for the AI-Driven Customer Journey,” featuring Daphne, CMO of Voyantis, and Josh Bliskll, AI Strategist at Profound, outlined a clear mandate for modern marketers: master data fidelity and own the narrative, or risk being left behind.

The key takeaway is a pivot from traditional tactics to strategic AI inputs.

The New Role in Paid Media: Signal Engineering

As advertising platforms like Google and Meta become increasingly "agentic," handling targeting and creative decisions, the marketer’s role is changing from tactical execution to strategic instruction.

"We really need one thing from you," explained Daphne, paraphrasing a Meta executive, "which is for you to tell us what business outcome you want us to optimize for."

This necessity has given rise to Signal Engineering (05:34). Marketers must now focus on sending the perfect predictive signal to ad platforms about the future value of a user. The challenge arises because the true Lifetime Value (LTV) of a customer often extends beyond the standard 7-day conversion window (29:19).

To overcome this, companies must:

  • Leverage First-Party Data: Use machine learning to analyze proprietary, non-PI data, moving beyond simple data points to identify complex combinations of user attributes that predict high LTV (14:57).

  • Employ Predictive Values: Instead of waiting for a deterministic conversion, marketers must send a constantly updated, predicted value back to the ad engines, ensuring the algorithm optimizes for high-quality customers (30:04).

Winning the AI Search Game with Utility-First Content

On the organic side, LLMs and AI Overviews are flattening the traditional marketing funnel. According to Josh Bliskll, the modality of search has shifted from learning to doing (07:13). Users are no longer looking for a list of links to click; they are looking for immediate answers, making the AI model the arbiter of product discovery (08:36).

For brands to maintain visibility, the content strategy must adapt:

  • Comparative Content is King: Data shows that the most commonly cited content across answer engines is comparative and listicle content (09:33). AI models prefer to pull from sources that have already done the heavy lifting of evaluation.

  • Focus on Utility: Brands must create utility-first content that clearly and deeply compares their products against competitors. "It's a gutsy thing to have to do," Bliskll notes, "but owning that comparison is basically mission critical" (10:26, 19:10).

  • New KPIs for Influence: While traditional click attribution is murky, traffic influenced by AI is "incredibly warm" (23:50), with conversion rates reported to be 5–7 times higher (23:24). Because the user journey is shortened, new metrics like visibility and citations are emerging as essential KPIs to track influence (25:13).

In summary, the AI-driven customer journey demands that brands evolve. Success hinges on a dual strategy: maximizing the fidelity of paid media through Signal Engineering and establishing authority in organic channels through proactive comparative content.

Profound, AIOptimization, SignalEngineering, GrowthMarketing, AISearch, LTV, AI Marketing, AI Optimization, Signal Engineering, Growth Marketing, AI SearchFrancesca Tabor