The New Customer Journey: How AI Search Engines Are Rewriting the Marketing Funnel

AI search engines are fundamentally reshaping how consumers discover brands, collapsing multi-touchpoint journeys into single conversations. With 59 percent of Google searches now ending without a click and 58 percent of consumers using generative AI for product recommendations (up With 59 percent of Google searches now ending without a clickfrom 25 percent in 2023), marketers face the most significant disruption to customer acquisition since the rise of search itself. The traditional model where brands optimized to appear in search results to earn conversions is giving way to an environment where AI intermediaries provide synthesized answers, often without users ever visiting a brand's website.

From Funnels to Feedback Loops: How We Got Here

The customer journey concept has evolved through three distinct paradigms. The AIDA model , developed by Elias St. Elmo Lewis, gave marketers a linear framework: Awareness → Interest → Desire → Action. For over a century, this funnel shaped advertising strategy, assuming marketers controlled the message flow and consumers moved predictably toward purchase.

McKinsey's Consumer Decision Journey shattered this linearity. Analyzing nearly 20,000 purchase decisions, researchers David Court and colleagues discovered that consumers actually expand their consideration set during active evaluation: 63 percent of auto buyers added new brands after starting their search.

Moreover: two-thirds of touchpoints during evaluation were consumer-driven (reviews, recommendations, independent research), not company-driven. 

Then came Google's Zero Moment of Truth. Jim Lecinski's research quantified what seemed intuitive: 84 percent of shoppers said online research shaped their decisions, consulting an average of 10.4 sources before purchase (up from 5.3 sources just one year earlier). ZMOT validated massive investment in SEO and content marketing, establishing the paradigm that dominated digital strategy for over a decade.

The common thread through all three models? The assumption that consumers would actively search, browse multiple sources, and visit websites to gather information. AI search is dissolving that assumption.

The New Reality: Ask and Receive

The shift from “search and browse” to “ask and receive” is occurring faster than most marketers anticipated. Google AI Overviews as of March 2025 appear in 13 percent of all U.S. desktop search queries, representing a 102 percent increase in just two months. When AI Overviews appear, click-through rates drop by 35 percent. Perplexity AI processes 780 million queries monthly, and ChatGPT now has 800 million weekly active users. The customer journey, which was previously complex and multi-touchpoint, is now collapsing, cutting touchpoints in half.

The traffic implications are severe in all industries. Chartbeat data shows organic Google search traffic down 33 percent for publishers globally between November 2024 and November 2025. Publishers like Forbes and Business Insider report 40 to 55 percent declines. Yet here's the paradox: visitors arriving via AI referrals convert 23 times better than traditional organic traffic, according to an Ahrefs analysis.

Visibility Without Traffic: The New Marketer's Dilemma

It's no longer just about click-through rates; it’s about reference rates: how often your brand gets cited in AI-generated answers. This represents a fundamental strategic shift.

Traditional SEO optimized for rankings and clicks. The emerging discipline of generative engine optimization (GEO) optimizes for citations and brand mentions within AI responses. When researching both consumer and B2B products, most buyers will naturally evaluate one or more AI tools. Research from Princeton and Georgia Tech found that adding expert quotations improved AI visibility by up to 37 percent on Perplexity.ai, while citing authoritative sources increased visibility by 115 percent for lower-ranked sites.

Google's EEAT framework (experience, expertise, authoritativeness, trustworthiness) has become the currency of AI citation worthiness. Unlike traditional search, where backlinks dominate authority signals, LLMs can weigh recent sentiment and user-generated content more immediately. A brand mentioned positively across Reddit threads, review sites, and recent articles can gain AI visibility faster than it might climb traditional rankings.

The Path Forward Demands Dual Optimization

The “AI vs. Search” narrative is largely manufactured. Traditional SEO still remains the primary traffic driver. The winning strategy isn’t abandoning proven approaches; it’s augmenting them and adjusting to a new reality. Marketers today should apply a two-pronged strategy: (a) maintaining traditional SEO, and (b) optimizing for AI platforms.

The customer journey hasn’t disappeared; it’s evolving. In the near future, some consumers will continue the traditional search-and-browse pattern, while others will increasingly delegate research to AI assistants. Brands that master both pathways won’t just survive the transition; they’ll shape how AI represents their entire category to the next generation of buyers.

Practitioners should prioritize these immediate actions:

• Start creating your own customer journey internally. Communicate with other departments and ask customers how they heard about you, then make note of each touchpoint via CRM until a deal is closed. First-party data is essential in this new era
• Invest in both traditional SEO and paid ads as complementary strategies. Evaluate whether it’s more efficient to capture visibility through earned strategies or paid placements, while acknowledging AI's role in zero-click searches that can significantly reduce CTR. Not all keywords trigger AI Overviews yet, but for those that do, flag them and assess brand visibility against competitors. Integrate schema markup for better AI citability and A/B test hybrid campaigns that blend paid ads with SEO to offset vulnerabilities, while monitoring metrics like AI citation rates alongside traditional CTR to avoid over-reliance on outdated models, as organic traffic could decline 20-40% for affected sites.
• Focus on direct interactions with customers. Through webinars, live videos, live product showcases, and similar formats, build authentic connections and control touchpoints, while addressing scalability by integrating AI tools for efficiency. These are resource-intensive and may not scale easily for global audiences without on-demand replays, which can reduce real-time engagement. To enhance ROI, prioritize high-value prospects and measure outcomes via engagement rates (e.g., B2B webinars convert 57% of registrants to attendees) and follow-up conversions
• Generate content that AI search engines surface in answers. Structure content for extraction: Lead with direct 40- to 60-word answers, use clear headers and FAQ formats, and implement schema markup (JSON-LD) across key pages. In addition, build citation-worthy authority: Publish original research, secure expert quotes in industry publications, and maintain consistent brand messaging across all touchpoints.

• Track new metrics. Monitor brand mentions in AI responses, citation share versus competitors, and AI referral traffic separately from traditional organic. HubSpot’s AI Search Grader and Semrush's AI Toolkit now allow brands to audit their AI visibility, tracking how often and how favorably they appear in generative responses.

Ultimately, the brands that win in this new customer journey will be the ones that accept loss of control as the price of relevance and respond by becoming unmistakably authoritative wherever AI systems learn and reason. You can no longer count on being discovered only after a user searches; you must be embedded in the trusted sources AI draws from long before any question is asked. That means treating visibility as an interconnected ecosystem challenge rather than a single-channel optimization problem, investing in credibility as deliberately as performance, and designing marketing strategies that assume fewer clicks but higher intent. The funnel is no longer something you guide step by step, it is something you influence upstream, long before the conversation begins.

Jovana Zrnic is a growth and performance marketing leader with extensive experience across B2B SaaS, global consumer brands, and venture-backed companies in the U.S. and EMEA. Her work centers on building scalable, data-driven growth systems that integrate paid media, marketing technology, automation, and AI-enabled optimization. She has led regional and multi-market performance programs for established brands and startups alike, combining strategic leadership with hands-on execution.