By Purva Gupta, Co-Founder and CEO of Lily AI
According to Bain & Company estimates, companies are seeing anywhere from a 15% to 25% reduction in organic web traffic across industries.
Where did the traffic go?
This was a hot topic among advertisers and agencies at the 2025 POSSIBLE conference, and the answer is, it’s complicated. From AI-powered search and shopping to social media and retail media, search is a fractured landscape where not all queries lead to a click, not all purchases require a click to an e-commerce site, and now with agentic AI, not all purchases begin with a click.
Zeroing In On Zero-Click Search
According to Bain & Company, new research indicates that roughly 80% of consumers now rely on “zero-click” results in at least 40% of their searches—those instant, AI-generated summaries that surface answers without requiring users to visit a website.
That certainly accounts for some portion of lost organic web traffic, yet what about people who are actively shopping and ready to click or buy?
Both Lily AI’s own 2025 consumer survey research and Bain’s recent survey show that about 40% of consumers already report using AI for shopping, including AI-powered search and answer engines.
To both simplify the buyer’s journey for consumers and potentially complicate it further for brands and retailers, answer engines are rolling out native shopping features such as Perplexity’s Buy with Pro and ChatGPT’s new shopping features.
Non-Branded Search: Where Discovery Meets Demand
As Bain also notes, “As organic clickthrough rates fall, marketers are losing share of voice in high-value, non-branded searches—that initial discovery phase where people seek answers and opinions before committing to a specific brand. These crucial moments are where customer discovery and subsequent conversion often occurs. Generative AI isn’t just disrupting search traffic—it’s turning the customer journey into an algorithm-driven narrative.”
This isn’t just a technical shift—it’s a strategic wake-up call for brand and performance marketers alike.
Non-branded search is the ultimate battleground for discovery that leads to demand and sales. Consumers shopping for something new expect search to be smart enough to understand their needs and intent, such as:
– “summer dress ideas for outdoor work events”
– “moisturizer for combination skin that won’t clog pores”
– “eco-friendly throw pillows for a boho living room.”
Unless product catalogs and assortments are enriched with the right AI-readable attributes such as fit, benefit, style, occasion, or aesthetic, your products won’t be found. Brands that fail to speak the language of consumer intent will lose the discovery game to those that do.
The search world, from digital agencies to SEO platforms, is already evolving. Take SEMrush and Ahrefs, both must-have SEO tools, you can find detailed ranking and keyword traffic information to monitor and optimize for AI Overview visibility and clicks.
Digital agencies have taken this idea a step further. Take creative innovation agency R/GA, for example. R/GA recently launched an AI SEO tool designed to track how brands appear across emerging AI search engines like ChatGPT, Gemini, Anthropic, Perplexity, and DeepSeek. It’s a sign of where the industry is headed: toward a future where tracking performance means tracking presence across generative interfaces, not just SERPs.
From Search Engine Optimization to Search Everywhere Optimization
According to Neil Patel, Search Everywhere Optimization is a new mindset for tackling a fracturing search landscape.
To be clear, it’s still a Google world, with Google driving 63% of US web traffic. See the figure below from Sparktoro and Datos, showing the diversity of sources driving traffic and clicks today.
Google is still a critical, if not the main pillar, of any search optimization strategy.
The good news for busy marketers and e-commerce teams is that there are universally beneficial tactics that retailers can use to maximize brand and product visibility on Google and beyond:
– Attribute-Rich Product Data: Every product needs structured data fields that reflect how people naturally search. Not just “crew neck tee,” but “soft t-shirt for layering under a blazer” or “stretchy black tee for postpartum body.”
– Consumer-Led Language: AI search engines prioritize relevance and usefulness. That means optimizing not for industry jargon, but for how shoppers actually describe and seek products.
– AI-Compatible Content: From PDPs to PLPs and landing pages, product metadata must be structured in ways that help AI find best-fit products.
From Clicks to Context: The New Discovery Algorithm
Traditional SEO focused on keywords, backlinks, and structured metadata. But AI-first search engines like ChatGPT, Gemini, Perplexity, and Anthropic are changing how discovery works. These generative models prioritize contextual understanding over exact-match keywords. That means brands must shift from optimizing for crawlers to optimizing for AI comprehension.
Enter the new worlds of GEO and AEO: Answer Engine Optimization (Perplexity and ChatGPT) and Generative Engine Optimization (AI Summaries in Google and Bing). Having an AEO and GEO strategy and process in place ensures that product content, descriptions, and metadata are structured and enriched in ways that AI systems can accurately parse and use to generate answers.
The convergence of AI and Search is creating a new discovery algorithm—one that’s powered by consumer intent and contextual intelligence, driven by natural consumer language, and surfaced by large language models. It’s not about keyword stuffing and other legacy hacks —it’s about clarity, context, and alignment with how people speak, search, and shop.
The bottom line? To win, brands must evolve from optimizing for engines to optimizing for answers. It starts and ends with optimized product data and metadata, powered by Product Content Optimization.
