Organic traffic, once the lifeblood of many online publications, is on the decline. Top tech outlets such as The Verge, Wired, and TechRadar have seen their traffic drop by 58% since 2024, according to Nieman Lab .
AI search is partially responsible for the shift. The more people use AI to answer their questions, the less they need to hop between websites to get the information they’re looking for.
According to Klaviyo’s 2026 AI Consumer Trends Report , 60% of global consumers interact with AI at least weekly, and 39% of consumers have purchased an AI-recommended product in the last 6 months.
AI search is consolidating the discovery and research phases of the buyer’s journey to one chat window. It also creates a wealth of contextual data: our report found that when searching with AI prompts, 78% of people say they include emotional or personal context at least some of the time.
To show up in AI search results, you’ll need to build out your product pages to include more of these contextual signals. This is a moment of opportunity to adapt your approach to product discovery with AI in mind.
In this guide:
- AI search terminology
- AI search trends
- Showing up in AI searches
What is answer engine optimization (AEO) for ecommerce?
AEO is the optimization of online content so that AI models include your products in their responses to queries.
AI-generated answers appear in Google AI overviews, answer engines like ChatGPT, Gemini, and Claude, and voice assistants like Alexa or Siri.
Compared to SEO, where the goal is to rank as high as possible in search results, the goal of AEO is for AI models to cite your content. While many SEO practices are transferable to AEO, the main difference is that content is optimized for long-tail conversations rather than keywords.
Which AI search trends should B2C brands pay attention to?
AI is where many consumers first start searching for products. Similar to how emerging social media created new discovery channels for brands in the early aughts and 2010s, LLMs are an emerging opportunity to showcase your products in a new way.
Consumers are using AI for product discovery
Our AI Consumer Trends Report found that Google and traditional search engines are still the most common starting point for consumers, but LLM use for product discovery is growing. Importantly, LLMs are a place where people can both discover new things and get things done.
This trend is particularly pronounced among high-frequency, high-trust users. According to our AI Consumer Trends Report, which defined 4 distinct AI personas based on consumer trust and usage levels, AI Enthusiasts who use AI a few times a week or more consult AI more than traditional search, social media, and their family or friends when:
- Learning a new skill
- Getting ideas or inspiration
- Planning activities or experiences
- Making life decisions
- Understanding a complex topic
Meanwhile, 83% of AI Enthusiasts say that within the last 6 months, AI recommended a product they didn’t previously know about that they ended up purchasing.
Even those who use AI less frequently say LLMs have influenced their shopping process. For example, 35% of AI Evaluators, who generally trust AI and use it monthly, say AI has introduced them to a product they’ve gone on to research further.
Search queries are longer and more specific
Traditional search is somewhat conversational with long-tail keywords, but LLMs have extended this trend further. Many consumers no longer primarily search with keywords. Instead, they search with phrases or questions.
According to our AI Consumer Trends Report, over half (52%) of consumers use moderately detailed queries of 3–7 words with multiple descriptors when searching with AI.
Gen Z and daily AI users are 27% more likely than the average consumer to use queries containing 8+ words or even full paragraphs.
LLMs are a goal-based discovery channel
Consumers are also sharing more context with AI. According to our research, 78% of people include emotional or personal context at least some of the time when using AI. For example, a shopper might ask for “something to cheer me up,” or “a gift that feels thoughtful.”
These types of prompts reflect a shift toward what Nekuda calls “ goal-based shopping .” A goal-based shopper searches based on something they want to achieve instead of starting with a specific product in mind.
Let’s say someone is heading to a music festival in a few weeks. Rather than separately searching for comfortable sneakers, a reusable water bottle, weather-appropriate outfits, etc., they may prompt an LLM with an overall goal to feel comfortable at the festival.
The AI model would then search for contextual information on brand websites to serve up product recommendations that meet the objective.
How can brands show up in consumer AI searches?
The growing importance of AEO doesn’t mean SEO is no longer relevant. In fact, the two work hand in hand. Here’s where to invest special attention to complement the SEO work you’re already doing:
Optimize your ecommerce store for AI search
On a technical and page level, here’s how to make your content easily digestible to answer engines :
- Enable crawling. Configure your robots.txt file to allow crawling by AI models and any content delivery network or hosting infrastructure.
- Include clear, structured product information. Use schema markup to support grounding for AI models. For example, build a content knowledge graph that can signal the relationship between pages using the standardized vocabulary of schema.org . Accurate identifiers like Global Trade Item Numbers (GTINs) and Stock Keeping Units (SKUs), pricing, and availability data are other types of information that LLMs use to verify products before recommending them.
- Add more context to product descriptions. AI models prefer content in question-and-answer formats because that’s how shoppers converse with them. Whether you publish this content as standalone articles or on existing product pages, go beyond descriptive information and make it clear what specific concerns your product addresses.
- Use a consistent brand voice across all channels. Use consistent language across your site, and make sure all content is clear and cohesive. Inconsistencies muddle an LLM’s ability to understand your website and may damage your brand’s authority.
Invest in AEO-friendly content types
Answer engines look for context and detail to offer users complete answers to their queries. Whereas SEO is about keywords, AEO is about complete sentences, content blocks that answer standalone questions, and overt product differentiation in your category.
If you don’t know where to start meeting these requirements, here are some AEO-friendly content types that can get you there:
- Customer reviews and UGC: To address specific buyer concerns, AI crawlers scan all available product reviews for contextual information. Incentivize detailed reviews or user-generated content (UGC) with surveys that ask specific questions and discounts that encourage longer reviews and real photos from customers.
- Detailed FAQs: AEO-friendly FAQs offer more context and may contain more “outlier” questions than typical FAQs. Tools like Semrush can help you analyze where your brand is cited in answers, which can direct the questions you include in your FAQs.
- Buying guides: Buying guides that help customers navigate a specific product category can signal your brand’s authority and position your products in your category. Consider AEO-friendly buying guides as the ultimate source for contextual data, which can feed answers to goal-based shopping queries.
- Comparison content: Comparison content also helps LLMs understand where your product fits in your category, so they can promote it when given the right context. Publish resources that weigh the pros and cons of different products as they relate to user concerns, like, “How AHA, BHA, and PHA exfoliants affect dry skin types.”
- Lists and roundups: Prioritize lists that address contextual concerns. “Best running shoes for knee concerns” and “types of energy fuel for long-distance running” are more helpful for AEO than “best running shoes” and “types of energy fuel,” which work better for traditional SEO.
Keep your content fresh and relevant with Klaviyo
Klaviyo B2C CRM makes it easier to connect with customers with AI, with:
- Composer : autonomously builds, refines, and optimizes marketing campaigns based on a prompt, goal, or idea
- K:AI Customer Agent : delivers personalized, real-time support, recommends relevant products, and hands off issues to a human when necessary
- Klaviyo Reviews : helps customers leave reviews faster with AI-generated headlines, while helping brands understand review sentiment more quickly
With Klaviyo, you get built-in agentic AI that uses your real-time customer profiles to launch marketing campaigns and resolve customer requests—on one platform, with humans in the loop.
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