AI stole my credit card 💳

Hello marketers. Welcome to AI Marketing School, where we dish out the latest and greatest in AI-powered marketing.

In this week’s issue:

• AI Marketing Update: The era of agentic eCommerce is upon us

• The Stack: Massive report from Influencer Marketing Hub

Onwards!

AI MARKETING UPDATE

Agentic eCommerce is coming

OpenAI’s Operator is tantalizing us with a future of agentic commerce – AI that doesn’t just suggest products but actively browses, compares, and buys on your behalf. 

According to OpenAI, “We’re collaborating with companies like DoorDash, Instacart, OpenTable, Priceline, StubHub, Thumbtack, and Uber.”

Competitors like Google, Nvidia, and Shopify are already working on their own AI shopping agents.

eBay is another of the first platforms to integrate with Operator —- Nitzan Mekel-Bobrov, eBay’s Chief AI Officer, wrote in a rather babbling press release:

“Our collaboration with OpenAI will introduce a new paradigm of discovery and shopping online.”

You can see how Operator will handle eCommerce purchasing below.

It all sounds quite far-fetched, maybe? Uber is already so easy to use. How can you make it easier? 

Will people really trust an AI agent to make actual purchasing decisions for them?

All very reasonable questions, but time moves on, and it’s only a matter of time before such things become slowly normalized. That’s a familiar cycle — so let’s anticipate and adapt.

The key point is that, until now, digital marketing has assumed human decision-making.

Search rankings, paid ads, and influencer marketing all relied on capturing user attention and guiding their choices. 

But when AI becomes the buyer, the rules change completely.

SEO, ads, and discovery in an AI-driven market

If AI handles purchases, traditional SEO and ad strategies lose power. First, traditional SEO and ad-based discovery could become disrupted.

AI shopping agents won’t scroll through endless product pages or fall for a well-placed banner ad. They’ll look for structured data, best prices, and logical decision trees. 

If a brand isn’t properly indexed for AI-driven searches, it may become invisible.

What could this mean in practice?

• AI-driven search will surface items users might never have found manually. Unlike traditional search, which relies on keywords, AI will scan massive inventories to recommend the best options based on user intent.

• AI buyers will probably prioritize efficiency – meaning users on marketplaces like eBay or Amazon must optimize their listings for AI decision-making. This might include writing enhanced machine-readable descriptions and making sure your listings offer as much data as possible. In other words, writing a good product title won’t be enough!

• Human psychology will have less impact on purchasing. AI doesn’t have emotions – it won’t care about your brand’s ethos or carefully curated aesthetic. It won’t interact with sales tactics, discounts, FOMO, etc, in the same way. Think about your last online shopping experience — how you can be tempted into getting stuff you don’t need. AI might not be so fallible!

So what can we do? Here are some top strategies to consider for creating AI-optimized product listings and related content:

• Structured product data – AI agents will likely favor listings with clear, detailed attributes. Ensure every product includes standardized specifications, pricing transparency, and complete metadata. If key details are missing, AI may not even consider your product.

• Machine-readable descriptions – AI will scan for direct, factual information: dimensions, materials, compatibility, warranty details, and certifications. If your product description is vague or lacks specifics, it could be ignored.

• AI-first discovery – Traditional keyword-based SEO might decline in importance as AI agents pull from broader structured data sets. Brands will need to ensure their products are indexed properly with well-formatted schema markup and accessible, crawlable content.

• Anticipate common AI queries – AI agents will be asked direct questions like “What’s the best budget laptop for video editing?” or “Find me a lightweight rain jacket for hiking under $100.” Brands must structure product pages and FAQs to explicitly answer these kinds of practical, intent-driven queries.

• Create dynamic FAQs – Instead of basic static FAQ pages, brands should incorporate conversational elements that answer layered, follow-up questions. Example: “What’s the difference between your two best-selling ergonomic chairs?” AI tools prioritize content that mimics real customer interactions.

• Optimize for AI shopping agents – Product descriptions should be structured to match the way AI will retrieve and compare data. Example: Instead of just listing "waterproof," include detailed breakdowns like “Waterproof rating: 10,000mm, suitable for heavy rain and snow.”

Brands definitely shouldn’t ignore human influence; most of these techniques cater to both humans and AI.

AI may handle transactions, but humans set the preferences and make the final calls — so elements like brand trust, social proof, and expert endorsements will still matter.

The key is to blend AI-friendly optimization with strong brand positioning to stay visible in both human and AI-driven purchasing decisions.

THE STACK

New report on AI’s impact on SEO

Influencer Marketing Hub just released a massive marketing report with insights from some top experts. 

I wanted to explore some of the main findings and how they tie into what we discuss here at AI Marketing School. 

How AI impacts search

According to growth marketer Kevin Indig's analysis, only 6% of Google's AI Overviews contain the exact search query.

Evidently, search engines are evaluating content based on how well it demonstrates expertise and comprehensive understanding.

This goes some way to explain why Reddit's traffic exploded from 180 million to 752 million visitors after Google's October 2023 EEAT update. 

Their traffic value now exceeds $309 million because Reddit naturally demonstrates what AI algorithms look for: authentic expertise and genuine user value in discussions.

When someone knowledgeable reads an article, they don't count keywords or check backlink.

They assess whether the content shows real understanding and provides valuable insights. That's what search engines are now doing.

It ties into the conversational method of content writing discussed above — it’s time to strike conversations with readers and share your expertise rather than just smashing keywords in standard blog content.

The rise of first-party data

Material backed by original research and data performs 76% better than generic content. 

When you explain what you've personally discovered works and doesn't work, you're creating content that can't be replicated by those without your specific experience.

While this might conjure up images of huge reports and surveys — think McKinsey or Gartner — real first-party data exists in every business, regardless of size. 

• A local artisan food store can share insights about their seasonal produce.

• A small accounting firm can document common tax filing mistakes they've helped real clients avoid, with first-hand expertise.

• A graphic design agency can analyze how different design styles impact engagement across industries, using real client projects to illustrate what works and why.

Making all of this work in practice?

Here are the three strategies anyone can implement today:

1. Transform experience into content

Start by looking at what you and your team actually know and do.

Research shows search engines now recognize genuine expertise, so focus on documenting your strategies, methods, and solutions — capturing the valuable knowledge that already exists in your organization.

• A web development agency documents its exact process for improving site speed, including specific improvements achieved for different types of websites

• An interior designer shares detailed before/after project images with specific material choices and why they worked

The bottom line? Create content which you can inject your expertise into. Make it people-centric. Build that digital evidence that you’re out there doing your thing.

2. Develop content from real interactions

Your customer interactions are a goldmine of content opportunities. Pay attention to the questions that keep coming up, the challenges you regularly solve, and the patterns you notice.

Turn these insights into content that demonstrates real understanding. The data shows this kind of authentic problem-solving content performs exceptionally well.

• A law firm creates detailed guides based on the most common questions from initial client consultations

• A gym documents the actual progression of client success stories, including specific workout modifications that helped overcome plateaus

Similar to the above, but this time, you’re channeling learnings and educational experiences into content. Rather than being guided by keywords, this is stuff you KNOW is important in your topic and niche.

It might not be ‘known’ to Google at all — Google is designed these days to locate topics that aren’t totally exposed.

3. Create content worth discussing

The huge growth in Reddit's traffic shows that search engines value content that sparks genuine discussion.

Share insights that make people think and encourage knowledge sharing. This isn't about creating controversy - it's about offering valuable perspectives that contribute to broader understanding.

• A restaurant shares unexpected findings about which wine pairings actually worked best with their dishes, based on customer feedback

• A marketing agency reveals data about which social media posting times worked best for different industries, inviting others to compare results

Forget chasing the algorithm for traditional SEO. Start demonstrating authority in a way both AI and real humans can recognize and talk about.

Hope you enjoyed this week’s issue. If you missed the last newsletter, you can read it here.

If you found it useful, please recommend it to a friend or colleague.

Until next time. Happy marketing.

—The AI Marketer