From Prompts to Presents: How the 2025 Holiday Season is the ‘Smartest’ Time of the Year

The 2025 holiday season, spanning Halloween, Black Friday, and Christmas, will mark the first true test of generative artificial intelligence's influence on shopping. Up until now, consumers have largely used AI tools for vague inspiration or validation. But in 2025, we’ve seen the dynamics shift. Queries moved from “wireless earbuds” to “what’s a sustainable tech gift for my teenage daughter?”

As consumers get used to AI as a discovery channel, retailers that still treat it as “SEO 2.0” may find themselves caught flat-footed.

Here are three under-the-radar shifts defining this new AI shopping era and how early movers are testing them already.

1. Be Memorable to the Model, Not Just Rankable in Search

We’ve all heard the buzz about “AI-optimized product pages,” but the real game changer is something subtler: optimizing for model recall. In the generative engine optimization (GEO) paradigm, the goal is to become an integral part of the AI’s internal thought process, rather than merely appearing in the search index.

So, how do you make your brand memorable to an algorithm?

• Tell mini stories, not specifications. Instead of listing features, weave quick, intent-driven scenarios, like “a dorm-friendly speaker for late-night study sessions.” These provide AI agents with context, enabling them to match your product to real human needs.
• Back it up with proofs. Include facts, unique metrics, awards, sustainability stats, and verified reviews that large language models (LLMs) can extract reliably as “evidence.” The more credible details you provide, the likelier your product becomes the “go-to” example in an AI answer.
• Connect the dots. Tie each product into related themes such as bundles, lifestyle content, or curated “gift stories.” When your catalog feels cohesive, the AI doesn’t just see isolated listings; it sees a brand that fits into a lifestyle narrative.

In short, don’t optimize for a page click; optimize for being cited by the AI in its answer.

2. Inventory Depth is the New Trust Signal

Generative systems now look for consistency and variety across products as cues that a brand is organized, trustworthy, and ready to serve real shopper intent.

Target’s Bullseye Gift Finder shows this shift in action. When shoppers search for “party supplies,” the result extends beyond candles and balloons. The AI suggests snacks, outdoor gear, and other relevant products, proving the system understands the occasion, not just the keywords.

From a brand’s perspective, this means:

• Show your range. Provide color, size, and bundle variants with visibility.
• Enable AI-facing “complement rules.” Specify which SKUs naturally go together (e.g., “if viewing speaker, also surface matching Bluetooth stand or carry case”).
• Surface scarcity logic transparently. If a variant is out of stock, flag it, but also show the alternatives. Silent “unavailability” can reduce model trust.

3. Don’t Treat AI Commerce as 'Search + Checkout'

The old path: search, click, cart, checkout, is breaking apart. With tools like ChatGPT’s Instant Checkout, shoppers can now browse and buy inside the conversation. The “zero-click” consumer isn’t coming; they’re already here.

To adapt:

• Support agent-native transactions. Prepare catalogs for instant purchase protocols as conversational platforms open their APIs.
• Shorten decision friction. Summarize products in a single, scannable, “pitch-once” summary: hero image + one-liner + proof point + call to action.
• Keep context close. Reviews, delivery estimates, and warranty details should be AI readable, not hidden in backend pages or deep modals on your site.

The Holiday Season That Will Test AI Readiness

Adobe expects AI-driven traffic to retail sites to surge nearly 520 percent, and ChatGPT’s new commerce features are now live for millions of shoppers. For the first time, retailers aren’t just competing for customers, they’re competing for algorithms. Those that earn the AI’s trust this holiday will own next year’s discovery.

For brands, the stakes are clear:

• If you treat AI discovery like “just another ad channel,” you risk invisibility.
• If your catalog isn’t structured for model recall, the AI may substitute a competitor’s.
• And if you don’t support agent-native commerce, you’ll likely lose the click to an AI-first player.

The holidays will come and go, but the product data you feed the machines this season will echo long after. Train the models right and it’s your brand the AI will remember and recommend first.

Marcel Hollerbach is the co-founder and chief innovation officer at Productsup, a leader in product data feed management.