AI-assisted shopping is the headline of this holiday season
Retail and tech giants rolled out smarter AI shopping tools just in time for peak buying. The pitch is simple: faster discovery, clearer choices, and fewer steps to checkout - all inside assistants people already use. The upside for retailers is obvious too: more qualified intent and higher conversion.
Early numbers point up. Salesforce estimates AI will influence $73 billion - roughly 22% - of global sales from the Tuesday before Thanksgiving through Cyber Monday, up from $60 billion last year. Still, adoption is uneven. Many sites lack useful AI features and some shoppers aren't ready yet, so the full impact remains limited this season.
1) Search and discovery just got practical
Shoppers can ask for what they want in plain English and get answers that feel like a trusted friend who knows the catalog. OpenAI added shopping research inside ChatGPT that builds personalized buyer's guides from product pages, reviews, prices, and past chats. It shines for complex buys like electronics or detail-heavy items like beauty and sporting goods.
Amazon's Rufus now remembers context - like kids' ages or hobbies - and uses browsing history and reviews to refine picks. Google's AI Mode interprets detailed prompts (for example, a casual sweater that works with jeans or a skirt in New York in January) and returns side-by-side comparisons pulled from its product listings. Walmart's Sparky suggests gifts by occasion and distills reviews, while Target's seasonal gift finder responds to prompts such as age and hobbies.
2) Price tracking moves from niche to default
Third-party trackers like CamelCamelCamel and PayPal's Honey have been around for years. Now the platforms are building it in. Amazon launched 90-day price history on most listings and lets shoppers set alerts tied to their budget. Google upgraded its tracker to factor in details like size and color, and Microsoft's Copilot added a price tracker as well.
Expect more pressure on pricing. As more shoppers discover alerts, price transparency will widen and deals will compress. That means fewer mistakes and tighter margins - but better trust if your pricing is disciplined.
3) Assistants that actually buy things
The next push is taking customers from browse to buy inside the same experience. OpenAI's instant checkout lets people buy items suggested by ChatGPT without leaving the app, including Etsy shops and brands on Shopify like Glossier, Skims, and Spanx. A separate OpenAI deal with Walmart enables near-full catalog shopping (excluding fresh food) with instant checkout, though it currently supports one item at a time.
Target's integration lets people build multi-item carts in ChatGPT, including fresh food, then finish payment in the Target app. On the agent side, Amazon's Rufus can now auto-purchase when an alert hits a target price, giving shoppers a brief window to cancel. If Amazon doesn't carry a product, "Shop Direct" routes the shopper to another retailer.
Google's price tracker includes a "buy for me" option that completes purchases with Google Pay for select merchants like Wayfair, Chewy, Quince, and some Shopify stores. Google also added automated AI calls that phone local stores to check stock or gather info. The caller identifies itself as AI, and stores can opt out. It's rolling out first for toys, health and beauty, and electronics.
What this means for sales and marketing teams
- Be findable inside assistants: keep product feeds clean, complete, and up-to-date. Include variants (size, color), specs, and rich attributes. Consistency across Amazon, Google Merchant Center, and Shopify matters.
- Write for natural-language queries: build pages and FAQs that answer questions the way people ask them. Comparison charts and "best for X" sections help assistants return your products.
- Lean into reviews: assistants summarize sentiment. Push for detailed, recent reviews and respond to issues so summaries work in your favor.
- Prepare for price transparency: align promo calendars with price-drop alerts. Monitor competitors daily and avoid messy pricing patterns that erode trust.
- Reduce checkout friction: enable eligible programs like Google's "buy for me," OpenAI instant checkout, and Amazon auto-buy where appropriate. Keep stock data accurate to prevent cancellations.
- Instrument attribution: tag assistant-driven sessions with UTMs and server-side tracking so you can see what actually converts.
Quick action plan for Q4
- Audit product feeds across Amazon, Google Merchant Center, and Shopify for complete attributes, variant coverage, and review markup.
- Ship comparison sections on top category pages and add buyer's guides that mirror popular queries you see in site search and chat.
- Enable price-drop alerts in your app and email. Segment by budget thresholds and automate reminder flows.
- Test eligibility for Google "buy for me" and confirm promo metadata (coupons, sale prices) is accurate in feeds.
- Map your catalog to Amazon's taxonomy cleanly so Rufus surfaces the right SKUs; verify brand and model identifiers.
- Set rules for auto-buy cancellations and alert windows; update customer comms and support macros.
- Train store teams to handle AI phone inquiries and keep hours/in-stock data current; tag these calls in your CRM.
- Create occasion-based gift guides (age, hobbies, price bands) that assistants can summarize cleanly.
- Stand up a daily price check for top 100 SKUs and log deltas against your margin guardrails.
- Report weekly on AI-influenced sessions, cart adds, and conversion to build next year's budget case.
The takeaway: AI will influence more holiday spending this year, but behavior change is gradual. Teams that make products easier to find, compare, and buy - inside assistants - will win share now and set the pace for 2026.
Further reading
Salesforce Holiday Shopping Insights
Google Shopping updates
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