US Online Black Friday Sales Hit $11.8B As AI Traffic Jumps 805% - Here's What Sales Teams Should Do Now
Black Friday set a new online record in the US: US$11.8 billion in spending, up 9.1% year over year, according to Adobe Analytics. That growth landed despite weaker consumer confidence, rising unemployment, and tighter budgets.
Online outpaced stores by a wide margin. Mastercard SpendingPulse reported online sales up 10.4%, while in-store rose 1.7%. A key driver: AI. Adobe noted AI-driven traffic to major retail platforms rose 805%, boosted by tools like Walmart's Sparky and Amazon's Rufus.
"Consumers are using new tools to get to what they need faster," said Suzy Davidkhanian, an eMarketer analyst. "Gift giving can be stressful, and LLMs make the discovery process feel quicker and more guided."
What sold-and what shifted
Demand clustered around LEGO sets, Pokémon cards, gaming consoles (Nintendo Switch, PlayStation 5), and popular hardware from Apple AirPods to KitchenAid mixers. Salesforce estimated AI agents influenced US$14.2 billion in global Black Friday sales, with about US$3 billion in the US. Including groceries and other staples, Salesforce said Americans spent US$18 billion online, with luxury apparel and accessories showing standout strength.
Baskets got smaller even as prices climbed. Salesforce reported orders down 1% and units per checkout down 2%, while average selling price increased 7% year over year. Caila Schwartz at Salesforce pointed to tariffs and a healthier high-income segment as the main reasons for higher prices. Discounts looked similar to 2024, but higher product costs limited deeper promotions-reducing the real value of Black Friday deals, as noted by Michael Ashley Schulman of Running Point.
Physical retail was quieter. Some shoppers pulled back given persistent inflation, trade uncertainty, and a softening labor market.
Cyber Monday outlook
Adobe expects Cyber Monday to surpass Black Friday with US$14.2 billion in sales-the biggest online day of the year if it lands. Electronics could see discounts up to 30%, with strong markdowns in apparel and computers.
Why this matters for Sales leaders
- Meet the AI buyer. Treat LLMs and retail chat as a new top-of-funnel. Clean up product feeds: titles, attributes, availability, pricing, reviews, and FAQs. If an assistant asks a question, your catalog should answer it instantly.
- Shorten discovery. Build guided gift finders and on-site chat flows that mirror how customers query Rufus/Sparky. Use clear prompts on product and category pages to help shoppers self-serve faster.
- Own value, not just price. With discounts flat and ASPs higher, package bundles, set free-shipping thresholds, and highlight total cart savings and delivery speed. Protect margin while giving a concrete reason to buy now.
- Merchandise to demand spikes. Lean into consoles, gaming accessories, high-velocity toys, and hero electronics. Keep premium lines in stock-high-income buyers are still active, particularly in luxury.
- Rethink attribution. Track AI-sourced sessions and chat-assisted conversions. Break these out from search and social to avoid double counting, then reallocate budget to the highest-assist channels.
- Prep for Monday surges. Lock pricing rules, inventory buffers, and ad budgets for late-day peaks. Have service teams staffed for chat and order support during evening hours.
- Upskill the team. Give reps practical prompt sheets for product discovery, comparisons, and cross-sell suggestions. Train them to translate AI-driven queries into clear answers and fast recommendations.
Fast actions you can ship this week
- Add missing attributes to top 200 SKUs (materials, compatibility, who-it's-for) so AI assistants surface your products more often.
- Publish a 3-5 step gift guide quiz and pin it sitewide. Route results to in-stock bundles.
- Set a cart threshold incentive that beats your average order value by 10-15%.
- Spin up a "last-minute delivery" message with realistic cutoff times to reduce hesitation.
- Tag and track "chat-assisted" orders and review daily for insight-led tweaks.
Useful sources
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