Macy’s AI Chatbot Quadruples Customer Spending

Why It Matters

The dramatic spend uplift proves AI can directly expand basket size, positioning conversational commerce as a key growth engine for legacy retailers.

Key Takeaways

• Ask Macy’s users spend 4.75× more than non‑users.
• Gemini‑powered chatbot offers outfit completion and virtual try‑on.
• AI rollout aligns with Macy’s return to comparable sales growth.
• 35+ AI use cases span supply chain to marketing.
• Chatbot learns from climate data, tailoring brand recommendations.

Pulse Analysis

Retailers have long chased the promise of AI‑driven personalization, but few have quantified its impact on the bottom line. Macy’s Ask Macy’s chatbot, built on Google’s Gemini large‑language model, moves beyond simple product search by offering real‑time outfit curation and virtual try‑on. By ingesting inputs such as budget, occasion, color and regional climate, the assistant crafts recommendations that feel like a knowledgeable sales associate, while continuously refining its responses through machine‑learning feedback loops. This level of contextual awareness is a step up from static recommendation engines that dominate many e‑commerce sites.

The financial payoff is striking. Internal testing revealed that users of the chatbot generate spend that is 4.75 times higher than non‑users, a metric that Bloomberg highlighted as a near‑quadrupling of average order value. This uplift contributed to Macy’s return to comparable‑sales growth in fiscal 2025, a milestone after years of flat performance. The company’s CFO, Tom Edwards, credited a suite of more than 35 AI initiatives—spanning supply‑chain optimization, merchandising analytics, marketing automation and call‑center support—for the broader turnaround, underscoring how AI is becoming a systemic advantage rather than a siloed experiment.

Macy’s success sends a clear signal to the broader retail sector: conversational AI can be a revenue driver, not just a cost‑saving tool. Competitors will likely accelerate their own LLM‑based assistants, focusing on seamless integration across mobile apps, in‑store kiosks and voice platforms. The challenge will be balancing personalization with privacy, ensuring data‑driven insights respect consumer consent while delivering the hyper‑relevant experiences shoppers now expect. For investors and executives, the takeaway is simple—AI that can meaningfully influence purchase decisions is fast becoming a core competitive moat in the digital commerce landscape.