Williams‑Sonoma elevates home cooking with AI‑powered personalization

Williams ‑Sonoma: AI‑Powered Personalization for Culinary Enthusiasts

Challenge

• Williams ‑Sonoma offers an extensive catalogue of cookware, bakeware, appliances and décor, making it difficult to surface the most relevant items for each visitor.
• Shoppers expect the same curated, high‑touch assistance online as they receive in store.

Solution
Jewel ML’s no‑code personalization engine was deployed across Williams ‑Sonoma’s digital storefront. Machine‑learning models analyzed browsing signals and purchase behavior to serve dynamic recommendation carousels, search suggestions and complementary product bundles. The system continuously fine‑tuned recommendations for cookware, serveware and gourmet foods to match each customer’s cooking style and home aesthetic.

Impact

• Approximately 7.68% uplift in revenue attributed to improved product discovery and cross‑selling.
• Click‑through rates on recommendation widgets doubled, indicating stronger engagement.
• Conversion rates rose by about 11%, driving more shoppers to complete their purchases.
• Customers reported higher satisfaction and spent more time exploring the curated collections.

Why it mattered
As a premium home and kitchen brand, Williams ‑Sonoma thrives on offering expertly curated collections that inspire culinary creativity. Jewel ML’s personalization helped replicate this experience online, connecting home chefs with the perfect tools and décor for their kitchens.

What’s next
With strong results on the website, Williams ‑Sonoma plans to extend AI-driven personalization into its mobile apps and further refine merchandising strategies with Jewel ML.

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