Sidekick is used nearly daily (21 of 30 days) to enable near-daily analytics, cross-brand insights, and rapid merchandising workflows, contributing to an ~80% reduction in weekly reporting time.

Shopify Sidekick is deployed as an AI team member to analyze performance, audit collections, optimize site operations, and guide strategic decisions across Maggy London’s six brands.

President Sara Bako leads Maggy London’s four-person ecommerce team, using Sidekick to analyze performance, audit operations, and drive cross-brand strategy.

Sidekick supported wholesale recut validation by providing data-driven confirmation of styles and sizes before reintroducing prior-year items.

Adoption of Sidekick is deep and ongoing, delivering substantial time savings, faster decisions, cost efficiency, and dramatically quicker reporting.

Weekly reporting time was slashed by roughly 80%, shrinking from several hours to about 20–30 minutes, and yielding at least a full additional day of work freed each week.

Future plans include AI-powered styling and a modernized storefront with personalized shopping experiences and event- or body type-specific dress recommendations.

Analysis of new versus returning customers using Sidekick quantifies acquisition and retention drivers to inform marketing and product decisions.

Key use cases cover a comprehensive collection audit, cross-brand customer behavior insights, a Q3 buy roadmap based on historical data, wholesale style validation, and site health improvements like search insights, landing-page optimization, automated merchandising with Shopify Flow, and review-to-conversion analysis.

A Q3 buy roadmap was built by analyzing historical data, suggesting unit quantities, and identifying hero styles for the upcoming season.

Site infrastructure and SEO readiness tasks are being prepared for AI-powered discovery, including URL redirects and LLMs.txt setup.

A 199-collection audit across six brands streamlined underperforming products, improving discovery and cleanup efficiency.