Forbes

Ulta chief marketer on brand-building and omnichannel strategy

Ulta Beauty’s chief marketer Kelly Mahoney outlines how the retailer combines brand-building, first‑party data and omnichannel tactics to drive growth. Ulta reported Q1 net sales up 11.1% to $3.2 billion and attributes part of the performance to marketing initiatives. Mahoney emphasizes leveraging the Ulta Beauty Rewards loyalty program (nearly 47 million members), a proprietary 'Beauty Graph' for personalized insights, and UB Media to deliver targeted retail-media campaigns. The company is using TikTok Shop for guest acquisition, building year‑long creator partnerships through the Ulta Beauty Collective, staging experiential in‑store events and partnering with IP holders (DC Studios/Warner Bros. Pictures on a 'Supergirl' collaboration). Mahoney frames cultural partnerships, retail media and creator-driven discovery as complementary levers in an omnichannel marketing playbook.

Kroger to Acquire Giant Eagle for Billions

Kroger announced a billion‑dollar acquisition of regional supermarket and pharmacy operator Giant Eagle, a move described as an attempt to expand the retailer's footprint in the eastern United States after its planned mega‑merger with Albertsons failed. The article cites Forbes and was published by Lebensmittelzeitung on 2026-07-02. The deal is presented as a strategic follow‑up to Kroger's earlier, unsuccessful Albertsons transaction and aims to strengthen Kroger’s presence in key eastern U.S. markets.

AI in Design: Depth Over Speed

Designer Dan Maccarone describes a year-long experiment rebuilding his studio’s design process around generative AI. Across four real products and client projects, the studio did not become faster—the five-day sprint cadence remained—but produced fuller, more integrated prototypes that served as a single source of truth. The new workflow uses an upfront experience brief, keeps skeptical team members close as validators, and has the AI generate documentation and component libraries from approved prototypes so docs stay in sync. The author warns of two liabilities: technical debt from AI-generated code and a loss of recorded rationale (the “why”) if decision reasoning isn’t captured before AI produces confident-looking outputs. The piece argues that AI’s real value is enabling deeper work and better judgment, not merely speed.