Cyber-attack threatens M&S’s fashion momentum
Marks & Spencer’s fashion resurgence is facing a major setback due to a recent cyber-attack that has taken its online clothing store offline since Easter. The disruption, expected to last until July, could cost the retailer up to £300 million, with two-thirds of the losses tied to clothing sales. While M&S has successfully repositioned itself as a fashion destination through smart collaborations and trend-led design, the outage threatens both revenue and customer trust.
Analysts warn that the data breach could erode hard-won brand loyalty. This incident comes just as M&S was gaining momentum with fashion-conscious shoppers and expanding digital engagement.
Resistance grows against full-time return-to-office mandates
According to research from King’s College London, less than half of UK workers would comply with a full-time return-to-office mandate. Just 42% support a five-day in-office schedule, down from 54% in 2022. Resistance is strongest among women, parents, and younger workers, with many saying they would quit or seek new jobs if forced back.
Despite employer pushback, average work-from-home days have increased slightly. Researchers warn rigid mandates may harm diversity and lead to a two-tier workforce. Experts urge formalising flexible hybrid models to retain talent, noting that remote workers often show higher productivity and loyalty.
Makip launches 3D avatar upgrade for unisize sizing tool
Makip has unveiled a major upgrade to its Unisize sizing engine, now featuring a 3D avatar view to help online shoppers visualise clothing fit more accurately. Customers can see their personalised avatars from four angles and even preview how trousers fall with different footwear.
This innovation aims to reduce the high rate of apparel returns, particularly from “bracketing” by Gen Z shoppers. CEO Shingo Tsukamoto highlights a 20% drop in returns among Japanese clients. As Makip expands globally, it continues to enhance personalisation with features like FaceChange and item comparison for returning users.