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Retail Sector Confronts Headwinds at Retail Technology Show Preview
The Retail Technology Show (RTS) preview highlighted retail's challenges amid rising costs, declining footfall, new legislation, and shifting markets, with executives from fashion, beauty, sport, and hospitality sharing strategies during a press day chaired by former digital directors from major brands. Meriel Neighbour, global transformation director at a leading fashion retailer, detailed its restructuring: streamlining stores, updating landlord agreements, securing £40 million in funding from new investors, and leadership transitions including a new CEO in 2025. This sets the stage for a multi-year technology programme focused on customer relevance across occasions like workwear, evenings out, family events, and more.[1]
RTS 2024 drew over 12,500 attendees—a 28% year-on-year increase—with 400+ tech exhibitors and sessions on ecommerce, AI, data, sustainability, operations, and payments; the 2025 edition shifts to ExCel London on 22-23 April, promising expanded scale, while 2026 plans feature 125+ speakers and 15,000+ professionals. Neighbour outlined priorities: unified commerce connecting app, web, social, stores, and marketplaces for seamless journeys—like starting online purchases en route to in-store pickup or desk delivery—supported by agile product cycles for continuous freshness without ultra-fast fashion extremes.[2][3][4]
Unified Journeys Reshape Product Feeds and Catalog Standards
Unified commerce demands integrated product data flows, directly impacting product feeds by requiring real-time synchronization across channels to prevent discrepancies in availability, pricing, or descriptions. For retailers closing stores yet upgrading survivors, this means feeds must reflect hybrid inventory—online stock visible in physical spaces via RFID for instant changing-room fulfillment, reducing friction and returns. Search results from RTS confirm RFID and self-checkout as core implementations, automating stock checks and enabling dynamic assortment updates without manual intervention.[1]
Catalog standards evolve under this pressure: rigid seasonal cycles yield to continuous models, enforcing standards like structured attributes for occasions (e.g., event-ready sizing across genders and ages). This necessitates robust data hygiene—consistent SKUs, variant mappings, and metadata—to fuel marketplaces and social commerce, where fragmented feeds lead to lost sales. Neighbour's vision aligns with RTS panels emphasizing AI for prediction, suggesting feeds must incorporate behavioral signals for proactive relevance.[2]
Modern Stores Demand Enhanced Card Quality and Speed
Physical stores persist as experiential hubs, particularly for younger demographics craving personalization beyond transactions. Quality and completeness of product cards become critical: RFID upgrades mean in-store scans pull rich digital cards with 360° views, size guides, and occasion tags, mirroring online depth to bridge channels. Incomplete cards—lacking high-res images or fit data—amplify returns, a pain point Neighbour targets via virtual try-on, where precise cataloging cuts mismatches by enabling AR overlays.
Speed of assortment rollout accelerates with agile models; no rigid A/W or S/S drops mean weekly refreshes, powered by no-code platforms for rapid feed ingestion and AI for trend detection. RTS insights note workforce management tools automating schedules via traffic data, tying store throughput to faster in-store card updates. This compresses time-to-market, keeping mid-range brands fresh against fast-fashion rivals without overstock risks.[1][3]
AI Wave Transforms No-Code Automation in Content Infrastructure
AI emerges as the next frontier, with Neighbour forecasting UK adoption mirroring US trends within six months, focusing on personalisation and virtual try-on to slash returns. For content infrastructure, this integrates no-code tools—low-code assemblers for dynamic cards that auto-generate recommendations or visuals from core feeds—reducing manual curation. RTS attendees highlighted tangible AI uses: predicting preferences for loyalty, supply chain tweaks for sustainability, over vaporware ideas.[2] This aligns with the needs for creating sales-driving product descriptions without spending a fortune as detailed in our blog.
No-code AI lowers barriers, letting non-technical teams iterate feeds with embedded logic for occasion-matching or sustainability filters, while fullness of cards improves via generative fills (e.g., auto-tagging images). Speed gains are evident: continuous cycles demand AI-orchestrated outputs, syncing unified journeys without dev cycles. Experts at RTS stressed measured investment, as tech shifts every 3-5 years per Neighbour, positioning no-code/AI as enablers for relevance without overcommitment. Retail Technology Show site; RetailTechInnovationHub. By automating feed conversions, enriching product content, and ensuring data consistency across all channels, NotPIM empowers e-commerce teams not only to keep pace with the fast-evolving retail landscape, but to optimize the shopping experience itself.