3 actionable ideas in 3 minutes, only for Retail Leaders
Welcome to DX Brief - Retail, where every week we review industry podcasts and reports to share what’s insightful and what you can do about it.
1. Shopping is increasingly mobile and AI-assisted
Morgan Stanley surveyed ~680 Gen Z interns and found that:
a) large brands are losing market share, so retailers need to on-board AND churn brands faster; and
b) 90% of them use multiple devices and rely on AI + content to inform purchases. Source: Morgan Stanley’s Thoughts on the Market podcast (Aug 26)
Retailers will have to onboard more niche brands faster AND churn them faster. That stresses PIM, DAM, PDP content, returns flows, and retail media targeting. Treat “brand onboarding speed” as a KPI. Build self-serve onboarding and content QA so category managers do not become the bottleneck.
Shoppers research and decide inside AI chats and on short-form video. Make product data retrievable by LLMs (clean schemas, plain-English attributes, store-level inventory). Upgrade stores with video-content capture areas so associates and creators can post compliant micro-demos that feed PDPs and social.
2. The small-package tariff loophole is closing
For years, many low-value imports (<$800) entered the US without duties under a rule called de minimis. In 2025 the US moved to curb or end that treatment for parcels from China/Hong Kong. Fast-fashion players like SHEIN and Temu have already flagged price increases as a result. Expect pricier and slower cross-border shipments and tighter customs checks.
Source: Shane Hewitt and The Nightshift podcast “Fast fashion on trial” (Aug 27) 1
Make your cart and OMS tariff-aware: plug in landed-cost calculators, clean HS codes, and show duty/VAT at checkout so customers are not surprised. Run 3 tariff scenarios in pricing and promo engines. Track margin hit and cancel/return rates for cross-border SKUs. Upgrade with duty/tax modules and APIs that attach to OMS/checkout (HS-code enrichment, landed-cost, audit logs).
Rethink routing and SLAs: test nearshore/ domestic alternatives for key items; set realistic ETAs when customs risk is high. Measure WISMO tickets1 and NPS pre/post change. Upgrade with a “trade-risk monitor” that flags products, lanes, and suppliers most exposed to new duties so merchandisers can swap or reprice quickly.
3. Speed is the new conversion lever
Home Depot used machine learning to choose store vs. DC fulfillment and added dedicated associates with a prioritization app. Q2 saw record delivery speeds and a 4.9% sales gain; faster delivery correlates with higher spend and cross-channel engagement.
Source: Retail Dive article (Aug 25)
If your WISMO volume is high or split-ship costs are rising, consider this playbook: ML sourcing rules inside the OMS, dedicated pick capacity, and an associate app that sequences tasks against SLAs. Measure uplift in order frequency and AOV for customers who experience sub-24h delivery.