Written by
Aurelija Vycaite
AI & Technology
In the mid-year Conway Brand Radar, we ranked the fastest-growing Dutch consumer brands by digital performance.
One pattern stood out: a subset of brands is moving past the early “AI as marketing toy” stage. Instead of using AI only for campaign copy, product descriptions, or image generation, they’re embedding it into fulfilment, inventory planning, customer service, personalisation, and analytics: areas that directly affect speed, margin, and scalability.
Below are recent examples from Dutch brands showing how this deeper integration looks in practice.
Fulfilment
How AI helps: uses robotics and algorithms to move goods through warehouses efficiently: from order to shipment. AI finds the fastest route for each item, balances workloads, and keeps stock flowing.
Why it matters: speeds up processing, cuts labour costs, and improves delivery reliability without adding staff at the same pace as order growth.
How we've seen brands adopting this:
Otrium opened a new, fully automated warehouse, the O-Mega Robot, using the AutoStore system by Kardex. It uses 95 robots and stores up to 2.3 million items. The system operates up to 5x faster than traditional warehouse models and delivers 400 % more storage efficiency. It runs at near-perfect uptime with high inventory accuracy.
Hunkemöller runs a distribution centre with 150 robots. This move enables Hunkemöller to process fashion orders more quickly, handle high SKU volumes, and expand logistics capacity without proportionate increases in labour.
The warehouse of Otrium (©Otrium)
Inventory planning
How AI helps: connects sales, stock, and seasonal data to predict demand. Instead of relying on historical averages, the system learns from live data, picking up early shifts in customer behaviour.
Why it matters: this prevents lost sales from stock-outs, avoids overstocks, and keeps inventory flowing where it’s most needed. It also frees teams from reactive fire-fighting.
How we've seen brands adopting this:
MR MARVIS uses Slimstock’s AI forecasting platform to predict demand and supply for each product and decide how to allocate stock between stores and the webshop. This, in turn, allows the brand to reduce unnecessary costs or stock-outs.
Rituals partnered with RELEX Solutions to leverage AI and machine learning for smarter demand forecasting, replenishment planning, and production scheduling.
Customer service
How AI helps: modern AI agents can interpret the intent of a query, pull relevant data from order systems, perform actions like processing a refund or updating an address, and summarise the interaction for a human if needed.
Why it matters: removes repetitive work from support teams, speeds up response times, and maintains service quality at scale.
How we've seen brands adopting this:
XXL Nutrition integrated HALO to summarise customer queries, suggest responses, and handle tasks like order lookups and returns. Employees focus on advisory roles while AI handles routine steps.
A Belgian example - Loop Earplugs launched Aura, an AI support agent, achieving 80% CSAT, 357% ROI, and handling the equivalent workload of 25 full-time employees.
Personalisation
How AI helps: analyses browsing patterns, purchase history, and context (time of day, weather, etc.) to adjust product recommendations and messaging.
Why it matters: shoppers find relevant products faster, average order value increases, and long-tail inventory is surfaced.
How we've seen brands adopting this:
Omoda launched an AI stylist built on Google Cloud’s Vertex AI to suggest complete outfits from available inventory. Users convert at over 2.5× the rate of non-users.
Studio Anneloes built an AI-driven personalisation and loyalty platform, to deepen customer relationships across channels. The system builds detailed customer profiles from purchase history, preferences, and style data, then uses AI to trigger “micro-activations” at the right moment: from onboarding sequences to abandoned-cart follow-ups. In the first year, the brand launched nine new AI-driven journeys, generating a 4,900% increase in revenue from personalised campaigns.
Tommy Hilfiger used Quin AI to analyze real-time visitor behavior on its e-commerce site and predict which shoppers were most likely to buy or leave without purchasing. Quin then triggered interventions, like showing targeted product messages, surfacing relevant categories, or timing discount banners. This led to a 51% conversion uplift and a 17× ROI.
Samsonite (in APAC market) incorporates EmotionsAI, which detects emotional triggers. Tailoring site content based on these insights led to a 7.17% uplift in transaction rates and a 108% boost in clicks on product ratings within targeted segments.
Keune uses AI through KAI, a virtual haircare assistant available via WhatsApp. Shoppers scan a QR code in-store, chat with KAI, and can even send photos of their hair or scalp. Using natural language processing and image analysis, KAI recommends the right Keune products based on the person’s hair type, condition, and preferences. It was developed by Croatian company Adria Analytics.
Omoda's AI Stylist (©Omoda)
Analytics
How AI helps: processes sales, marketing, and operational data in real time to uncover patterns and generate actionable recommendations.
Why it matters: enables faster, more accurate decisions, spotting opportunities or issues before they have major impact.
How we've seen brands adopting this:
Ekster integrated Triple Whale’s Moby Agents to automate daily P&L reporting, saving 3.5 hours per week, improving marketing efficiency ratio by 20%, and supporting 50% YoY revenue growth.
Suitsupply uses AI through Centric Market Intelligence, a platform that analyzes consumer trends, competitor assortments, and pricing across its 23+ markets. The AI processes large amounts of market data to highlight opportunities, spot pricing gaps, and suggest optimal product mixes, helping Suitsupply position itself correctly in each country.
Samsonite was getting inflated website metrics because automated bots were generating fake visits and clicks. They adopted HUMAN’s Data Contamination Defense, which uses AI and behavioral analysis to distinguish real human visitors from bots in real time. By filtering out bot traffic, Samsonite restored clean, trustworthy data
What this means for digital leaders
These examples show that AI in Dutch e-commerce is shifting from isolated marketing experiments to operational integration. But none of these results happened overnight. In every case, success relied on:
A clear link between AI use and commercial objectives.
Reliable, well-structured data.
A technical platform able to integrate and scale.
Teams with the skills to run and evolve the solution.
Without these foundations, AI can add complexity instead of removing it.
Disclaimer: Conway & Co is not affiliated with the vendors mentioned. All examples are based on publicly available information. AI adoption should always be evaluated in the context of a company’s business model, technology infrastructure, and growth objectives.
