AI for Retail Leaders
From fragmented data and manual forecasting to AI-powered retail intelligence
We help retail leaders unify data across channels, optimise inventory, and personalise at scale, while navigating the tension between D2C growth and wholesale partner relationships.
Trusted by leading organisations
30%
Better demand forecasting accuracy
20%
Reduction in overstock and markdowns
2x
Faster product asset production across channels
We understand the retail reality you're navigating
As a retail leader, you're caught between Amazon-scale personalisation expectations and the reality of fragmented systems, manual forecasting, and 900+ wholesale partners who all report differently. AI promises to help, but most vendors don't understand the complexity of omnichannel retail.
Fragmented data and manual reporting across channels
You're drowning in data from webshops, marketplaces, and wholesale, but combining and interpreting it costs too much time. Inventory allocation is still done manually in spreadsheets, with forecasts split by gut feeling rather than algorithms.
Omnichannel integration stuck between D2C and wholesale
Your business was built for brick-and-mortar with e-commerce bolted on. There's no integration layer between your marketplace and D2C platforms, and creating a unified customer experience across 70%+ wholesale and growing D2C feels impossible.
Inventory management still based on intuition, not data
Without predictive algorithms, purchasing decisions rely on outdated data and gut feel. You can't determine optimal safety stock by SKU, and your retail partners are even worse at forecasting, making supply chain planning a guessing game.
The masterclass with WAIMAKERS was very insightful. Their ability to translate AI principles into real retail use cases for SSP UK was unique.
Learn. Lead. Make.
How we help Retail leaders turn AI into omnichannel growth and operational efficiency
Retail team AI enablement
Workshops that train your buying, merchandising, and e-commerce teams to use AI tools effectively. From interpreting demand signals to crafting product descriptions, we build hands-on skills with real retail scenarios from your own business.
Team-wide AI readinessData literacy for retail decisions
Help your teams understand the data landscape across webshop, marketplace, wholesale, and POS systems. Our education programmes show what data is available, how AI interprets it, and how to ask the right questions to drive better buying and pricing decisions.
Data-informed decision makingRetail AI strategy and use case prioritisation
You already know the solutions: demand planning, pricing optimisation, personalisation. The real question is why haven't they worked yet? Traditional AI required months of data engineering and six-figure budgets. Generative AI changes the equation. We help you identify where it cuts through complexity, build the business case, and align your leadership on a roadmap that delivers results in weeks, not quarters.
Prioritised retail AI roadmapOmnichannel data and pricing strategy
Traditional pricing tools need clean, structured data pipelines before they can do anything. Generative AI can work with messy, fragmented data from day one, interpreting unstructured reports, normalising inconsistent formats, and surfacing pricing insights across channels without waiting for a perfect data layer. We help you define the strategy, set guardrails, and build the governance that makes it scale.
Cross-channel pricing frameworkAI product imagery and information
Stop using the same product shot on every touchpoint for every consumer. Generative AI enables you to create channel-specific product visuals, adapt imagery for different markets, and generate tailored product information at a fraction of the time and cost.
2x faster asset productionPersonalisation at scale
Traditional personalisation required expensive recommendation engines and dedicated data science teams. Generative AI lets you create segment-specific product experiences, from tailored descriptions to localised assortment recommendations, without building custom models from scratch.
Segment-specific experiencesImpact on metrics that matter to you
Real results from retail brands that implemented AI strategically
Customer service automation
55%
Of support tickets handled end-to-end by AI - a gift card fintech now processes 80-90 tickets/day without human touch
D2C conversion uplift
+120%
A US e-commerce brand grew D2C conversion from 0.9% to 2.0%, generating $65K/month from AI-driven email flows with 60%+ open rates
Banner production per set
~5 min
A premium consumer brand now resizes campaign banners to all social media formats in approximately 5 minutes - saving roughly 3 hours per asset cycle
CS response time reduction
75-80%
Time saved on common customer service requests at a premium fashion retailer - with team members using AI assistants daily for routine enquiries
“WAIMAKERS helped our category and supply chain teams see how generative AI could transform the way we work with product data, forecasting, and vendor reporting. It went from abstract to actionable in a single session.”
Category & Supply Chain Leadership
Mid-market retail brand
“The masterclass with WAIMAKERS was very insightful. Their ability to translate AI principles into real retail use cases for SSP UK was unique.”
Rolf Geling
CFO UK, Ireland & Netherlands, SSP Group Plc
“Greg and WAIMAKERS did a brilliant job both inspiring our leadership team about the transformative potential of AI and showing us how to move forward with practical, high-impact steps. The biggest shift was realising that this isn't just about tools or software, it's about people, behaviours, and how we work.”
Chirag Patel
CEO, Pentland Brands
“The WAIMAKERS team translated Generative AI into immediate business value for NEOM. The session was both creatively inspiring and operationally relevant - both for significant day-to-day productivity gains but also for product development, compliance, and brand storytelling.”
Isabel Malbois
CEO, NEOM
“The Generative AI Masterclass helped the Copus teams to move beyond curiosity and into execution. We explored concrete use cases around employer branding, multichannel outreach, and internal content operations.”
Brecht De Mey
CEO, Copus
AI use cases for retail leaders
Practical applications we've implemented for retail brands and their channel operations
AI-Powered Demand Forecasting & Inventory Optimisation
You know demand forecasting is the answer. But traditional ML models need months of data science work, clean pipelines, and dedicated teams to maintain. Generative AI lets you start with the messy data you already have, from wholesale spreadsheets to marketplace exports, and get actionable forecasts in weeks instead of quarters. That is what makes it different.
- ✓SKU-level demand prediction from wholesale exports and marketplace data - no clean pipeline required to start
- ✓Automated safety stock calculations per product and channel, replacing error-prone spreadsheet models
- ✓Real-time inventory allocation across D2C, marketplace, and wholesale reducing overstock risk
- ✓Early warning system for stockouts flagged before they hit - a 550-store retailer targets €10M in savings by 2028
- ✓Integration with existing ERP and supply chain systems in weeks, not quarters
Questions we hear from retail leaders
Addressing the real concerns before you have to ask
"Our data is too fragmented to even start with AI."
We know. 15 companies, 15 Excel formats. That's exactly why we start with data normalisation and a unified data layer as step one. It's not glamorous, but it's the foundation that makes everything else possible. We've done it for brands with 900+ wholesale partners.
"Our legacy IT systems block AI adoption."
We understand your tech stack was built for traditional brick-and-mortar with e-commerce added on. We deploy AI on top of your existing infrastructure, whether that's SAP, Shopify, or legacy ERP, without requiring a full re-platform. Start small, prove value, then scale.
"Personalisation requires more data than we have."
You don't need Amazon-level data to start. Even a relatively small CRM database combined with POS data and behavioural signals gives you enough to move from zero personalisation to meaningful segmentation. The key is starting with what you have, not waiting for perfect data.
"ROI is unclear on already-thin retail margins."
That's exactly why AI matters most in retail. Reducing overstock by 20% and improving forecast accuracy directly hits your bottom line. We model expected impact before deployment and start with the use cases that have the clearest margin impact: inventory optimisation and pricing.
Resources for Retail leaders
Explore our knowledge base on AI for retail and consumer brands
AI strategy guides and industry research
In-depth reports on AI in retail - from supply chain optimisation to customer experience and omnichannel personalisation.
Browse whitepapers→AI je nieuwe collega?
Our Dutch-language podcast exploring how AI changes the way organisations work - featuring retail leaders sharing practical AI wins.
Listen now→Discuss AI for your retail business
A 30-minute call to explore how AI can improve your supply chain, customer experience, and operational efficiency.
Book a call→Let's discuss AI for your retail business
Book a 30-minute call with a consultant who understands retail operations and omnichannel complexity. No pitch, just practical advice.