AI is only as good as the data it learns from. If your size-run data lives in Excel, your buyer preferences in emails, and your sell-through data in retailers' systems you cannot access — no AI tool can help.
FIRE captures structured size-level data from every sales interaction. That structured data is what makes practical AI possible for footwear brands.
Companies buy AI tools expecting intelligence. What they get is garbage in, garbage out — because the data is not structured, not connected, and not deep enough.
AI needs structured, machine-readable data. Excel size matrices with merged cells and inconsistent formatting are not structured. You need a platform that creates structured data as a byproduct of selling.
Size data in the ERP. Buyer profiles in the CRM. But browsing data, size selection patterns, and buyer intent — captured nowhere. FIRE connects to your ERP and CRM while adding the structured sales intelligence layer they were never designed to provide.
Size patterns need at least two full seasons of data. Start capturing now, and AI capabilities grow with every month. Wait, and you delay the timeline by exactly as long as you wait.
Real intelligence that becomes available once your data is structured and has sufficient depth.
Data-driven size curves per retailer type and region. A Nordic outdoor store needs a fundamentally different distribution than a Southern European boutique.
Predict demand at the style-colour-size level using browsing signals, sell-in velocity, and historical patterns. Reduce overproduction and prevent stockouts.
Detect which sizes at which retailers need restocking based on sell-through velocity. Proactive, automated, size-level. Fewer stockouts, less overstock.
Use early sell-in signals and portal browsing data to predict which styles will perform before production is committed. Adjust quantities early.
Identify retailers whose ordering or browsing activity is declining. Alert your team before the account is lost — not six weeks after the expected order fails to arrive.
Recommend optimal style-size assortments per retailer type based on what similar stores sell best. Increase sell-through by matching the right products to the right accounts.
Each product captures different intelligence. Together they create the data foundation AI needs.
Trade fair meetings produce the earliest demand signals. Which styles catch a buyer's eye? Which sizes do they select?
Field visits capture relationship intelligence: visit frequency, products discussed, buyer feedback.
The highest-volume data source: every search, click, size selection, and cart abandonment.
Every FIRE touchpoint generates structured data. That data feeds dashboards immediately. After enough history, AI models activate — turning operational data into foresight.
Key insight: You do not need to wait for AI. Structured data has immediate value in dashboards and reports. AI is the bonus that arrives once your data compounds.
The footwear brands that lead with AI are the ones building their data foundation now. FIRE captures the data. Time compounds it. AI transforms it into intelligence.
Start Building Your AI FoundationTell us about your brand, your current B2B setup, and what you are looking to improve. We will show you exactly how FIRE works for your specific situation.
No generic demos. No slide decks. A real walkthrough with your products and your industry configuration.
The path to AI in footwear B2B is about building the right data foundation through every sales interaction.
Book a personalised demo — integrated with your ERP in 20–40 days.