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b2b commerce
All articles tagged with "b2b commerce".
Commerce operations insights and applications
Unified Commerce Intelligence: Orchestrating Revenue Across Omnichannel B2B Transactions
A £60M foodservice distributor processes orders through four channels: Shopify Plus, EDI feeds, phone, and WhatsApp. Each channel lands in a different system. Web orders sync to the ERP overnight. EDI orders arrive every 15 minutes but don't update inventory visibility until the next batch run. Staff key phone orders directly into the ERP. Staff transcribe WhatsApp orders into a spreadsheet, then manually enter them. The operations director calculated the cost. Pricing inconsistencies between channels cost £180K annually in margin leakage. A customer quoted £4.20/kg for chicken thighs on the phone receives a different price (£4.45/kg) when they order the same product via the website three days later. They call to query it. The phone team has no visibility of the web order. They create a second order. By the time staff spot the duplicate, the customer has been invoiced twice and the stock has been picked. Resolution takes 90 minutes and involves three people.
Platform capabilities and technical insights
Event-Driven Architecture: Real-Time Commerce Operations at Scale
A West Midlands foodservice distributor runs seven systems: SAP for ERP, Shopify Plus for commerce, Manhattan for warehousing, Salesforce for CRM, Xero for accounting, Akeneo for product data, and a legacy routing tool built in-house. None of them talk to each other in real time. Pricing updates take three days. Inventory visibility lags 24 hours behind actual stock. The operations director spends Monday mornings reconciling conflicts created by systems working from different versions of the truth. This is the middleware bottleneck. Mid-market B2B distributors have invested in best-of-breed systems but lack the integration layer to connect them. The B2B middleware market reached £14.1 billion in 2025, growing at 12.23% annually (MarketsandMarkets, 2024). That growth reflects a painful reality: buying good systems is easy, making them work together is not. Event-driven architecture promises to solve this. Order placed, inventory updated, fulfilment triggered, customer notified—all in real time. But most mid-market stacks lack the middleware to orchestrate that sequence. Without it, teams fall back to manual processes and the operational friction compounds.
Operational workflow improvement
Task-Specific AI Agents in B2B Commerce: From Procurement to Order Management
A procurement exception flags in your ERP at 4:47pm on Friday. Supplier lead time extends from 14 to 21 days. Inventory on your fastest-moving line drops below reorder point. The alert sits unread until Monday morning. By then, the supplier's order window has closed for the week. You've lost seven days, and your customer delivery commitment is now at risk.
Platform capabilities and technical insights
Composable Commerce Architecture: Building Modular Systems That Evolve With Your Business
A Midlands foodservice distributor spent £240,000 recovering from a pricing error in 2024. Their monolithic commerce platform took three days to update prices across 12,000 SKUs. Commodity costs moved faster than their approval cycle. By the time new prices went live, margins had eroded. The problem wasn't the platform. It was the architecture. Pricing, inventory, and order management sat in one system. Upgrading the pricing engine meant ripping out everything else. The platform vendor quoted 18 months and £180,000 for a custom pricing module. The distributor couldn't wait that long. This is the composable commerce question: when one component fails, can you swap it without dismantling the entire system?
Operational workflow improvement
Agentic Sales Agents: When AI Handles Customer Negotiations in Distributed Channels
Most B2B distributors take 2-5 days to generate a complex quote. Sales teams spend 30-40% of their time on quote administration rather than relationship-building. Autonomous negotiation systems can issue quotes in under two minutes—but only if decision thresholds are explicit and governance is built in from the start. Without clear boundaries, AI agents commit companies to commercial terms they didn't intend.
Platform capabilities and technical insights
Agentic AI Advisory: When Your Operations Need Real-Time Workflow Support, Not Quarterly Reviews
A foodservice distributor takes three days to change a price. By the time the spreadsheet is approved and uploaded, the margin opportunity has passed. A seven-depot building merchant routes deliveries manually each morning, missing optimisation windows that close by 9am. A fashion retailer delays markdown decisions until stock levels force action, tying up £180,000 in slow-moving inventory for an extra six weeks. Workflow delay costs more than imperfect decisions made fast.
Operational workflow improvement
Agentic Pricing Intelligence: When Custom Models Set Prices Autonomously
Most B2B distributors take three days to change a price. By the time it's live, the margin opportunity has passed. Autonomous pricing agents compress this cycle from days to minutes - but only if governance is built in from the start. Without it, you hand control to a system that optimises for volume while destroying margin.
Platform capabilities and technical insights
Build vs Buy vs Partner: The AI Vendor Selection Framework for Mid-Market Distributors
Mid-market distributors face three paths when deploying AI: pre-built vendor models, custom development, or third-party APIs. Most lack a clear framework to evaluate them. The wrong choice delays implementation by 6-12 months and wastes £50,000-£200,000. This decision matrix maps implementation timeline, cost structure, and risk profile for each approach. Pre-built models deploy in 8-12 weeks at lower cost but limited customisation. Custom development takes 16-24 weeks with full control and competitive advantage. Third-party APIs offer middle ground at moderate cost and configuration flexibility. The right choice depends on data maturity, technical capacity, and competitive urgency. A distributor with clean data and a 6-month runway can pursue custom development. A distributor with fragmented systems and a 10-week deadline cannot. Four questions determine the viable path: data quality, timeline urgency, competitive differentiation, and internal technical capacity.
Operational workflow improvement
The £8 Billion GenAI Governance Gap: What B2B Commerce Leaders Must Know
Forrester predicts B2B companies will lose over £6.4 billion in 2026 due to ungoverned AI use. Mid-market distributors score 4.8/10 on AI governance readiness, creating vulnerabilities in pricing, inventory, and customer communications that cascade through supply chains and destroy relationships worth millions.
WithPraxis
Client Success Stories: Real ROI from Applied AI
Real ROI from applied AI across five distribution verticals. Anonymous case studies showing measurable outcomes: 6% margin improvements, 18% fulfilment cost reductions, and 90% error elimination. Implementation timelines, effort required, and lessons learned from actual client engagements.
Platform capabilities and technical insights
Customer Lifetime Value Intelligence: Predicting Profit Per Relationship
Most B2B distributors calculate customer lifetime value by adding up historical purchases, missing predictive factors that signal churn risk and growth opportunities. True CLV intelligence uses behavioural patterns, payment data, and market context to guide resource allocation decisions before customer value changes become obvious in purchase history.
Operational workflow improvement
Why Most Commerce Businesses Don't Need AI Strategy — They Need Workflow Clarity
Most B2B commerce businesses don't need a sweeping AI strategy. They need clarity on the handful of critical operational workflows that drain time and margin, one decision at a time.
Commerce operations insights and applications
Quote-to-Cash Intelligence: Why Manual Quotation Processes Kill B2B Deals
Three days to generate a B2B quote while competitors respond in hours. Manual quotation processes create systematic disadvantage - delayed responses, pricing errors, approval bottlenecks. Intelligent automation transforms quote generation from operational burden to competitive advantage.