WM Commercial Advisory — Next-generation commercial systems.

Who we work with

Commercial leaders ready to build trading systems.

Bold teams

Businesses ambitious enough to engineer how they trade, rather than improvise it.

Consumer

Retail, food, FMCG, marketplaces, franchise and digital-led brands.

Complex routes to market

Where the path to the end customer runs through channel partners, marketplaces, franchisees, agencies and owned digital — and the system has to hold them all together.

Where we have worked

Impact delivered in prior commercial roles

>£500m

Of partner-led enterprise deal-making across three continents.

5×

Partner-funded investment uplift against prior models in a multi-country food-delivery platform.

£250m+

Of franchise business-unit P&L responsibility across three emerging markets.

£1bn

Pricing remit across one of the UK’s largest general-merchandise estates.

What we see

Commercial teams under strain.

Four trends are converging on consumer commercial. Each on its own is manageable; together, they explain why the next generation of trading has to be engineered rather than improvised.

1. Channel complexity

More routes to market than the model was built for.

A modern consumer business now trades through more discrete routes than its commercial model was built for — owned digital, marketplaces, franchise, agency, retail partners, social commerce, and increasingly agentic channels where AI assistants buy on the customer’s behalf. Each behaves differently.

Strain shows in: pricing rules conflict across channels · promo mechanics clash · range duplicated or misaligned

2. Range extension

Catalogues outgrowing human attention.

Catalogues are an order of magnitude larger than they were a decade ago — from a few thousand SKUs across an FMCG brand portfolio to tens of thousands in big-box retail. Range expansion is structural, driven by long-tail demand and faster product introduction.

Strain shows in: a fraction of lines actively reviewed · the long tail runs on autopilot · margin and stock-turn leak quietly

3. Pace and 24/7 trading

Hourly markets, weekly meetings.

Consumers expect price, promo, range and inventory to react in hours. Competitors automate large parts of their trading. Margin and conversion now move faster than a weekly cadence can carry.

Strain shows in: weekly meeting vs hourly market · two-week lag on competitor moves · decisions arrive too late

4. Maturation of technology

The tools to keep up have arrived.

Machine learning, structured decision systems, optimisation under uncertainty — no longer research. Compute is cheap, libraries are mature, SaaS layers production-grade. Hedge-fund-only ten years ago; consumer-trading-grade now.

Strain shows in: technology no longer the constraint · most systems aren’t built to use it · adopter–laggard gap compounds

The end goal: a trading team of one. The system handles the 99% of decisions a system can take; the operator’s time goes entirely to the 1% that decides the year.

What we bring

Reinvented trading across marketplaces, partnerships, owned digital, and customer lifetime.

Marketplace Strategy

Make your seller economics work both ways.

Fee economics, seller mechanics, take-rate modelling, marketplace P&L.

Typical improvements in: marketplace contribution margin · seller retention · take-rate yield · GMV per active seller

Analytical Partnership Management

Partnership economics, modelled and optimised.

Franchise unit economics, joint business planning grounded in shared forecasting, marketplace seller economics, agency commercial terms — designed and optimised across the partner stack.

Typical improvements in: partner LTV · joint-forecast accuracy · partner-funded investment · deal NPV with confidence bands

Owned Digital Channel Optimisation

Stop guessing which lever in the funnel actually moves the number.

Funnel optimisation, basket-economics design, channel-mix planning, retention-loop engineering across owned digital.

Typical improvements in: conversion rate · average order value · contribution per session · retained cohort value

Customer Lifetime Value Management

Treat LTV as a managed asset, not a downstream metric.

Cohort design, retention engineering, loyalty programme economics, churn prediction, net-revenue-retention management — built into how the trading function operates.

Typical improvements in: customer LTV · net revenue retention · cohort payback period · churn rate

Built on two decades of FTSE-250 consumer commercial experience and a production-grade quantitative toolkit. The practice brings what works at scale in consumer together with what works at the frontier of applied technology.

Next-generationcommercial systems.