Eugene Mischenko / Business resources
Retail, marketing & AI.
Launch an online retail operation, improve order economics, organise marketing and evaluate AI. Detailed guides, working files and analyses grounded in published sources.
Practical guides
E-commerce profitability: diagnose the cost of each order
Calculate contribution per fulfilled order, trace picking and delivery costs, and diagnose why online sales growth fails to improve profit.
Omnichannel audit: connect stores, orders and customer data
Audit customer identity, stock availability, store picking, pickup, returns and channel economics across a retail network.
Marketing department audit: a working checklist for owners
Review strategy, budgets, roles, agency coordination and measurement. Prepare the evidence for a marketing department audit and a practical improvement plan.
How to evaluate a marketing agency’s work
Review agency scope, account access, campaign quality, costs and commercial results before renewing a contract or changing your provider.
Working with a fractional CMO: mandate, team and first decisions
Define the mandate of a fractional CMO, the team they will lead, decision rights, reporting and the first phase of an engagement.
Choose an AI marketing use case for a measurable pilot
Compare AI marketing tasks by business value, data readiness, error consequences, review effort and integration requirements before starting a pilot.
Taking a retail store online: picking, delivery and fulfilment
Plan an online retail launch around assortment, stock, store picking, delivery capacity, customer service and order economics.
Hiring a Head of E-commerce: assess commercial judgement
Build a role brief, structured interview and retail business case to assess candidates for Head of E-commerce or Online Sales Director.
How to audit an e-commerce business
An e-commerce audit checklist covering order economics, conversion, fulfilment and repeat purchases. Practical questions for owners and commercial teams.
How to plan an AI pilot in marketing
A practical framework for evaluating AI in marketing: use cases, test data, quality, human review and operating costs. From business question to pilot decision.
Experience in detail
METRO: customer data across online and store purchases
A METRO case analysis of customer identity, coordinated communication and measuring purchases across stores, websites, apps and delivery partners.
METRO: store picking and delivery partner operations
A retail fulfilment case examining store picking, partner handovers, staging space and the economics of serving online orders from a trading store.
L’Occitane: online shopping and store customer experience
A L’Occitane case analysis covering product choice, gifting, loyalty identity and the evaluation of customer movement between online and retail stores.
METRO in 2020: changing online demand and store pickup
A case analysis of METRO’s April 2020 demand and pickup discussion, with practical decisions on basket mix, capacity, collection and repeat purchases.