Buying and Merchandising Course Online

This module introduces the responsibilities of the Fashion Buyer and explains how the role contributes to sales, profitability, brand positioning and customer satisfaction. You will understand how buyers collaborate with different departments and manage product assortments across markets and sales channels.

• The purpose and main responsibilities of Fashion Buying
• Daily activities and key professional skills
• Collaboration with merchandising, finance, supply chain, marketing and retail teams
• Differences between global, local and multibrand buyers
• Fashion collection structure: seasons, collections, drops and pre-collections
• Carryover, seasonal and Never-Out-of-Stock products
• Introduction to sell-in, sell-out and sell-through

This module explains how buyers transform business objectives, market insights and historical performance into a structured buying plan. You will learn how to define purchasing budgets, establish commercial targets and use the Open-to-Buy framework to control inventory investment.

• Top-down and bottom-up planning approaches
• Combining financial targets with store and market insights
• Total-look buying versus category-based buying
• Defining sales, margin and inventory targets
• Open-to-Buy definition and formula
• Calculating the available purchasing budget
• Updating the Open-to-Buy based on actual performance
• Using historical data and forecasts to guide buying decisions

This module focuses on building commercially balanced assortments and allocating products according to store potential, customer demand and brand strategy. You will learn how to determine the right number of styles, quantities, sizes and product options for different stores and markets.

• Creating the master order for an ideal reference store
• Translating the master order into store and market assortments
• Allocating orders by individual store or store cluster
• Balancing assortment width and depth
• Defining product options, quantities and size ranges
• Adapting size curves to different markets
• Balancing carryover, seasonal and Never-Out-of-Stock products
• Aligning product availability with store capacity and sales potential

This module develops the analytical skills required to evaluate product performance, identify inventory risks and improve stock productivity. You will learn how to interpret the most important Fashion Buying KPIs and translate performance data into commercial actions.

• Understanding the inventory lifecycle
• Measuring stock turnover
• Analysing sell-in and sell-out performance
• Using the funnel approach: from channel and market to SKU
• Core buying KPIs: sales, units, margin and average selling price
• Sell-through, stock cover and full-price sales
• Identifying bestsellers and slow movers
• Managing overstock and stock-outs
• Planning replenishments, stock transfers and reorders

This module explains how buyers monitor performance during the season and take timely action to protect margins, maximise sales and reduce leftover inventory. You will learn how to manage replenishments, transfers, promotions and markdowns throughout the product lifecycle.

• The buyer’s responsibilities during the buying campaign
• Daily and weekly performance monitoring
• Comparing actual results with budgets and forecasts
• Rebalancing stock between stores and markets
• Replenishing high-performing products
• Planning markdown timing and discount levels
• Monitoring markdown rate and average discount
• Managing end-of-season inventory
• Using outlets, stockists and other clearance channels

This module shows how to manage physical stores and eCommerce as a unified inventory ecosystem. You will learn how to allocate products across channels, support omnichannel fulfilment and maximise product availability while protecting the customer experience in each market.

• Unified stock planning across retail and eCommerce
• Allocating products by channel and store type
• Defining the role of flagship, medium and smaller stores
• Using stores as decentralised fulfilment hubs
• Ship-from-store and store-as-warehouse models
• Reserving local stock while supporting online demand
• Dynamic allocation and in-season rebalancing
• Managing omnichannel bestsellers and long-tail products
• Monitoring channel-specific availability and performance KPIs

This module explores practical ways in which artificial intelligence can support Fashion Buyers, improve operational efficiency and enhance decision-making. You will discover how AI can assist with data analysis, forecasting, replenishment and market intelligence while respecting data-security requirements.

• Using AI to analyse complex buying and sales data
• Summarising reports and identifying commercial insights
• Automating Never-Out-of-Stock replenishment processes
• Monitoring competitors, markets and emerging trends
• Supporting forecasts and product-performance analysis
• Identifying potential risks and commercial opportunities
• Protecting confidential company information when using external AI tools

This practical module allows you to apply the frameworks and KPIs covered during the course to realistic Fashion Buying scenarios. Through data-based exercises, you will practise making purchasing, inventory and omnichannel allocation decisions and learn how to justify them using commercial evidence.

• Calculate the available Open-to-Buy budget
• Allocate a buying budget across different store clusters
• Analyse sell-through, stock cover and full-price performance
• Decide when to replenish, transfer, markdown or maintain products
• Estimate the commercial impact of delayed action
• Allocate inventory across physical stores and eCommerce
• Balance online demand with stock reserved for local customers
• Justify buying decisions using data and commercial objectives

Introducing Fashion Merchandising

Understanding how Fashion Merchandisers connect creative vision with commercial objectives throughout the product lifecycle

• The purpose and responsibilities of Fashion Merchandising
• Balancing creativity, market demand and financial performance
• Collaboration with design, product development, finance, buying and marketing teams
• Product hierarchy: style, material, colour, size and SKU
• Fashion collection structure and seasonal terminology
• Pre-collections, main collections, carryovers, deliveries and drops
• Introduction to sell-in, sell-through and sell-out
• The collection calendar and retroplanning process

Using Data to Evaluate Collection Performance

Learning how to identify product opportunities, commercial risks and priorities through structured performance analysis

• Analysing sell-in and sell-out performance
• Using the analytical funnel: from market and channel to individual SKU
• Measuring sales performance in value and units
• Understanding product and category contribution to total business
• Evaluating year-on-year performance variations
• Margin and profitability analysis
• Average selling price and Units per Transaction
• Sell-through and discount-rate monitoring
• Using Excel, Power BI, Tableau and Qlik for merchandising analysis

Translating Business Objectives into a Collection Plan

Creating a structured collection brief that combines financial targets, market insights, product needs and creative direction

• The purpose and structure of the collection brief
• Defining financial and collection-size targets
• Identifying product needs and key design directions
• Creating the price architecture
• Establishing the range plan
• Measuring collection efficiency
• Understanding the 70% development-to-production efficiency target
• Managing the commercial and operational risks of over-development
• Translating analytical findings into clear product requests

Building a Balanced and Competitive Collection

Using collection structure, price positioning, trend research and benchmarking to identify market opportunities

• Creating the collection pyramid
• Balancing image products, seasonal products and carryovers
• Mapping price ranges and product functions
• Identifying product and price gaps within the collection
• Researching trends through social media, VIPs and fashion shows
• Using trend-forecasting platforms such as WGSN and Heuritech
• Collecting insights from local teams and international markets
• Benchmarking competitors by product, material and price point
• Using Retviews, LiveTrend and EDITED for market intelligence

From Product Concept to Final Sample Set

Applying the merchandising strategy during product development while maintaining creative, financial and commercial alignment

• Coordinating design sketches and prototype development
• Reviewing products for design, cost and strategic alignment
• Maintaining numerical and commercial objectives during development
• Managing product changes and development reviews
• Freezing the collection for the selling campaign
• Defining the sample set
• Selecting which SKUs should be physically sampled
• Using samples for sales, marketing, photoshoots and celebrity placements
• Communicating differences between samples and final production

Preparing and Presenting the Collection

Organising the physical and digital selling environments required to communicate the collection and support buying decisions

• Reviewing sample quality, costs and margins
• Finalising prices, deliveries and product drops
• Managing last-minute product changes
• Setting up the physical showroom
• Creating looks and product combinations that support buying decisions
• Preparing the virtual showroom
• Using platforms such as JOOR, NuORDER and Hyphen
• Creating the master order and merchandising push
• Selecting products for marketing and communication activities
• Presenting the collection concept, novelties, materials and craftsmanship
• Understanding the merchandising implications of fashion-show collections

Managing the Collection Across Stores and eCommerce

Coordinating the product launch and using in-season performance data to improve sales and product availability

• Monitoring sell-in results and production status
• Tracking production delays and launch timing
• Preparing product training and updated content
• Coordinating store and eCommerce launches
• Ensuring consistent product visibility and information across channels
• Monitoring sell-through and customer-demand signals
• Combining quantitative data with qualitative market feedback
• Identifying bestsellers and underperforming products
• Recognising seasonal products with future carryover potential
• Supporting replenishment, redistribution and corrective actions

Managing the Final Stage of the Product Lifecycle

Clearing remaining inventory while protecting margins, profitability and brand positioning

• Evaluating stock levels and residual customer demand
• Defining markdown strategies according to product performance
• Balancing inventory clearance with brand positioning
• Managing discounts and promotional activity
• Redistributing remaining products across markets and channels
• Using outlets and stockists as alternative sales channels
• Analysing final collection performance
• Identifying lessons and insights for the next collection brief

Using AI to Improve Merchandising Efficiency

Exploring how artificial intelligence can accelerate analysis, automate recurring activities and improve market responsiveness

• Using AI to summarise complex data files
• Extracting insights from sales and product-performance information
• Supporting trend and market research
• Discovering emerging brands and competitors
• Automating product descriptions and copy corrections
• Increasing the efficiency of recurring merchandising activities
• Using AI as a decision-support tool rather than a replacement for human judgement
• Protecting sensitive and confidential company information