Merchandising & Buying
Product lifecycle stage classification
Classify every line by lifecycle stage — launch, growth, mature, decline — from sales trajectory, rate of sale, and price realisation, so ranging and markdown decisions follow the stage rather than the calendar.
5–10%
improvement in full-price sell-through
Opportunity assessment
Moderate impact. Meaningful cost or revenue improvement, likely noticeable at function level but modest relative to total business scale.
Relatively straightforward. Off-the-shelf tools handle the core task. Implementation is well-understood with good examples to follow.
Moderate data needs. Works with data most businesses hold, but will likely need consolidation, cleaning, or reformatting before use.
Low risk. Limited external exposure. A human reviews output before it reaches anyone outside the team.
Moderate people impact. Part of someone's working day changes. Requires training and some adjustment time, but roles remain broadly the same.
Tooling required
Things to consider
The commercially useful call is the transition from growth to mature, because that is when buying depth should change and usually does not.
Distribution changes confound the trajectory. A line whose sales rose because it went into fifty more stores is not in growth, and the model needs store-count-adjusted rate of sale to see that.
Short-life seasonal lines need a separate model. Applying a lifecycle framework designed for continuity lines to a six-week seasonal buy produces nonsense.
Experiment starter: Classify your continuity range and check the classification against what the buying team believes. Focus the discussion on the lines the model calls mature that the team still buys as growth.
Go deeper in the playbook
Section — Opportunity Identification, including the AI Opportunity Assessment ScorecardSection — RAG and Knowledge Systems: Unlocking Proprietary DataThis is an decision support opportunity — see the relevant playbook section for how to approach it.More in Merchandising & Buying
Product description writing
Generate first-draft product descriptions from attributes, imagery, and brand guidelines. Buying team reviews, edits, and approves before publish.
Supplier spec sheet extraction
Extract structured product data from unstructured supplier spec sheets, PDFs, and email attachments. Outputs clean records ready for system upload.
Range review analysis
Summarise sales performance, markdown rates, and return data by category to surface underperformers and inform ranging decisions.
AI Transformation Playbook
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