Merchandising & Buying
Newness versus continuity performance analysis
Analyse the sales contribution of new lines against carry-forward lines across seasons. Identifies whether newness is driving incremental revenue or cannibalising existing bestsellers.
5–10%
improvement in newness sell-through rate
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.
Very low risk. Fully internal use. A person checks everything before it goes further. Worst case is a minor internal inconvenience.
Very easy to absorb. Runs quietly in the background or gives people a helpful new input. Makes everyday work easier with almost no friction.
Tooling required
Things to consider
Requires product data that reliably distinguishes new, updated, and carry-forward lines — if this classification isn't in the data, it needs to be added before analysis is possible.
Cannibalisation analysis is inherently difficult: a decline in a continuity line when a new line launches could be cannibalisation or a natural decline. The AI surfaces the correlation; the buyer applies judgment.
The most actionable output is a view of which new lines delivered truly incremental volume versus which merely displaced existing sales. This directly informs future ranging strategy.
The analysis is most useful when done at category or sub-category level, not across the full range. Averaging across all categories obscures the patterns that drive decisions.
Experiment starter: For two completed seasons, classify all lines as new, updated, or continuity and compare average sell-through, markdown rate, and contribution by classification. Present the analysis in the next ranging review. If it changes the team's perspective on newness investment levels, it's working.
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.
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