Merchandising & Buying
Product cannibalisation detection
Identify when new product introductions are stealing sales from existing range rather than generating incremental revenue. Flag cannibalisation patterns at category and location level.
10–20%
improvement in new product incremental revenue assessment
Opportunity assessment
Moderate impact. Meaningful cost or revenue improvement, likely noticeable at function level but modest relative to total business scale.
Challenging. Significant technical work required. Likely needs an AI engineer or specialist vendor. Not a quick win.
Demanding data requirements. Relies on clean, integrated data across multiple systems. Significant data preparation work typically needed.
Low risk. Limited external exposure. A human reviews output before it reaches anyone outside the team.
Light people impact. A new tool slots into an existing workflow. Minimal training needed. Most people will adapt quickly.
Tooling required
Things to consider
Cannibalisation is hard to isolate from other effects (seasonality, promotion, competitor activity). The model needs to control for confounders, which requires good baseline data.
This works best post-launch as a diagnostic tool rather than a predictive tool — confirming cannibalisation quickly lets you adjust range or space allocation before the season is lost.
Buyers are often resistant to evidence that their new product isn't generating incremental sales — frame the output as range optimisation, not performance criticism.
Experiment starter: Select three recent product introductions and one control group of similar existing products. Run a basket analysis to see whether the new products appear alongside or instead of existing lines. If substitution exceeds 40%, you have a cannibalisation problem worth investigating at scale.
Go deeper in the playbook
Section — Opportunity Identification, including the AI Opportunity Assessment ScorecardSection — The Experimentation FrameworkFeasibility is limited here — the experimentation framework covers how to run a bounded pilot before committing.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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