Merchandising & Buying
Trend report synthesis
Summarise trend intelligence from runway reports, trade press, social data, and competitor observations into structured buying briefs. Reduces research time before range planning.
60–75%
reduction in trend research and synthesis time
Opportunity assessment
Negligible commercial impact. Saves time at the margins but won't move the needle on revenue or profit.
Very easy to implement. Ready-to-use tools exist. Can be up and running in days or weeks with minimal technical resource.
Light data requirements. Uses straightforward inputs — documents, product descriptions, customer records — that are usually accessible with minimal prep.
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
Heuritech, used by Louis Vuitton, Dior, and Moncler, analyses 3M social media images daily and achieves 90% accuracy on trend prediction up to 24 months ahead (Harvard Business School).
The AI summarises and structures; the creative judgment about which trends are relevant to your customer is still the buyer's work.
Source quality drives output quality — if the AI is summarising low-quality or narrow sources, the synthesis will reflect that. Curate the input library carefully.
Format the output to match how buying teams actually use trend information (by category, by key look, by colour direction) rather than as a generic summary.
There is a real risk of homogenisation if all buyers across the market use the same AI-summarised trend sources. The synthesis should be a starting point for conversation, not a replacement for a buyer's own commercial eye.
Experiment starter: Before the next range planning session, have an LLM synthesise the trend reports and trade press the team would normally read and produce a structured brief. Ask buyers to compare the synthesis against their own research notes and identify anything it missed or got wrong. A time saving with no material gaps makes the case for regular use.
Go deeper in the playbook
Section — Opportunity Identification, including the AI Opportunity Assessment ScorecardSection — The Experimentation FrameworkThis is an augmentation 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
Ready to assess your own opportunities?
The playbook gives you the full 150-opportunity directory, scoring tools, and 100+ templates for every stage of an AI transformation programme.