Merchandising & Buying
Competitor product monitoring
Monitor competitor ranges, pricing changes, and new product launches. Summarise weekly into a structured digest for buying and trading teams.
60–80%
reduction in competitor monitoring effort
Opportunity assessment
Minor improvement. Small efficiency gain with limited effect on overall turnover or bottom line.
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 a consistent data source — whether scraped, manually pulled, or via a third-party feed. The AI summarises; it doesn't collect.
Define the competitive scope clearly (which competitors, which categories) to keep the digest focused and actionable.
The digest format matters: decide what the buying team actually wants to know each week and design the output around that, not what's easy to generate.
Web scraping carries legal and technical risk — check terms of service for each competitor site, and consider whether a third-party data provider is a more reliable and defensible source than a custom scraper.
Experiment starter: Manually pull competitor data for three key categories over four consecutive weeks and use an LLM to summarise changes and flag new launches. Share the digest with the trading team and test whether they find it useful before investing in automation.
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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