User ManualOPERATIONS FIELD GUIDE

Data analysis

Product reviews data

Read original reviews, star filters, and derived distributions.

Review analysis reads acquired product reviews without requiring automatic low-rating follow-up to be enabled. Investigate product quality, expectation gaps, and delivery experience; analysis does not itself contact buyers.

All tables contain fictional sample data, not real reviews. Detail comes from review queries. Rating distributions, averages, and issue categories are subsequent AI analysis, not additional sources.

#Product review detail

Each row is one Shop review, retaining its latest version, without duplication across multiple SKUs. Available fields include review/order/product identifiers, seller SKU when supplied, stars, title/text, creation/update timestamps, and buyer nickname when available.

Query all 1–5-star Brightloom US reviews from the last 30 days. Preserve original text and creation dates, calculate rating distributions by product, then summarize issues. Do not contact buyers.

Select dates using Shop-local review creation, preserving update time separately. Queries default to a 1–3-star focus; explicitly request 1–5 stars for overall analysis.

#Sample raw detail

ReviewCreatedProductSKUStarsBuyer nicknameOriginal text
DEMO-RV012026-10-13Cloud BlanketCB-BLUE2maya-demoThe color is darker than the photo.
DEMO-RV022026-10-14Cloud BlanketCB-BLUE5—Soft and the right size.
DEMO-RV032026-10-14Bedside LampBL-WHITE1rowan-demoDamaged packaging and a cracked shade.

Leave anonymous or missing nicknames unavailable. A nickname is not a guaranteed contactable account. Text can be revised; today's content need not be the earliest submitted version.

#Sample AI-derived summary

ProductQueried reviews1–3 stars4–5 starsAverage starsIssue lead
Cloud Blanket2113.50Color expectations
Bedside Lamp1101.00Packaging or transit damage

Across these three rows, the average is (2 + 5 + 1) ÷ 3 ≈ 2.67 stars. Querying only 1–3 stars excludes row two and cannot produce an overall rating average.

Issue categorization is text analysis, not proven responsibility. A cracked shade warrants checking returns/refunds, products, and logistics; one review does not establish fault by a warehouse or carrier.

#Reviews and exports

State the period, star filter, actual coverage, and review count. Incomplete history is not an absence of low ratings, and a revision is not an extra review. Before follow-up, check contact rules and human-decision workflows.

Return to Business data or read Reports and exports.

TK COPILOT · OPERATIONS FIELD GUIDE© 2026 RIVON LLC