Customer Feedback Review Cycle

Confirm the post-purchase flow is firing on the Order Fulfilled trigger (not Order Placed) so survey requests don't go to canceled orders. Check open and click rates against last month — a sudden drop usually means a deliverability issue with the sending domain or a broken merge tag.

Pull all reviews and seller feedback from the prior 30 days for each ASIN. Do not request reviews via outbound email — only the Seller Central "Request a Review" button or Vine are within Amazon ToS for incentivization.

Export site reviews and photo/video UGC submissions. Filter for unmoderated reviews still in the queue — letting these sit kills review velocity on product pages.

Filter for tickets tagged sizing, defect, shipping-damage, missing-item, and refund-request. Don't rely solely on tags — sample 20 untagged tickets to spot-check coverage; CX agents miss tags during high-volume days.

Confirm response rate is in your historical band (typically 5-15% for transactional NPS). A drop usually means survey fatigue, a broken send, or a list segmentation error. Note the count of detractors (0-6) and passives (7-8) for downstream outreach.

Combine Klaviyo, Amazon, Yotpo, Gorgias, and NPS exports into a single sheet or BI tool (Triple Whale, Glew, Daasity). Normalize the columns: source, date, SKU/ASIN, customer ID, rating, verbatim, channel.

Apply a fixed taxonomy: sizing, fit, quality/defect, shipping-damage, shipping-speed, packaging, listing-mismatch, CX-experience, pricing, subscription-billing. Avoid free-tag drift — operators invent synonyms that fragment themes.

A theme that's universal looks different from one concentrated on a single SKU or one channel. Sizing complaints concentrated on Meta-acquired customers usually mean the ad creative is overpromising fit; complaints concentrated on one SKU mean a manufacturing or listing-image issue.

Cross-reference low-star reviews with returns rate by SKU. A SKU moving from 3% to 8%+ returns rate alongside negative reviews on the same theme is a manufacturing or listing problem that needs the product team, not just a CX response.

Each theme: short name, volume, sample verbatims, affected SKUs, estimated revenue exposure (returns + lost LTV). One page max — leadership won't read a 10-page deck monthly.

Quick win quadrant: high impact, low fix cost (listing copy, sizing chart, packaging insert). Defer: low impact, high fix cost (tooling change for an edge complaint). Cheap-and-easy fixes ship this cycle; expensive ones go to the product roadmap.

Listing fixes go to the merchandiser or e-commerce manager. Quality/defect themes go to the product manager or sourcing lead. CX-experience themes go to the CX lead. Each owner gets a due date and a definition of done.

Refresh sizing chart, A+ content, lifestyle images, or bullets to match the actual product. After Amazon edits, monitor for listing suppression — a flagged claim or an attribute mismatch can pull the listing from search until reviewed.

For SKUs flagged in the analysis phase: open a quality investigation with sourcing or manufacturing. Include defect rate, sample reviews, photos from CX tickets, and affected lot/batch numbers if known.

Personal reply from a CX lead, not a templated drip. Acknowledge the specific complaint, share what's changing, and offer a make-good (replacement, refund, or store credit) where appropriate. Detractor recovery is the highest-leverage CX work in any given month.

Public responses on 1-3 star reviews show prospective buyers the brand is engaged. Keep responses factual; never argue with a reviewer or imply they're lying — Amazon will pull the response and may flag the seller account.

Send through Klaviyo to repeat customers and segment to the customers who flagged the issue. Concrete and specific ("we updated the sizing chart for the relaxed-fit tee after 40 of you told us it ran small") — not generic ("we listened to your feedback").

Trigger a targeted Klaviyo survey 30-45 days after the fix ships, only to customers who reported the issue. This validates whether the change actually moved the metric, and feeds the next cycle's analysis.