n8n Workflow: Triage AliExpress Reviews with Apify Scraper

Spot AliExpress review problems fast—triage complaints automatically with Apify

This n8n workflow scrapes a bounded sample of AliExpress product reviews using Apify (FalconScrape’s AliExpress Reviews Scraper), then generates a triage report that flags low-rated complaints, issue categories, and the variants most affected—all on demand.

What this workflow does

• Runs manually: you provide the target AliExpress /item/<number>.html URL, review sample size, spend cap, and a low-rating threshold.
• Validates inputs and either resumes an existing Apify Actor run (via run ID) or starts a new charge-capped Apify run for the product (e.g., $0.01–$1).
• Polls Apify run status until it succeeds, or fails/stops if the run errors or takes too long.
• Fetches and cleans review data: pulls up to 100 cleaned review items from the Apify dataset.
• Computes rating distribution and filters to reviews at or below the low-rating threshold.
• Triages low-rated text into issue buckets using keyword rules, aggregates the most affected variants, and includes example excerpts with basic PII redaction.
• Outputs an action-level report: “ATTENTION” when there are one-star reviews or at least three low-rated reviews; otherwise “ROUTINE”.

Use cases

• Monitor a specific AliExpress listing for emerging quality issues without manual reading.
• Identify recurring complaint themes (via keyword issue buckets) and which variants attract the most low ratings.
• Support customer-facing teams with a quick, evidence-based triage summary.

Technical details

• Apify integration: requires an Apify API credential and access to Actor ID wfBNb1rkpWRQhOufx (FalconScrape’s AliExpress Reviews Scraper).
• n8n nodes used: if, set, code, sticky note, http request, manual trigger.

Configure product, set maxReviews (1–100), maxChargeUsd ($0.01–$1), and lowRatingThreshold, then run the workflow to get an immediate review triage report.