Track Amazon Best Sellers rank with Apify and qualify low-competition products

Reads Amazon Best Sellers, Movers & Shakers and New Releases for your categories through Apify in monitor mode, so only new entries and rank changes come back. Each one is scored on rank gain, new-entry status, top-10 position, price band and how few reviews it has (a strong rank with few reviews suggests a market you could enter). Built for sellers doing product research and for brand teams watching a category. The rank is part of the dedupe key, so a product that moves again is reported again.

How it works Daily schedule / manual run reads every setting from Config. A weekly schedule uses the same Config to send a report instead of running the actor. Starts the Apify actor asynchronously, then waits and polls the run; FAILED, ABORTED, TIMED-OUT or too many polls stop with an error. Downloads the dataset, validates rows and dedupes within the run and across runs (workflow static data, dedupeMemoryDays). A transparent rule score runs first, then an LLM chain with a structured output parser reads each record against your plain-English aiCriteria and returns a fit score, verdict, summary, outreach angle and red flags. Calls are batched with a delay for rate limits, retried, and fall back to the rule score if the model fails. Upserts every row to Google Sheets. Hot rows go to Slack as one approve / dismiss message (send-and-wait, 24 h limit) and the decision is written back to the sheet; warm rows go to an HTML email digest; cold rows stay in the sheet. Weekly report: reads the sheet, summarises the last 7 days (tiers, approvals, top 10) and emails it. A separate Error Trigger branch posts any failure to Slack.

Setup (about 15 minutes) Create an HTTP Header Auth credential: name Authorization, value Bearer (Apify Console > Settings > API & Integrations). Select it on the 3 Apify HTTP nodes. Create a Google Sheet with a tab named in sheetTab and a header row matching the sheet columns (see Upsert to Google Sheets, plus status and reviewedAt). Paste its ID into googleSheetId. Connect OpenAI (or swap the chat model sub-node for Anthropic, Gemini, Ollama...), Slack and Gmail; set slackChannelId and digestEmail in Config (also the channel on Slack: error alert). In Config set actorInput.categories, listTypes and countryCode, then lowCompetitionReviews, minStars, minPrice and maxPrice. Use a distinct monitorStoreName per tracker. Write your ideal-lead description in aiCriteria; set aiWeight (0 = rules only, 1 = AI only). Run once manually, check the sheet, then activate.

Customize Edit weights in Score rank movers (new entry 25, rank gain 25, top-10 15, low reviews 15, % change 15, price band 10). Add depth for subcategories or scrapeProductDetails for brand and seller data. Swap Gmail/Slack for Teams, Discord, HubSpot, Airtable, etc. Each delivery node only reads $json.

Disclosure: I maintain these Apify actors (account transparent_meteorite). The actor is a paid pay-per-event Apify tool; check its Store page for current pricing before scheduling.