Apify Ecommerce

Step 4: Run the Actor and Fetch Results

Two steps: run the Actor (blocks until done), then fetch dataset items in the requested format.

Run the Actor — returns run metadata as JSON; extract defaultDatasetId for the next step:

apify actors call "ACTOR_ID" -i 'JSON_INPUT' \
  --user-agent apify-awesome-skills/apify-ecommerce --json 2>/dev/null

From the output use .id (run ID), .status (should be SUCCEEDED), and .defaultDatasetId.

Fetch results — pick the variant based on the user's preference:

# Quick answer: total count + fields + top 5 in chat (no file)
apify datasets info DATASET_ID --json \
  --user-agent apify-awesome-skills/apify-ecommerce 2>/dev/null \
  | jq '{itemCount, fields, consoleUrl}'
apify datasets get-items DATASET_ID --limit 5 \
  --user-agent apify-awesome-skills/apify-ecommerce --format json 2>/dev/null

# CSV file
apify datasets get-items DATASET_ID \
  --user-agent apify-awesome-skills/apify-ecommerce --format csv 2>/dev/null > YYYY-MM-DD_OUTPUT_FILE.csv

# JSON file
apify datasets get-items DATASET_ID \
  --user-agent apify-awesome-skills/apify-ecommerce --format json 2>/dev/null > YYYY-MM-DD_OUTPUT_FILE.json

Other --format options: jsonl, xlsx, xml, rss, html. Use --offset N to paginate large datasets.

Tip: for anything more than a quick peek, save the dataset to a local file first (with > file.json / > file.csv) and run further analysis from disk. apify datasets get-items always streams over the network, so piping it straight into jq re-downloads the whole thing every iteration.

Combining with jq for quick extraction:

Treat jq as a complement to apify datasets get-items, not a replacement: server-side --limit / --offset / --format keeps cost and bandwidth down. Use jq on a sample item or on a file you already saved.

# Discover real field names from one sample item (Actor outputs vary —
# use this before composing further jq queries)
apify datasets get-items DATASET_ID --limit 1 --format json \
  --user-agent apify-awesome-skills/apify-ecommerce 2>/dev/null \
  | jq '.[0]'

# Quick aggregation from a JSON file you already saved with the commands above
jq '[.[] | select(.rating != null and .rating >= 4.5)] | length' YYYY-MM-DD_OUTPUT_FILE.json

Step 5: Analyze Results and Deliver Answer

After the run completes, deliver a direct synthesized answer — not a data dump:

• Pricing: price range, average, top 5 cheapest with URLs
• Reviews: average rating, top 3 positive and negative themes, recent snippets
• Bestsellers: top 10 by rank with name, price, rating, URL
• Sellers: total sellers, price range per seller, unauthorized seller flags
• Store-scrape: total products, category breakdown, price range, stock summary
• Tech-stack: platform detected, confidence level, notable plugins
• Food delivery: restaurant count, average rating, price tier breakdown
• Ads intelligence: total ads, active/inactive split, top creative formats

Error Handling

• Auth error → run apify login, or set APIFY_TOKEN env var
• Actor not found → check Actor ID spelling in the routing table
• Run status FAILED → open the console URL (.consoleUrl from run metadata) for logs
• Timeout / very long run → pass --timeout <seconds> to apify actors call
• No results → broaden the keyword, switch to the Fallback Actor, then use the Escalation discovery command (under Step 1) if both fail
• proxy is required → add "proxy": {"useApifyProxy": true} to the Actor input
• Platform not detected → default to apify/e-commerce-scraping-tool with generic intent

Gotchas

• --input --json is a trap. It returns the full ~250 KB actor object, not the schema. Use apify actors info ID --input --user-agent apify-awesome-skills/apify-ecommerce 2>/dev/null (no --json) for the clean schema; only dig into .taggedBuilds.latest.build.inputSchema if you specifically need it as JSON.
• The Primary actor has no maxResults field. Its caps are mode-specific (maxProductResults, maxReviewResults, maxSellerResults, maxSearchEngineResults, maxDeliveryResults). Setting maxResults does nothing and the run scrapes unbounded.
• The Primary handles most intents via the right input mode (URLs → detailsUrls/listingUrls; query → keyword or searchEngineKeyword), including competitor, search-intent, classifieds, automotive, real-estate, website-marketplace, and events. It genuinely can't do tech-stack, seo-audit, store-enrichment, product-matching, ads-intelligence, content-discovery (Pinterest), or tiktok-shop — route those straight to the Fallback.
• apify actors call -i expects valid JSON on one line. For inputs with URL arrays or quotes, write a file and pass -i @input.json instead of inlining — shell quoting silently corrupts complex inputs.
• datasets get-items always streams over the network. Save to a file once (> file.json), then run jq against the file — don't re-pipe the command into jq repeatedly or you re-download every time.
• apify actors search --sort-by popularity ignores relevance. It returns the biggest-name scrapers regardless of your query (an "etsy" search surfaces Instagram/Google Maps Actors). For escalation discovery keep the default relevance sort and filter on stats.totalUsers/actorReviewRating instead.
• marketplaces values are full domain slugs, e.g. ["www.amazon.com", "www.ebay.com"] — not "amazon" or display names. Delivery mode is even narrower: marketplacesDelivery only accepts ["www.doordash.com", "www.instacart.com"] (no UberEats — use the e-commerce/ubereats-reviews-scraper fallback for that). Always confirm accepted values from the --input schema's enum before guessing.