Amazon & Shopify Review Pain-Point & Ad Hook Miner | MCP & AI avatar

Amazon & Shopify Review Pain-Point & Ad Hook Miner | MCP & AI

Pricing

from $40.00 / 1,000 verified defect cluster & direct-response ad hook packs

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Amazon & Shopify Review Pain-Point & Ad Hook Miner | MCP & AI

Amazon & Shopify Review Pain-Point & Ad Hook Miner | MCP & AI

Cluster product and SaaS reviews into quantified engineering failure modes, severity matrices, and ready-to-launch Meta/TikTok direct-response ad hooks.

Pricing

from $40.00 / 1,000 verified defect cluster & direct-response ad hook packs

Rating

5.0

(1)

Developer

Vadim Polansk

Vadim Polansk

Maintained by Community

Actor stats

3

Bookmarked

5

Total users

4

Monthly active users

18 hours ago

Last modified

Security

Limited permissions

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E-Commerce Review Pain-Point Matrix & Ad Hook Miner (ecom-review-pain-miner)

Pay-Per-Event (PPE) AI & Data Enrichment Actor — No monthly subscription required. Pay only for verified dataset items pushed to your output.

Why Use ecom-review-pain-miner?

  • Target Use Case: Amazon/Shopify Brands, SaaS Product Managers, Performance Ad Teams
  • Sub-Millisecond Quality Gate (borz-s45-tc-09): Built-in 0.34ms neural quality pre-gate filters out boilerplate, cookie banners, and low-signal noise before emitting billable dataset items.
  • Live URL & Domain Fetching: Pass raw URLs (https://...), company domains (stripe.com), or raw text excerpts — the actor automatically fetches live page titles, metadata, and body signals when a URL/domain is provided.
  • Ready for AI Agents, MCP, n8n, Make.com & Clay: Outputs strict, deterministic JSON schemas with an interactive Overview Table view.

Input Example (JSON)

{
"items": [
"Cluster #1 (38.4% of 1-star reviews, n=412): Silicone lid gasket warps above 65°C dishwasher cycle, causing 15ml/min leak. Ad Hook: 'Tired of shaker lids leaking in your gym bag after one wash?'",
"Cluster #2 (29.1% of SaaS churn reviews, n=189): Webhook retry queue drops events silently during 502 spikes without DLQ replay. Ad Hook: 'Stop losing Stripe webhooks during traffic spikes—100% replayable DLQ.'",
"Cluster #3 (44.0% of wireless earbud returns, n=620): Copper charging pogo-pins oxidize from sweat after 3 weeks, blocking left-bud charge. Ad Hook: 'Sealed magnetic induction charging—zero sweat-corroded pins.'"
]
}

Output Example (Dataset Item)

{
"item_index": 1,
"input_item": "Cluster #1 (38.4% of 1-star reviews, n=412): Silicone lid gasket warps above 65°C dishwasher cycle, causing 15ml/min leak. Ad Hook: 'Tired of shaker lids leaking in your gym bag after one wash?'",
"live_fetched_title": "Verified Live Signal Context",
"enriched_output": {
"task_class": "TC-09_APIFY_REVIEW_PAIN_MINER",
"signal_category": "HIGH_INTENT_VERIFIED",
"actionable_summary": "Cluster #1 (38.4% of 1-star reviews, n=412): Silicone lid gasket warps above 65°C dishwasher cycle, causing 15ml/min leak. Ad Hook: 'Tired of shaker lids leaking in your gym bag after one wash?'",
"recommended_next_action": "Route directly to CRM / RAG vector index / automated sequence",
"token_efficiency_ratio": 0.84
},
"borz_gate": {
"head_id": "borz-s45-tc-09",
"pred_prob": 0.964,
"passed_local_gate": true,
"inference_ms": 0.012
},
"ppe_event_billed": "apify-default-dataset-item"
}

Quick Integration Guides

1. Python (apify-client)

from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("ultra-liquid/ecom-review-pain-miner").call(run_input={
"items": [
"Cluster #1 (38.4% of 1-star reviews, n=412): Silicone lid gasket warps above 65°C dishwasher cycle, causing 15ml/min leak. Ad Hook: 'Tired of shaker lids leaking in your gym bag after one wash?'",
"Cluster #2 (29.1% of SaaS churn reviews, n=189): Webhook retry queue drops events silently during 502 spikes without DLQ replay. Ad Hook: 'Stop losing Stripe webhooks during traffic spikes—100% replayable DLQ.'",
"Cluster #3 (44.0% of wireless earbud returns, n=620): Copper charging pogo-pins oxidize from sweat after 3 weeks, blocking left-bud charge. Ad Hook: 'Sealed magnetic induction charging—zero sweat-corroded pins.'"
]
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)

2. n8n / Make.com / Clay HTTP Webhook

curl -X POST "https://api.apify.com/v2/acts/ultra-liquid~ecom-review-pain-miner/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"items": [
"Cluster #1 (38.4% of 1-star reviews, n=412): Silicone lid gasket warps above 65°C dishwasher cycle, causing 15ml/min leak. Ad Hook: 'Tired of shaker lids leaking in your gym bag after one wash?'",
"Cluster #2 (29.1% of SaaS churn reviews, n=189): Webhook retry queue drops events silently during 502 spikes without DLQ replay. Ad Hook: 'Stop losing Stripe webhooks during traffic spikes—100% replayable DLQ.'",
"Cluster #3 (44.0% of wireless earbud returns, n=620): Copper charging pogo-pins oxidize from sweat after 3 weeks, blocking left-bud charge. Ad Hook: 'Sealed magnetic induction charging—zero sweat-corroded pins.'"
]
}'