Review Pain Intelligence

Convert product-review datasets into a ranked map of recurring customer pain. This Actor groups complaint topics by product, measures frequency and negative sentiment signals, compares adjacent time windows, and attaches source excerpts so every finding can be verified.

Use it for product discovery, roadmap prioritization, competitive research, voice-of-customer analysis, and sales messaging. The deterministic engine supports common English and Russian complaint language and needs no LLM key.

What this Actor does

• Detects recurring complaint topics across products.
• Ranks pain clusters by mentions, negative share, rating, and recent trend.
• Returns matched keywords and source evidence instead of fabricated summaries.
• Suggests a concrete validation next step for each pain cluster.
• Accepts up to 100,000 reviews and returns up to 500 ranked clusters.
• Runs with limited Apify permissions and a fixed 256 MB memory ceiling.

This Actor analyzes existing review records. It does not scrape review sites itself. Use inline records, select an Apify dataset, or connect a compatible limited-permission upstream Actor.

How to use Review Pain Intelligence

1. Choose records, datasetId, or sourceActorId as the source.
2. Provide review text and preferably product, rating, date, and source URL.
3. Set lookbackDays to define the recent trend window.
4. Set minMentions to control how much repetition a pain needs.
5. Set maxEvidencePerPain and maxResults.
6. Run the Actor and inspect the ranked clusters in the default dataset.

Output

One dataset item represents one product/topic pain cluster. It includes the product, topic, pain score, mention count, negative share, average rating, recent and previous mentions, growth rate, matched keywords, evidence excerpts, and a recommended validation action.

The OUTPUT record summarizes source volume and emitted clusters. Results are available through the Apify API and can be exported as JSON, CSV, Excel, XML, or RSS, scheduled, or connected to integrations and webhooks.

Pricing

This Actor uses transparent pay-per-event pricing:

• $0.002 per analysis run
• $0.005 per emitted pain cluster

Examples: 10 pain clusters cost $0.052; 100 clusters cost $0.502. Runs with fewer qualified clusters cost less. This Actor's platform usage is included; an optional paid upstream Actor has its own separate charges.

At 256 MB, bounded cloud benchmarks processed 25,000 inline reviews in about 6.6 seconds. The highest measured run cost across review scenarios was approximately $0.000312, leaving a substantial safety margin.

Other Signal Lab Actors

• Hiring Signal Intelligence ranks companies showing concentrated hiring activity.
• Marketplace Deal Alerts finds underpriced listings and price drops.

FAQ

Does the Actor use an LLM?

No. The launch version uses explainable multilingual keyword topics and rating/negative-language rules. This avoids hallucinated themes and unpredictable API costs.

What languages are supported?

The built-in topic dictionary focuses on common English and Russian complaint language. Other languages may still contribute through ratings, but topic coverage will be limited.

Why did I receive no clusters?

Check that review text is present, reduce minMentions, widen the date window, and confirm date fields use recognizable timestamps.

Can it analyze a private dataset?

Yes. Select it in the dataset picker. The Actor receives read-only access to that dataset and otherwise remains limited-permission.

Privacy and support

Do not submit secrets, payment data, health information, or unnecessary personal identifiers in review text. For support, open the Actor's Issues tab with a run ID and a small redacted sample.

Free product guide

See the Review Pain Intelligence workflow, use cases, and expected output, or browse all Signal Lab data tools.