SaaS Voice-of-Customer Battlecard

Convert customer-review datasets into traceable product and competitive intelligence. The Actor accepts reviews directly or reads another Apify Actor's dataset; it does not scrape review sites itself and ignores reviewer identities.

Outputs

Structured theme rows contain:

• theme and category
• frequency and severity
• sentiment and date-aware trend
• evidence count and short representative evidence
• explicit competitor mentions

The final battlecard row groups the strongest findings into strengths, weaknesses, common complaints, missing features, switching reasons, competitive opportunities, and product opportunities.

Why deterministic first

The Actor uses transparent phrase dictionaries, ratings, dates, and user-supplied custom themes. It does not send review text to an LLM, so there is no model/API key requirement, no invented quote, and no uncontrolled token bill. Evidence excerpts come from the supplied review text and remain short.

Input notes

Provide reviews (array of objects; text can be in text, review, content, body, comment, or pros/cons) or a datasetId from another Actor (for example a G2, Capterra or Trustpilot scraper). Records without usable text and duplicate texts are skipped with a warning and are not charged. Ratings outside 0-5 are ignored. The prefilled reviews on the Store page are demo text only.

Quick start

{
  "productName": "Acme Cloud",
  "reviews": [
    { "text": "Easy to use, but reports are slow and sometimes crash.", "rating": 3, "date": "2026-07-01" },
    { "text": "Please add a native Salesforce integration.", "rating": 3, "date": "2026-08-01" }
  ],
  "competitorNames": ["RivalCo"]
}

Pricing

The intended model is low-cost pay per review analyzed, with platform usage included. Theme rows and the battlecard are included. Current exact prices appear on the Store page. If a maximum run charge stops processing, the battlecard is marked partial.

Limitations

Keyword analysis is explainable but cannot understand every idiom, language, sarcasm, or implicit product comparison. Trend requires enough dated reviews and reports unknown on small samples. Frequency reflects the supplied sample, not the entire customer base. Do not use the output to profile individuals or make automated high-impact decisions.

FAQ

Does it scrape the data itself? No. It analyzes records you supply (pasted JSON or another Apify dataset), so you stay in control of where the data comes from. Pair it with a collector Actor or your own export.

Do I need an OpenAI or other AI key? No. Themes, severity and trends come from deterministic rules, so results are repeatable and every theme links back to the reviews behind it.

How much does it cost? $0.50 per 1,000 analyzed reviews plus $0.01 per run. The Pricing tab is authoritative.

Can I run it through the API or on a schedule? Yes. Save your input as a task, schedule it in Apify Console, or call it from the Apify API. Results export as JSON, CSV or Excel and connect to Google Sheets, Slack, Make, Zapier or a webhook.

Related Actors

• Customer Review Complaint Analyzer
• App Release Review Analyzer
• Dataset Cleaner & Deduplicator