SaaS Review Gap Battlecard Scorer

Turn imported SaaS review rows into evidence-backed competitor weakness, positioning, roadmap, and sales battlecard signals.

What it does

This Actor reads review rows you already have from sources like G2, Capterra, Trustpilot, Chrome Web Store, App Store, Shopify App Store, spreadsheets, CRM notes, or manual research. It does not scrape those sites.

For each deduped review row, it produces:

• normalized source, competitor, rating, review URL, and review date;
• deterministic sentiment band;
• complaint themes and praise themes;
• buyer-language snippets and evidence snippets;
• competitor weakness score and level;
• sales battlecard angle;
• positioning hook;
• roadmap signal;
• content or enablement idea;
• warnings and risk flags for unsupported interpretation.

Input

This MVP supports items mode only.

Required:

• items: non-empty array of SaaS review-like row objects.

Optional:

• yourProduct: product, service, or offer profile for positioning hooks.
• targetCompetitors: competitor names to prioritize.
• targetSegments: buyer roles or ICP terms for talk tracks.
• themeKeywords: custom complaint themes to detect.
• maxItems: maximum rows to process. Default: 500.
• scrapedAt: reference timestamp for deterministic metadata.

Common row fields:

• competitorName, productName, appName, companyName
• source, reviewSource, platform, site
• rating, stars, score
• reviewTitle, title, headline
• reviewText, text, body, description, summary
• pros, cons
• date, reviewDate, publishedAt, postedAt
• reviewUrl, url, sourceUrl
• role, jobTitle, companySize, segment

Example input:

{
  "items": [
    {
      "competitorName": "Acme CRM",
      "source": "G2",
      "rating": 2,
      "reviewTitle": "Powerful automations, painful onboarding",
      "reviewText": "The workflow builder is flexible, but onboarding took weeks. Our RevOps team struggled with integrations and reporting exports.",
      "cons": "Onboarding, integrations, reporting, and support were painful.",
      "reviewUrl": "https://reviews.example/g2/acme-crm/onboarding-gap"
    }
  ],
  "yourProduct": "Lightweight CRM automation platform for SaaS teams",
  "targetCompetitors": ["Acme CRM"],
  "targetSegments": ["RevOps", "SaaS founders"]
}

Output

The Actor pushes one dataset item per deduped review evidence row. The default dataset is documented by .actor/dataset_schema.json for the Store/API output tab.

Key output fields:

• competitorName
• source
• rating
• sentimentBand
• complaintThemes
• praiseThemes
• buyerLanguage
• evidenceSnippets
• competitorWeaknessScore
• weaknessLevel
• salesBattlecardAngle
• positioningHook
• roadmapSignal
• contentIdea
• riskFlags
• warnings

Scoring

The weakness score is deterministic. It increases when imported review evidence contains low ratings, negative language, complaint themes, and usable evidence snippets. A high score means the row may be useful as a competitor weakness signal; it does not prove churn, budget, account intent, market share, or legal truth.

MVP limitations

• It does not scrape review sites.
• It does not call G2, Capterra, Trustpilot, app stores, or other external websites.
• It does not bypass logins, paywalls, or robots rules.
• It does not use AI/LLM.
• It does not claim that one review proves competitor weakness by itself.
• It does not guarantee sales outcomes, buyer intent, churn, legal compliance, or factual completeness.
• It supports deterministic top-level row fields only in this version.

Running it

In Apify Console, start with the prefilled input in Apify Console or paste your own review rows using the example input shape above. The prefilled sample produces a non-empty dataset for Store QA.

For local source checkout verification:

npm install
npm test
apify validate-schema

To run locally without Apify storage, save input as input.json and run:

$node src/main.js --input input.json --output output.json