Salesforce AppExchange Apps & Reviews Extractors

🚀 Salesforce AppExchange Apps & Reviews Extractor Discover Salesforce AppExchange apps and extract structured metadata and public reviews for research, competitive intelligence, and solution discovery. The Salesforce AppExchange Apps & Reviews Extractor is an Apify Actor that discovers apps on Salesforce AppExchange by category, extracts key app information, and optionally collects public user reviews, delivering results in a clean, structured dataset.

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✅ What this Actor does • Discovers Salesforce AppExchange apps by category • Extracts app name, vendor, category, and supported Salesforce clouds • Collects ratings, review counts, and pricing text (when available) • Optionally extracts public user reviews • Outputs structured datasets with a table view • Supports CSV / XLSX exports You control:

1. Sphere (where to explore on AppExchange)
2. Primary categories (e.g. finance, marketing, analytics)
3. How many apps to process
4. Whether to extract reviews (optional)

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👥 Who this Actor is for • Salesforce consultants and ISVs • SaaS founders and product managers • Market researchers and analysts • Data teams building AppExchange intelligence pipelines

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🔍 How discovery works (conceptual) Step 1 — Choose sphere A sphere is a top-level AppExchange navigation area. Currently supported: • business_needs Step 2 — Choose categories Within a sphere, select one or more categories such as: • finance • marketing • analytics • integration • salesforce-labs Step 3 — Apps discovery For each category, the Actor: • loads listing pages • expands results (“Show more” / dynamic loading) • collects and deduplicates app detail URLs Step 4 — App detail extraction For each app listing: • app name and vendor • short description • rating and review count • pricing text (when visible) • supported Salesforce clouds • unique listing_id (used for reviews) Step 5 — Reviews extraction (optional) If enabled, public reviews are extracted per app up to maxReviewsPerApp.

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🧪 Safe default input (recommended) The default input is intentionally conservative to ensure fast and reliable runs (recommended for first use and Store testing): { "mode": "apps", "sphere": "business_needs", "categoryPreset": ["marketing"], "maxPages": 1, "startIndex": 1, "endIndex": 5, "headless": true, "maxReviewsPerApp": 0 } Advanced users can increase categories, pages, and enable reviews as needed.

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🔧 Input reference Required • mode: apps | reviews | apps+reviews • categoryPreset: list of categories within the selected sphere Optional • sphere (default: business_needs) • maxPages — how many listing expansions to attempt per category • startIndex / endIndex — slice which apps to process • maxReviewsPerApp — limit reviews per app (0 = unlimited) • headless — run browser headless • proxySettings — proxies for large-scale runs

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📦 Output Apps dataset One row per AppExchange app, including: • listing_id • sphere • category_preset • primary_category_name • app_name • vendor • short_description • rating, reviews_count • price_text • clouds (array) • app_url • last_seen_at Saved as: • Dataset with table view • Optional APPS.csv, APPS.xlsx Reviews dataset (optional) One row per review, including: • listing_id • rating • review text • reviewer (public) • date Saved as: • Dataset • Optional REVIEWS.csv, REVIEWS.xlsx

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📍 Local results (development) When running locally with APIFY_LOCAL_STORAGE_DIR set: • APPS.csv, APPS.xlsx in project root • REVIEWS.csv, REVIEWS.xlsx (if reviews enabled) • Debug records in: • apify_storage/key_value_stores/default/

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🔐 Compliance & ethics • Collects publicly available information only • No login required • No gated or private data accessed • Users are responsible for compliance with Salesforce terms and local regulations

💰 Pricing & monetization (recommended) Pay-per-event model: • 1 event = 1 dataset item written o each app row → 1 event o each review row → 1 event This makes cost predictable and transparent.

🧯 Troubleshooting “No reviews created” • Ensure listing_id exists in the apps dataset • Run apps+reviews mode “Row skipped: missing listing_id” • Listing ID missing or malformed • Ensure apps extraction completed successfully

Final note This Actor is designed to be safe by default and scalable for advanced users. Start small, validate results, then scale categories, pages, and reviews as needed