HubSpot Marketplace Review Intelligence Report
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from $2.89 / 1,000 results
HubSpot Marketplace Review Intelligence Report
Analyze public HubSpot Marketplace reviews and output structured app summary and per-review dataset rows for SaaS competitor intelligence, product feedback, sentiment, topics, and voice-of-customer research.
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from $2.89 / 1,000 results
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Inus Grobler
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Turn public HubSpot App Marketplace reviews into recurring SaaS competitor intelligence, product feedback, sentiment, topic, developer-response, and voice-of-customer dataset rows. This Actor accepts HubSpot app names, search terms, or direct marketplace listing URLs, extracts visible public listing and review data, and returns app summaries, per-review signals, monitoring changes, and multi-app comparisons in an Apify Dataset.
Use it for HubSpot Marketplace review analysis, competitor research, SaaS app positioning, product feedback mining, support issue discovery, pricing objection research, and B2B SaaS voice-of-customer analysis.
What this Actor does
- Finds public HubSpot App Marketplace listings from app names or listing URLs.
- Extracts visible public listing metadata such as app name, rating, review count, installs, categories, and listing URL where available.
- Extracts visible public review details such as rating, date, reviewer, review text, pros/cons, and developer replies where available.
- Classifies reviews into sentiment, topic, business signal, priority, summary, and competitor opportunity.
- Optionally compares reviews with the last fully successful snapshot for a private monitoring key.
- Detects new or changed reviews, developer replies, rating changes, and sentiment changes.
- Produces a cross-app comparison when two or more apps are analyzed.
Snapshot mode is stateless and remains the default. Compare-and-update mode stores only stable review identities, hashes, and aggregate signals in a named key-value store in the caller's Apify account. It does not retain full review text in monitoring state.
How to analyze HubSpot Marketplace reviews
- Open the Actor in Apify Console.
- Enter an exact HubSpot app name or a direct public Marketplace listing URL.
- Add more apps only when you want a comparison report.
- For recurring monitoring, choose Compare and update baseline and reuse a private monitoring key.
- Click Start, then open the Overview, App summaries, Review signals, Monitoring changes, or App comparisons dataset view.
Input
The input is intentionally simple.
{"appInputs": ["CloudTalk"]}
Input fields
| Field | Description |
|---|---|
appInputs | HubSpot app names, search terms, or direct public HubSpot Marketplace listing URLs. |
maxReviewsPerListing | Maximum visible reviews to analyze for each app, from 1 to 500. Default: 10. |
includeOpenRouterAnalysis | Enables optional AI analysis. Default: false; deterministic analysis remains available. |
outputMode | summary_only, summary_and_signals, or raw_reviews. |
monitoringMode | snapshot for an independent run or compare_and_update for recurring change detection. |
monitoringKey | Private key that identifies a monitoring baseline. Required in compare-and-update mode. |
The Actor defaults to analyzing up to 50 visible public reviews per app with deterministic local analysis and returns app summaries plus per-review signals. AI analysis and raw review text are excluded by default.
Recurring monitoring example:
{"appInputs": ["CloudTalk", "Aircall", "JustCall"],"monitoringMode": "compare_and_update","monitoringKey": "calling-apps-weekly"}
The first successful monitored run creates a baseline without labeling existing reviews as new. Later successful runs compare against that baseline. A failed or partial run never replaces a valid baseline, and the Actor does not claim that missing reviews were deleted because marketplace pages can expose capped or incomplete review lists.
Best results come from exact app names or direct listing URLs. Broad search terms are supported, but they may return fewer or less precise matches because the Actor uses public HubSpot Marketplace pages, not a private HubSpot search API.
Examples for appInputs:
["CloudTalk","Zapier","calling software","https://ecosystem.hubspot.com/marketplace/apps/cloudtalk"]
Output
Results are saved to the default Apify Dataset. The Dataset includes focused views for:
Report: the best all-purpose table for quick review.App summaries: one row per app with the executive summary and top signals.Review signals: one row per analyzed review with sentiment, topic, priority, and competitor opportunity.Monitoring changes: one row per app with new reviews, changed reviews, developer replies, rating changes, and sentiment changes.App comparisons: a cross-app view with negative-review share, developer-reply rate, and leading complaint topic.Raw reviews: available only for API users who explicitly request raw review output.Errors: invalid or unresolved inputs.
App summary example
{"itemType": "app_summary","appName": "CloudTalk","listingUrl": "https://ecosystem.hubspot.com/marketplace/apps/cloudtalk","ratingAverage": 4.36,"reviewCount": 106,"categories": ["CALLING"],"reviewsAnalyzed": 50,"topComplaints": [],"topPraise": [{"topic": "VOIP system","count": 8,"priority": "medium","summary": "Customers praise setup, support, and calling workflows."}],"competitorOpportunities": ["Competitors can differentiate with easier setup and stronger customer support."],"executiveSummary": "CloudTalk has positive review sentiment across 50 visible reviews, with praise as the most frequent business signal."}
Review signal example
{"itemType": "review_signal","appName": "CloudTalk","listingUrl": "https://ecosystem.hubspot.com/marketplace/apps/cloudtalk","rating": 5,"reviewDate": "Apr 1, 2026","sentiment": "positive","topic": "VOIP system","businessSignal": "praise","priority": "low","summary": "CloudTalk is praised for easy setup and responsive support.","competitorOpportunity": "Competitors can learn the importance of user-friendly integration and strong customer support.","hasDeveloperReply": false}
Monitoring change example
{"itemType": "change_summary","appName": "CloudTalk","monitoringStatus": "compared","baselineAt": "2026-09-01T08:00:00.000Z","newReviews": 3,"changedReviews": 1,"developerRepliesAdded": 1,"ratingChanges": 0,"sentimentChanges": 1}
Output detail
The standard output includes one app summary row per listing plus per-review intelligence rows. Raw review text is excluded by default to keep the Dataset clean and privacy-conscious.
Advanced API users can still request raw public review fields with outputMode: "raw_reviews", but this is intentionally not exposed in the standard Apify input form.
OpenRouter review analysis
AI analysis is opt-in. When includeOpenRouterAnalysis is enabled and OPENROUTER_API_KEY is configured as an Actor secret or environment variable, the Actor uses OpenRouter to classify each deduplicated review. You can optionally set OPENROUTER_MODEL; otherwise the default model is used.
If OpenRouter is not configured, the Actor still runs and uses a local fallback heuristic based on review rating and keywords.
Only review fields needed for classification are sent for analysis. The Actor does not send unrelated listing metadata or maintain an analysis cache between runs.
Common use cases
- Analyze HubSpot Marketplace reviews for a competitor app.
- Find recurring complaints in SaaS app reviews.
- Identify support, onboarding, pricing, usability, and integration issues.
- Discover competitor positioning opportunities.
- Build a current voice-of-customer report for HubSpot ecosystem apps.
- Compare review sentiment across multiple HubSpot Marketplace listings.
- Monitor new complaints and developer responses across scheduled customer-owned runs.
Public example tasks
Try these ready-to-run examples:
| Task | Input | Best for |
|---|---|---|
| Analyze CloudTalk reviews | { "appInputs": ["CloudTalk"] } | Single-app voice-of-customer analysis |
| Compare HubSpot calling apps | { "appInputs": ["CloudTalk", "Aircall", "JustCall"] } | Competitor review comparison |
| Research integration complaints | { "appInputs": ["Zapier", "PandaDoc", "Typeform"] } | Product and integration feedback mining |
API usage
from apify_client import ApifyClientclient = ApifyClient("YOUR_APIFY_TOKEN")run_input = {"appInputs": ["CloudTalk", "Aircall"],"monitoringMode": "compare_and_update","monitoringKey": "calling-apps-weekly",}run = client.actor("thescrapelab/hubspot-marketplace-review-intelligence-report").call(run_input=run_input)dataset = client.dataset(run["defaultDatasetId"])for item in dataset.iterate_items():print(item)
You can schedule compare-and-update runs in Apify or connect the dataset to webhooks and integrations. Reuse the same monitoring key to compare against the last fully successful snapshot.
Compliance and privacy
This Actor scrapes only public HubSpot App Marketplace pages supplied or resolved from the user's current input. It does not log in, does not use OAuth, does not use HubSpot private APIs, does not bypass CAPTCHAs, does not bypass access controls, and is not an official HubSpot integration.
The Actor uses the default Apify Dataset for current-run output. Compare-and-update mode uses a named key-value store in the caller's account containing only stable identities, hashes, and aggregate signals. Full review text is never written to monitoring state.
Limitations
- The current version supports HubSpot App Marketplace listings only.
- It extracts visible public listing and review data available during the run.
- It does not guarantee complete historical review extraction if older reviews are hidden behind dynamic loading.
- It does not use HubSpot private APIs.
- It does not log in to HubSpot.
- Change detection requires compare-and-update mode and a reused monitoring key.
- It does not infer deletions from missing reviews because public listings may return incomplete or capped review sets.
- Other marketplaces are not supported by the current version.
Pricing and cost notes
- Small examples with one app are the cheapest way to verify output quality.
- Multi-app comparison runs increase runtime because each app listing and visible review set must be fetched and analyzed.
- Direct listing URLs are usually more efficient than broad search terms because they skip marketplace search resolution.
- Raw review output is intended for API users who explicitly need it; the standard report keeps the dataset cleaner and smaller.
Troubleshooting
- If an app name returns no result, use the exact HubSpot Marketplace app name or paste the direct listing URL.
- If a broad search term resolves the wrong app, replace it with a direct listing URL.
- If review rows are fewer than expected, the public listing may expose only a limited set of visible reviews during the run.
- If AI review analysis is unavailable, the Actor still returns heuristic sentiment and topic signals.
- If a listing is temporarily blocked or unavailable, rerun later or narrow the input to fewer apps.