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apify-market-research

apify-market-research

github.com/sickn33Marketing & growth48.9k111 installsUpdated today
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About apify-market-research

A workflow for gathering market research data from maps, social platforms, trend sources, and travel services using Apify Actors. It guides schema checks, output selection, analysis runs, and synthesis of findings.

Key features

  1. 01Select Apify Actors by research goal
  2. 02Inspect Actor input schemas
  3. 03Export results as CSV or JSON
  4. 04Summarize findings and next steps
  5. 05Confirm scope and result limits before runs

Use cases

  1. 01Analyze regional interest or business density
  2. 02Research product pricing and consumer demand
  3. 03Summarize travel accommodation reviews
  4. 04Collect social platform hashtag and activity data

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/sickn33/agentic-awesome-skills --skill apify-market-research

After installing, type/apify-market-researchin Claude Code to confirm it loaded.

Bundled filesreference/scripts/run_actor.js

Details

From the project README

Market Research

Conduct market research using Apify Actors to extract data from multiple platforms.

When to Use

  • You need market sizing, regional demand, pricing, trend, or consumer behavior data.
  • The task is to gather research inputs from maps, travel, Facebook, Instagram, or trend sources with Apify.
  • You need structured market data plus a synthesized view of opportunities or risks.

Prerequisites

Verify prerequisites before any paid run.

  • .env file with APIFY_TOKEN
  • Node.js 20.6+ (for native --env-file support)
  • An approved Apify connector or Console access to inspect the chosen Actor and its schema; the bundled runner uses REST directly.
  • Keep .env untracked and private; configure the token locally without pasting it into chat or command arguments.

Workflow

Copy this checklist and track progress:

Task Progress:
- [ ] Step 1: Identify market research type (select Actor)
- [ ] Step 2: Fetch Actor schema via an approved connector or Console
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the analysis script
- [ ] Step 5: Summarize findings
Step 1: Identify Market Research Type

Select the appropriate Actor based on research needs:

User NeedActor IDBest For
Market densitycompass/crawler-google-placesLocation analysis
Geospatial analysiscompass/google-maps-extractorBusiness mapping
Regional interestapify/google-trends-scraperTrend data
Pricing and demandapify/facebook-marketplace-scraperMarket pricing
Event marketapify/facebook-events-scraperEvent analysis
Consumer needsapify/facebook-groups-scraperGroup research
Market landscapeapify/facebook-pages-scraperBusiness pages
Business densityapify/facebook-page-contact-informationContact data
Cultural insightsapify/facebook-photos-scraperVisual research
Niche targetingapify/instagram-hashtag-scraperHashtag research
Hashtag statsapify/instagram-hashtag-statsMarket sizing
Market activityapify/instagram-reel-scraperActivity analysis
Market intelligenceapify/instagram-scraperFull data
Product launch researchapify/instagram-api-scraperAPI access
Hospitality marketvoyager/booking-scraperHotel data
Tourism insightsmaxcopell/tripadvisor-reviewsReview analysis
Step 2: Fetch Actor Schema

Inspect the current Actor details and input schema using the authenticated Apify connector available in the session, or its Console page. Discover actual tool names and parameters before calling them. Do not parse .env with shell substitution or pass a token as a CLI header argument. Treat the Actor table as discovery candidates, not verified availability or schemas.

This returns:

  • Actor description and README
  • Required and optional input parameters
  • Output fields (if available)
Step 3: Ask User Preferences

Before running, ask:

  1. Output format:
    • Quick answer - Display top few results in chat (no file saved)
    • CSV - Bounded export, union of returned fields
    • JSON - Bounded export in JSON format
  2. Number of results: Based on character of use case
Step 4: Run the Script

Quick answer (display in chat, no file):

node --env-file=.env "<resolved-skill-directory>/reference/scripts/run_actor.js" \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT'

CSV:

node --env-file=.env "<resolved-skill-directory>/reference/scripts/run_actor.js" \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT' \
  --output YYYY-MM-DD_OUTPUT_FILE.csv \
  --format csv

JSON:

node --env-file=.env "<resolved-skill-directory>/reference/scripts/run_actor.js" \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT' \
  --output YYYY-MM-DD_OUTPUT_FILE.json \
  --format json
Step 5: Summarize Findings

After completion, report:

  • Number of results found
  • File location and name
  • Key market insights
  • Suggested next steps (deeper analysis, validation)

Error Handling

APIFY_TOKEN not found - Ask user to create .env with APIFY_TOKEN=your_token Connector unavailable - Inspect the schema through the Console; do not claim an unavailable tool was called. Actor not found - Check Actor ID spelling Run FAILED - Ask user to check Apify console link in error output Timeout - The local timeout does not abort the remote run. Inspect the printed run ID in Console before retrying to avoid duplicate charges.

Run Boundaries

Before launch, confirm the selected Actor, authorized public-data scope, current input schema, result limits and pricing with the user’s request. Respect source terms and access controls; do not collect private group data or unnecessary personal contact information. Start with a small Actor-supported input limit. --max-items limits downloaded output only (default 1000); it does not cap Actor work or billing. The helper sends a skill-identifying User-Agent to Apify. Resolve the installed skill directory in the command placeholders. Output files must be new paths; exports preserve long values and heterogeneous fields. Quick answers fetch at most five records; minimize or redact personal fields before sharing.

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

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