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apify-market-research

apify-market-research

github.com/apifyMarketing & growth2.5k3.4k installsUpdated 1w ago
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About apify-market-research

A market research skill that guides Apify Actor selection and execution across location, trend, social, and travel data. It is for research workflows that need configurable results and a concise findings summary.

Key features

  1. 01Actor selection by research goal
  2. 02Dynamic Actor schema lookup with mcpc
  3. 03Quick, CSV, or JSON output
  4. 04Results and insight summary

Use cases

  1. 01Assess local business density
  2. 02Research regional trends or consumer groups
  3. 03Compare tourism reviews and hospitality data

MCP support

Uses the mcpc CLI to retrieve an Apify Actor's schema and details before running the selected Actor.

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/apify/agent-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.

Prerequisites

(No need to check it upfront)

  • .env file with APIFY_TOKEN
  • Node.js 20.6+ (for native --env-file support)
  • mcpc CLI tool: npm install -g @apify/mcpc

Workflow

Copy this checklist and track progress:

Task Progress:
- [ ] Step 1: Identify market research type (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] 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

Fetch the Actor's input schema and details dynamically using mcpc:

export $(grep APIFY_TOKEN .env | xargs) && mcpc --json mcp.apify.com --header "Authorization: Bearer $APIFY_TOKEN" tools-call fetch-actor-details actor:="ACTOR_ID" | jq -r ".content"

Replace ACTOR_ID with the selected Actor (e.g., compass/crawler-google-places).

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 - Full export with all fields
    • JSON - Full 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 ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT'

CSV:

node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/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 ${CLAUDE_PLUGIN_ROOT}/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 mcpc not found - Ask user to install npm install -g @apify/mcpc Actor not found - Check Actor ID spelling Run FAILED - Ask user to check Apify console link in error output Timeout - Reduce input size or increase --timeout

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