Instagram Users Extractor (Rich Metadata) ## Overview This actor performs a deep extraction of Instagram user profile data, delivering structured metadata with high fidelity for analytical and lead generation workflows. The extractor captures comprehensive account metrics, engagement statistics, and business contact information while maintaining data integrity through timestamped snapshots and unique identifiers. Designed for reliability, this tool provides consistent schema output suitable for CRM integration, data warehousing, and downstream analytical processing. ## Data Dictionary | Field Name | Data Type | Definition | |------------|-----------|------------| | search_id | String | Unique identifier for the search operation | | query_timestamp | String (ISO 8601) | UTC timestamp indicating when the search was executed | | results.user_id | String | Instagram's internal numeric identifier for the user account | | results.username | String | The account's unique handle (without @ symbol) | | results.display_name | String | Public-facing name displayed on the profile | | results.external_id | String | Composite identifier combining platform prefix, user ID, and extraction timestamp | | results.is_verified | Boolean | Indicates whether the account has official verification status (blue checkmark) | | results.is_private | Boolean | Indicates whether the account requires follow approval to view content | | results.language_code | String (ISO 639-1) | Two-letter language code representing the account's primary language | | results.follower_count | Integer | Total number of accounts following this user | | results.following_count | Integer | Total number of accounts this user follows | | results.post_count | Integer | Total number of posts published by this account | | results.engagement_metrics.avg_likes | Integer | Mean number of likes across recent posts | | results.engagement_metrics.avg_comments | Integer | Mean number of comments across recent posts | | results.engagement_metrics.engagement_rate | Float | Calculated engagement percentage relative to follower base | | results.engagement_metrics.reach_score | Float | Normalized score (0-10) indicating content reach effectiveness | | results.profile_metadata.category | String | Business or content category classification | | results.profile_metadata.business_email | String | Publicly listed contact email address (if available) | | results.profile_metadata.website | String (URL) | External website link from profile bio | | results.profile_metadata.location.city | String | Geographic city identifier from profile location | | results.profile_metadata.location.country_code | String (ISO 3166-1) | Two-letter country code | | results.profile_metadata.location.timezone | String (IANA) | IANA timezone identifier for the location | | results.content_analysis.primary_topics | Array[String] | Extracted keywords representing main content themes | | results.content_analysis.sentiment_score | Float | Sentiment polarity score ranging from -1 (negative) to 1 (positive) | | results.content_analysis.account_quality_score | Integer | Composite quality metric (0-100) based on authenticity signals | | results.scraped_at | String (ISO 8601) | UTC timestamp of data extraction completion | ## Sample Dataset Below is a sample of the high-fidelity JSON output: json { "search_id": "usr_789456123", "query_timestamp": "2025-12-19T08:15:22Z", "results": { "user_id": "245789123456", "username": "tech_innovator", "display_name": "Tech Innovator", "external_id": "ig_usr_245789123456_2025121908", "is_verified": true, "is_private": false, "language_code": "en", "follower_count": 156789, "following_count": 892, "post_count": 1243, "engagement_metrics": { "avg_likes": 12456, "avg_comments": 342, "engagement_rate": 7.94, "reach_score": 8.2 }, "profile_metadata": { "category": "Technology & Innovation", "business_email": "contact@techinnovator.com", "website": "https://techinnovator.com", "location": { "city": "San Francisco", "country_code": "US", "timezone": "America/Los_Angeles" } }, "content_analysis": { "primary_topics": ["tech", "startup", "innovation"], "sentiment_score": 0.87, "account_quality_score": 92 }, "scraped_at": "2025-12-19T08:15:22Z" } } ## Configuration Parameters To ensure optimal data depth, configure the following: | Parameter | Field Name | Data Type | Example Value | Description | |-----------|------------|-----------|---------------|-------------| | Search Query | query | String | "trending" | Keyword or search term used to discover Instagram user accounts matching specified criteria | ## Analytical Use Cases Researchers and data scientists can leverage this structured dataset for multiple analytical workflows: - Lead Scoring & Qualification: Utilize engagement_rate, account_quality_score, and follower_count to build predictive models for B2B prospect prioritization - Sentiment Analysis: Apply NLP techniques to sentiment_score and primary_topics for brand perception studies and competitive intelligence - Network Mapping: Construct social graphs using following_count and follower_count ratios to identify influencer hierarchies and community structures - Longitudinal Studies: Track temporal changes in engagement metrics and follower growth by comparing query_timestamp snapshots across multiple extraction runs - Geographic Segmentation: Aggregate profiles by location.country_code and timezone for regional market analysis and localization strategies - Content Strategy Optimization: Correlate primary_topics with engagement_metrics to identify high-performing content themes ## Technical Limitations Important Considerations: - Rate Limiting: Extraction throughput is subject to platform-imposed rate limits; sustained high-volume operations may require request throttling or distributed execution - Data Freshness: Metrics such as follower_count and engagement_metrics represent point-in-time snapshots and may lag real-time values by several minutes - Private Accounts: Profiles with is_private: true return limited metadata; full engagement metrics and content analysis require authenticated access - Email Availability: The business_email field is populated only when publicly disclosed in the profile; absence does not indicate lack of business status - Engagement Calculations: Average metrics are computed from the most recent 12-50 posts depending on account activity; accounts with fewer posts may show statistical variance - Data Retention: Extracted datasets should be refreshed periodically as Instagram profiles are dynamic; stale data older than 30 days may not reflect current account status ## Keywords & Tags This specification covers: instagram scraper, instagram user search, instagram search users tool, export instagram followers, instagram profile data extractor, instagram lead generation, instagram data extraction, instagram account discovery