{
    "_source": {
        "name": "Tyler Willis Intelligence",
        "url": "https://tylerewillis.com/intelligence/benchmarks/real-estate-mid-us",
        "author": "Tyler Willis",
        "publisher": "tylerewillis.com",
        "license": "CC-BY-4.0",
        "license_url": "https://creativecommons.org/licenses/by/4.0/",
        "attribution_required": "Include source URL or citation string when redistributing, quoting, or embedding in AI responses.",
        "citation": "Tyler Willis. \"Real Estate Agencies · Mid (101-500) · US.\" tylerewillis.com/intelligence. Accessed 2026-06-12. https://tylerewillis.com/intelligence/benchmarks/real-estate-mid-us",
        "docs": "https://tylerewillis.com/intelligence/api"
    },
    "slug": "real-estate-mid-us",
    "segment_name": "Real Estate Agencies · Mid (101-500) · US",
    "industry": "Real Estate",
    "company_size_segment": "mid",
    "employee_count_range": "101-500",
    "revenue_range": null,
    "geographic_market": "US",
    "business_model": "service",
    "maturity_stage": "established",
    "automation_maturity": "intermediate",
    "pct_using_any_automation": "50.00",
    "pct_using_ai_tools": "5.00",
    "pct_using_workflow_automation": null,
    "pct_using_ai_for_content": null,
    "pct_using_ai_for_reporting": null,
    "pct_using_ai_for_outreach": null,
    "pct_using_ai_for_client_service": null,
    "pct_planning_automation_investment": null,
    "automation_budget_range": "thousands to tens of thousands USD monthly",
    "top_automation_tools_used": [
        "Snappt",
        "RentGrow",
        "Yardi ScreeningWorks Pro",
        "Realm-X",
        "Juniper Square"
    ],
    "avg_tools_in_stack": null,
    "avg_hours_per_week_manual_tasks": null,
    "pct_time_on_automatable_tasks": null,
    "hours_saved_per_week_from_automation": null,
    "tasks_automated_count": null,
    "reporting_time_hours_per_week": null,
    "onboarding_time_hours": null,
    "client_communication_hours_per_week": null,
    "avg_revenue_per_employee": null,
    "avg_client_count": null,
    "avg_client_ltv": null,
    "avg_monthly_retainer": null,
    "avg_profit_margin_pct": null,
    "automation_roi_reported": "708.00",
    "churn_rate_monthly": null,
    "cac": null,
    "avg_client_acquisition_channels": null,
    "pct_referral_driven": null,
    "avg_proposal_conversion_rate": null,
    "avg_sales_cycle_days": null,
    "primary_bottleneck": "manual administrative tasks and screening",
    "top_pain_points": [
        "application fraud",
        "manual screening time",
        "high operational costs",
        "digital fraud risks"
    ],
    "top_growth_levers": [
        "AI-driven screening and fraud prevention",
        "workflow automation",
        "predictive analytics for lead conversion",
        "data-backed engagement tools"
    ],
    "benchmark_index_score": "65.00",
    "automation_opportunity_gap": "80.00",
    "predicted_growth_rate": "13.00",
    "ai_insights_summary": "Top performers in mid-sized US real estate agencies leverage AI tools to reduce screening time by up to 95%, dramatically improve accuracy, and achieve ROI exceeding 700%. Early adopters gain competitive advantages through automation of administrative tasks and predictive client targeting, enabling more time for negotiation and client interaction.",
    "data_collection_date": "2026-05-29",
    "data_collection_method": "secondary research from industry reports and market analyses",
    "source_url": null,
    "source_credibility": "secondary",
    "sample_size": null,
    "geographic_scope": "US",
    "statistical_confidence": "0.70",
    "outlier_flag": 0,
    "created_at": "2026-05-29 03:30:12",
    "updated_at": "2026-06-11 05:31:10",
    "uuid": "29cc9691-5b45-11f1-8d34-525400d81b6e"
}