{
    "_source": {
        "name": "Tyler Willis Intelligence",
        "url": "https://tylerewillis.com/intelligence/benchmarks/logistics-small-global",
        "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. \"Logistics and Transportation Firms · Small.\" tylerewillis.com/intelligence. Accessed 2026-07-02. https://tylerewillis.com/intelligence/benchmarks/logistics-small-global",
        "docs": "https://tylerewillis.com/intelligence/api"
    },
    "slug": "logistics-small-global",
    "segment_name": "Logistics and Transportation Firms · Small",
    "industry": "Logistics",
    "company_size_segment": "small",
    "employee_count_range": null,
    "revenue_range": null,
    "geographic_market": "Global",
    "business_model": null,
    "maturity_stage": "growth",
    "automation_maturity": "intermediate",
    "pct_using_any_automation": "68.00",
    "pct_using_ai_tools": "57.00",
    "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": "72.00",
    "automation_budget_range": "EUR 30K-150K",
    "top_automation_tools_used": [
        "AI-directed picking",
        "Computer vision sorting",
        "Route optimization",
        "Predictive fleet maintenance",
        "Last-mile optimization",
        "Driver behavior analytics",
        "Demand sensing",
        "Customs automation",
        "Risk monitoring",
        "Emissions optimization"
    ],
    "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": "250.00",
    "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": "High upfront costs and workforce skill gaps",
    "top_pain_points": [
        "High upfront automation costs",
        "Workforce skill gaps",
        "Manual data entry inefficiencies",
        "Meeting next-day delivery demands"
    ],
    "top_growth_levers": [
        "Adoption of robotics and AI-powered systems",
        "Integration of automation with ERP systems",
        "Use of RaaS subscription models",
        "Transport management automation"
    ],
    "benchmark_index_score": "65.00",
    "automation_opportunity_gap": "45.00",
    "predicted_growth_rate": "15.73",
    "ai_insights_summary": "Top performers in small logistics firms leverage AI-driven warehouse and transport automation to achieve ROI of 200-350% over three years, significantly reducing costs and improving delivery times. Adoption of robotics-as-a-service and integration with ERP systems are key differentiators enabling scalability and operational efficiency.",
    "data_collection_date": "2026-06-13",
    "data_collection_method": "Secondary research from industry reports and market analyses",
    "source_url": null,
    "source_credibility": "secondary",
    "sample_size": null,
    "geographic_scope": "Global",
    "statistical_confidence": "0.70",
    "outlier_flag": 0,
    "created_at": "2026-06-13 03:30:14",
    "updated_at": "2026-06-16 05:30:40",
    "uuid": "a63bf48c-670e-11f1-b71e-525400d81b6e"
}