SEO & Website Traffic (New)

Overview

SEO & Website Traffic v2 signals reveal which companies are growing or struggling digitally — surfacing both opportunities and pain points across millions of domains.

We pull monthly traffic data, compute month-over-month and 3-month change percentages, and enrich every record with traffic source breakdown, engagement metrics, AI-platform referrals, top organic keywords, and a composite Digital Health Score.

Signals fire when traffic crosses significance thresholds (surges ≥25% MoM, declines ≤−30% MoM, or 3+ consecutive months of directional change). A baseline snapshot is also delivered for every domain so you have a current state record even when no significant change occurred.

What's new in v2

• unique_visitors (estimated) with model tier disclosure
• AI-platform traffic share (ChatGPT, Perplexity, etc.)
• Top organic keywords with volume, CPC, and estimated value
• Composite Digital Health Score (0–100) and 8 categorical health bands
• Country-level rank and category-level rank
• Per-source absolute visit counts (search_visits, direct_visits, etc.)

Available Subtypes

A single domain may produce multiple rows per batch when it qualifies for more than one subtype (e.g. a domain that grew 3 consecutive months and spiked +50% MoM will produce both sustainedGrowth and trafficSurge). Dedupe by company.domain if you want one row per company.

Schema

{
  "signal_id": "e3a67666-d510-4edf-ae0e-56ea740e5993",
  "batch_id": "cf11373a-8c2f-4f10-b9be-756d51bb51a6",
  "signal_type": "website-traffic",
  "signal_subtype": "trafficSurge",
  "signal_name": "Website Traffic",
  "detected_at": "2026-04-27T13:51:46Z",
  "association": "company",
  "company": {
    "name": "Learn R, Python & Data Science Online",
    "domain": "datacamp.com",
    "linkedin_url": "linkedin.com/company/datacampinc",
    "industries": ["science_and_education/science_and_education"],
    "employee_count_low": 201,
    "employee_count_high": 500,
    "description": "Learn data skills 1x faster..."
  },
  "data": {
    "summary": "datacamp.com traffic surged 47% MoM to 8.1M monthly visits.",
    "relevance": 87,
    "traffic": {
      "2026-01-01": 6234155,
      "2026-02-01": 5510887,
      "2026-03-01": 8094470
    },
    "snapshot_date": "2026-03-01T00:00:00+00:00",
    "unique_visitors": 3854509,
    "visits_unique_ratio": 2.10,
    "uv_model": "moderate",
    "search_visits": 4856682,
    "direct_visits": 2185507,
    "referral_visits": 728502,
    "social_visits": 242833,
    "mail_visits": 80946,
    "change_mom_pct": 46.9,
    "change_3mo_pct": 29.8,
    "consecutive_months": 1,
    "trend": "fluctuating",
    "traffic_band": "established",
    "global_rank": 8542,
    "country_rank": 2103,
    "country_rank_country": "US",
    "category": "science_and_education/science_and_education",
    "category_rank": 32,
    "website_title": "Learn R, Python & Data Science Online",
    "website_description": "Learn data skills 1x faster...",
    "small_website": false,
    "traffic_sources": {
      "direct": 0.27, "search": 0.60, "referral": 0.09,
      "social": 0.03, "paid": 0.01, "mail": 0.00
    },
    "engagement": {
      "bounce_rate": 0.48,
      "pages_per_visit": 4.92,
      "avg_visit_duration_seconds": 156
    },
    "top_countries": {
      "US": 0.34, "IN": 0.12, "GB": 0.05, "DE": 0.03, "BR": 0.03
    },
    "top_keywords": [
      { "name": "datacamp", "volume": 165000, "cpc": 4.10, "estimated_value": 8520 },
      { "name": "python tutorial", "volume": 89000, "cpc": 2.30, "estimated_value": 4200 }
    ],
    "ai_traffic": {
      "total_visits": 12340,
      "traffic_share": 0.0015,
      "top_platforms": ["chatgpt", "perplexity"],
      "top_prompts": []
    },
    "search_dependency": "high",
    "search_dependency_detail": "High search dependency at 60% of total traffic.",
    "brand_strength": "strong",
    "brand_keyword_ratio": "3/5",
    "brand_strength_detail": "Strong brand recognition with 27% direct traffic. Brand keyword ratio: 3/5.",
    "engagement_quality": "moderate",
    "engagement_quality_score": 58,
    "engagement_quality_detail": "Moderate engagement (58/100) with 48% bounce rate, 4.9 pages per visit, 156-second average duration.",
    "social_traffic_level": "low",
    "social_traffic_detail": "Low social traffic at 3% of total visits.",
    "referral_strength": "moderate",
    "referral_strength_detail": "Moderate referral strength at 9% of traffic.",
    "ai_traffic_level": "minimal",
    "ai_traffic_detail": "Minimal AI traffic at 0.15% of total visits.",
    "geo_concentration": "diversified",
    "geo_concentration_detail": "Diversified traffic: US (34%), IN (12%), GB (5%).",
    "digital_health_score": 71,
    "digital_health_label": "good",
    "digital_health_detail": "Score 71: Engagement 58/100 (25%), Volume 88/100 (20%), Brand 80/100 (15%), Diversification 72/100 (15%), Rank 75/100 (15%), AI Readiness 15/100 (10%)."
  }
}

Field Reference

Core Fields

Company Object

Data Object — Traffic & Change

Data Object — Unique Visitors (estimated)

unique_visitors is a derived estimate, not measured. The pipeline applies a multiplier to total visits based on engagement signals (bounce rate, pages per visit, session duration). The uv_model field discloses which tier was used so you can interpret the value appropriately.

For change-detection use cases (surge/decline signals) unique_visitors mirrors visits trend and is reliable directionally. Treat the absolute value as a derived estimate.

Data Object — Per-Source Visit Counts

Absolute visits attributed to each source for the snapshot month. Sum equals total monthly visits.

Data Object — Rank & Category

Traffic Sources Object

Breakdown of where a company's website visitors originate. Values are proportions (0–1) summing to approximately 1.0.

Engagement Object

Metrics describing how visitors interact with the website once they arrive.

Top Countries Object

Geographic distribution of website visitors. Keys are ISO 3166-1 alpha-2 country codes, values are proportions (0–1).

Top Keywords Array

Top organic search keywords driving traffic to the domain. Up to 5 entries.

AI Traffic Object

Visits arriving from AI assistants (ChatGPT, Perplexity, Gemini, Claude, etc.) — increasingly important as AI-mediated discovery grows.

Digital Health Score

A composite 0–100 score measuring overall digital presence quality. Computed from 6 components:

• Engagement (25%) — bounce rate, pages per visit, session duration
• Volume (20%) — total monthly traffic
• Brand (15%) — direct traffic share + brand-keyword ratio
• Diversification (15%) — geographic and source diversification
• Rank (15%) — global rank percentile
• AI Readiness (10%) — AI traffic share

Categorical Health Bands

Each band exposes a categorical level, a 0–100 score where applicable, and a human-readable detail string for direct use in messaging.

Example Output

"Noticed DataCamp's traffic surged 47% month-over-month to 8M monthly visits — and their Digital Health Score sits at 71 with strong brand strength and diversified geographic mix. That kind of acceleration paired with high direct traffic typically signals broader growth investment. Would love to share how we're helping similar education platforms capitalize on momentum like this."

Coverage

• Refresh: Monthly
• Coverage: 4M+ companies (CB Insights universe)
• Best for: Marketing agencies, sales intelligence platforms, SEO tools, advertising platforms, analytics vendors, M&A diligence

Data Sourcing Notes

• Traffic, engagement, rank, category, keywords, AI referrals, geo distribution
• Unique visitors — derived estimate (see uv_model)
• Firmographics (LinkedIn URL, employee count, industries) — joined from Autobound's company database
• Health scores and categorical bands — computed by Autobound's pipeline from the raw metrics above

Contact [email protected] to get started.