Claude Skill

traffic-analysis

When the user wants to analyze website traffic sources, attribution, or dark traffic. Also use when the user mentions "traffic sources," "dark traffic," "direct traffic," "UTM parameters," "traffic attribution," "channel attribution," "attribution optimization," "channel analysis

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Download kostja94-marketing-skills-skills_analytics_sources_traffic-26cef34.zip · 3 KB
Part of kostja94/marketing-skills — 171 skills

Install

skills CLI npx skills add https://github.com/kostja94/marketing-skills/tree/main/skills/analytics/sources/traffic
Claude Code claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install kostja94-marketing-skills@llmmart
Git git clone https://github.com/kostja94/marketing-skills.git

The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole kostja94/marketing-skills collection as a plugin from our marketplace. Git is the plain clone.

Skill manifest

Analytics: Traffic

Guides website traffic analysis across all channels (organic, paid, social, referral, direct). Covers traffic source attribution, dark traffic identification, and multi-channel reporting.

When invoking: On first use, if helpful, open with 1-2 sentences on what this skill covers and why it matters, then provide the main output. On subsequent use or when the user asks to skip, go directly to the main output.

Scope

  • Traffic sources: Organic, paid, social, referral, direct, email
  • Dark traffic: Unattributed visits labeled as "Direct / None"
  • Attribution: UTM tagging, segmenting, reporting accuracy

Branded vs. Non-Branded Traffic (Organic)

Type Characteristics
Branded Higher CTR, conversion, purchase intent; users closer to funnel bottom
Non-branded Touchpoint with future users; most sites get more non-brand traffic; competition fiercer

Brand traffic grows over time as brand awareness increases.

Bot Traffic

A large share of traffic can be bot traffic—RPA, search crawlers, spiders, scrapers. Exclude or segment when evaluating real user behavior; use GA4 filters or segments to isolate human traffic.

Traffic Channels

Channel Typical Sources Attribution
Organic Google, Bing, other search Referrer preserved
Paid (web) Google Ads, Meta Ads, etc. UTM required
Paid (app) App install ads; Google App Campaigns, Apple Search Ads UTM; in-app events
Paid (TV/CTV) Streaming ads; Hulu, Roku, YouTube TV UTM for QR/URL; brand lift
Social Public posts (Facebook, LinkedIn, etc.) Often preserved
Referral External sites, backlinks Referrer preserved
Direct Typed URL, bookmarks No referrer
Email Newsletters, campaigns Often dark without UTM

Dark Traffic

What It Is

Traffic without clear origin--analytics tools default to "Direct" when referrer is missing. Common causes:

  • Private/dark social: WhatsApp, Messenger, Slack, Discord, TikTok shares
  • Email clients: Many strip referrer headers
  • HTTPS->HTTP: Referrer not passed
  • Mobile apps: In-app browsers often omit referrer
  • Ad blockers, privacy tools: Block tracking

Misattribution (Research)

When traffic was sent from known sources, analytics often misattributed:

  • 100% as direct: TikTok, Slack, Discord, WhatsApp, Mastodon
  • 75%: Facebook Messenger
  • 30%: Instagram DMs
  • 14%: LinkedIn public posts
  • 12%: Pinterest

Mitigation

Action Purpose
UTM parameters Tag links in emails, social, campaigns: ?utm_source=X&utm_medium=Y&utm_campaign=Z
Block internal IPs Exclude company visits from reports
Segment direct traffic Split by page type to estimate dark vs. genuine direct

Segmenting Direct Traffic

  1. Expected direct: Homepage, short URLs, brand pages--likely real direct
  2. Unexpected direct: Long URLs, deep pages, product pages--likely dark traffic
  3. Report separately: Use segments in GA4/analytics to avoid overcounting direct

Attribution for Channel Optimization

Ads, growth channels, and medium can be optimized by viewing attribution data. Clean UTM + conversion tracking feeds attribution models; reliable attribution drives budget allocation and channel decisions.

Use Action
Optimize ads Compare paid channels (Google, Meta, LinkedIn) by attributed conversions; reallocate budget to winners
Optimize growth channels Identify which medium (cpc, email, social, referral) drives conversions; scale what works
Multi-touch attribution Requires clean UTM data; inconsistent tagging (e.g., facebook vs Facebook) fragments reports and misattributes

GA4 Default Channel Grouping: Align utm_medium and utm_source with GA4's rules to avoid "Unassigned" traffic. ~30% of campaigns lack proper UTM markup, leading to wasted ad spend; teams standardizing UTM see 29% improvement in attribution accuracy.

Reference: UTM.io – utm_medium, utm_campaign & utm_source Optimization, UTMs for Marketing Attribution

UTM Best Practices

Parameter Use Example
utm_source Origin newsletter, facebook, google
utm_medium Channel type email, cpc, social
utm_campaign Campaign name summer_sale, product_launch
utm_content Variant (optional) banner_a, cta_button
utm_term Paid keyword (optional) running_shoes

GA4 alignment (avoid Unassigned):

Channel utm_medium utm_source
Paid Search cpc google, bing
Paid Social paid-social, cpc facebook, instagram
Email email newsletter, mailchimp
Organic Social social twitter, linkedin
App install cpc, app google, facebook, apple
CTV / Streaming video, ctv hulu, roku, youtube
Display / Banner display, cpc Publisher or network name
Directory ads paid, cpc taaft, shopify, g2, capterra
  • Consistent naming: Lowercase, hyphens; document conventions; never tag internal links (overwrites session attribution)
  • Apply everywhere: Every link in emails, social posts, ads
  • Avoid: Typos, inconsistent values; causes fragmentation

Traffic Diversification

Principle Guideline
Search share Keep organic search below ~75% of total traffic
Health Higher direct + referral share = healthier profile
Brand sites Diversified traffic is common for strong brands
Engagement Content, email, social, free tools drive return visits

See seo-monitoring for full SEO data analysis framework.

Natural Traffic Benchmark

Location: GA4 > Reports > Acquisition > Traffic acquisition

  1. Review organic traffic trend
  2. Record baseline (e.g., monthly total)
  3. Compare periodically to detect growth or decline

Output Format

  • Traffic source breakdown
  • Dark traffic estimate and actions
  • UTM tagging recommendations
  • Segmentation approach for reporting

Related Skills

  • analytics-tracking: Implement UTM, events, conversions; attribution models
  • google-ads, paid-ads-strategy: Paid channels; attribution informs budget allocation
  • ai-traffic-tracking: AI search traffic
  • google-search-console: GSC performance and indexing analysis
  • seo-monitoring: Full SEO data analysis system, benchmark, article database
  • email-marketing: Email strategy; UTM for email links
Files (marketing-skills)
  • SKILL.md 7.3 KB
    ---
    name: traffic-analysis
    description: When the user wants to analyze website traffic sources, attribution, or dark traffic. Also use when the user mentions "traffic sources," "dark traffic," "direct traffic," "UTM parameters," "traffic attribution," "channel attribution," "attribution optimization," "channel analysis," "traffic analysis," "traffic diversification," "natural traffic benchmark," or "organic vs paid traffic." For GA4 setup, use analytics-tracking.
    metadata:
      version: 1.1.1
    ---
    
    # Analytics: Traffic
    
    Guides website traffic analysis across all channels (organic, paid, social, referral, direct). Covers traffic source attribution, dark traffic identification, and multi-channel reporting.
    
    **When invoking**: On **first use**, if helpful, open with 1-2 sentences on what this skill covers and why it matters, then provide the main output. On **subsequent use** or when the user asks to skip, go directly to the main output.
    
    ## Scope
    
    - **Traffic sources**: Organic, paid, social, referral, direct, email
    - **Dark traffic**: Unattributed visits labeled as "Direct / None"
    - **Attribution**: UTM tagging, segmenting, reporting accuracy
    
    ## Branded vs. Non-Branded Traffic (Organic)
    
    | Type | Characteristics |
    |------|-----------------|
    | **Branded** | Higher CTR, conversion, purchase intent; users closer to funnel bottom |
    | **Non-branded** | Touchpoint with future users; most sites get more non-brand traffic; competition fiercer |
    
    Brand traffic grows over time as brand awareness increases.
    
    ## Bot Traffic
    
    A large share of traffic can be **bot traffic**—RPA, search crawlers, spiders, scrapers. Exclude or segment when evaluating real user behavior; use GA4 filters or segments to isolate human traffic.
    
    ## Traffic Channels
    
    | Channel | Typical Sources | Attribution |
    |---------|-----------------|-------------|
    | **Organic** | Google, Bing, other search | Referrer preserved |
    | **Paid (web)** | Google Ads, Meta Ads, etc. | UTM required |
    | **Paid (app)** | App install ads; Google App Campaigns, Apple Search Ads | UTM; in-app events |
    | **Paid (TV/CTV)** | Streaming ads; Hulu, Roku, YouTube TV | UTM for QR/URL; brand lift |
    | **Social** | Public posts (Facebook, LinkedIn, etc.) | Often preserved |
    | **Referral** | External sites, backlinks | Referrer preserved |
    | **Direct** | Typed URL, bookmarks | No referrer |
    | **Email** | Newsletters, campaigns | Often dark without UTM |
    
    ## Dark Traffic
    
    ### What It Is
    
    Traffic without clear origin--analytics tools default to "Direct" when referrer is missing. Common causes:
    
    - **Private/dark social**: WhatsApp, Messenger, Slack, Discord, TikTok shares
    - **Email clients**: Many strip referrer headers
    - **HTTPS->HTTP**: Referrer not passed
    - **Mobile apps**: In-app browsers often omit referrer
    - **Ad blockers, privacy tools**: Block tracking
    
    ### Misattribution (Research)
    
    When traffic was sent from known sources, analytics often misattributed:
    
    - **100% as direct**: TikTok, Slack, Discord, WhatsApp, Mastodon
    - **75%**: Facebook Messenger
    - **30%**: Instagram DMs
    - **14%**: LinkedIn public posts
    - **12%**: Pinterest
    
    ### Mitigation
    
    | Action | Purpose |
    |--------|---------|
    | **UTM parameters** | Tag links in emails, social, campaigns: `?utm_source=X&utm_medium=Y&utm_campaign=Z` |
    | **Block internal IPs** | Exclude company visits from reports |
    | **Segment direct traffic** | Split by page type to estimate dark vs. genuine direct |
    
    ### Segmenting Direct Traffic
    
    1. **Expected direct**: Homepage, short URLs, brand pages--likely real direct
    2. **Unexpected direct**: Long URLs, deep pages, product pages--likely dark traffic
    3. **Report separately**: Use segments in GA4/analytics to avoid overcounting direct
    
    ## Attribution for Channel Optimization
    
    Ads, growth channels, and medium can be optimized by viewing **attribution data**. Clean UTM + conversion tracking feeds attribution models; reliable attribution drives budget allocation and channel decisions.
    
    | Use | Action |
    |-----|--------|
    | **Optimize ads** | Compare paid channels (Google, Meta, LinkedIn) by attributed conversions; reallocate budget to winners |
    | **Optimize growth channels** | Identify which medium (cpc, email, social, referral) drives conversions; scale what works |
    | **Multi-touch attribution** | Requires clean UTM data; inconsistent tagging (e.g., `facebook` vs `Facebook`) fragments reports and misattributes |
    
    **GA4 Default Channel Grouping**: Align `utm_medium` and `utm_source` with [GA4's rules](https://support.google.com/analytics/answer/9756891) to avoid "Unassigned" traffic. ~30% of campaigns lack proper UTM markup, leading to wasted ad spend; teams standardizing UTM see 29% improvement in attribution accuracy.
    
    **Reference**: [UTM.io – utm_medium, utm_campaign & utm_source Optimization](https://web.utm.io/blog/utm_medium-utm_campaign-utm_source/), [UTMs for Marketing Attribution](https://web.utm.io/blog/utms-for-marketing-attribution/)
    
    ## UTM Best Practices
    
    | Parameter | Use | Example |
    |-----------|-----|---------|
    | `utm_source` | Origin | `newsletter`, `facebook`, `google` |
    | `utm_medium` | Channel type | `email`, `cpc`, `social` |
    | `utm_campaign` | Campaign name | `summer_sale`, `product_launch` |
    | `utm_content` | Variant (optional) | `banner_a`, `cta_button` |
    | `utm_term` | Paid keyword (optional) | `running_shoes` |
    
    **GA4 alignment** (avoid Unassigned):
    
    | Channel | utm_medium | utm_source |
    |---------|------------|------------|
    | Paid Search | `cpc` | `google`, `bing` |
    | Paid Social | `paid-social`, `cpc` | `facebook`, `instagram` |
    | Email | `email` | `newsletter`, `mailchimp` |
    | Organic Social | `social` | `twitter`, `linkedin` |
    | App install | `cpc`, `app` | `google`, `facebook`, `apple` |
    | CTV / Streaming | `video`, `ctv` | `hulu`, `roku`, `youtube` |
    | Display / Banner | `display`, `cpc` | Publisher or network name |
    | Directory ads | `paid`, `cpc` | `taaft`, `shopify`, `g2`, `capterra` |
    
    - **Consistent naming**: Lowercase, hyphens; document conventions; never tag internal links (overwrites session attribution)
    - **Apply everywhere**: Every link in emails, social posts, ads
    - **Avoid**: Typos, inconsistent values; causes fragmentation
    
    ## Traffic Diversification
    
    | Principle | Guideline |
    |-----------|-----------|
    | **Search share** | Keep organic search below ~75% of total traffic |
    | **Health** | Higher direct + referral share = healthier profile |
    | **Brand sites** | Diversified traffic is common for strong brands |
    | **Engagement** | Content, email, social, free tools drive return visits |
    
    See **seo-monitoring** for full SEO data analysis framework.
    
    ## Natural Traffic Benchmark
    
    **Location**: GA4 > Reports > Acquisition > Traffic acquisition
    
    1. Review organic traffic trend
    2. Record baseline (e.g., monthly total)
    3. Compare periodically to detect growth or decline
    
    ## Output Format
    
    - **Traffic source** breakdown
    - **Dark traffic** estimate and actions
    - **UTM** tagging recommendations
    - **Segmentation** approach for reporting
    
    ## Related Skills
    
    - **analytics-tracking**: Implement UTM, events, conversions; attribution models
    - **google-ads, paid-ads-strategy**: Paid channels; attribution informs budget allocation
    - **ai-traffic-tracking**: AI search traffic
    - **google-search-console**: GSC performance and indexing analysis
    - **seo-monitoring**: Full SEO data analysis system, benchmark, article database
    - **email-marketing**: Email strategy; UTM for email links
    

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