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Traffic Analysis Agent Skill

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.

2k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
836
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/kostja94/marketing-skills --skill traffic-analysis

The instruction itself

16 sections, as written by the author

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

  • Expected direct: Homepage, short URLs, brand pages--likely real direct
  • Unexpected direct: Long URLs, deep pages, product pages--likely dark traffic
  • 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

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

Output Format

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

Copy the folder

Take kostja94/traffic-analysis from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.