Website Traffic Analyzer

Traffic analysis

by kostja94 · MIT license · ★ 1,006 on GitHub

Traffic analysis cover

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,"…

---
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

Overview

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

What you get

  • Traffic sourcebreakdown
  • Dark trafficestimate and actions
  • UTMtagging recommendations
  • Segmentationapproach for reporting
Manual install (npx, ZIP)
Claude Codenpx skills add kostja94/marketing-skills --skill traffic-analysis -g -a claude-code
Claude Code (degit)npx degit kostja94/marketing-skills/skills/analytics/sources/traffic#main ~/.claude/skills/traffic-analysis
Claude.ai / desktopZip the folder and upload it under Settings → Capabilities → Skills.
Codex, Cursor, other agentsPoint them at SKILL.md. The other files are plain text.

Connects with Agent Alley MCP · agentalley.io/mcp

Files included

  • SKILL.md7.3 KB
Read SKILL.md here
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SKILL.md
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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
  • 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
1---
2name: traffic-analysis
3description: 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.
4metadata:
5 version: 1.1.1
6---
7 
8# Analytics: Traffic
9 
10Guides website traffic analysis across all channels (organic, paid, social, referral, direct). Covers traffic source attribution, dark traffic identification, and multi-channel reporting.
11 
12**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.
13 
14## Scope
15 
16- **Traffic sources**: Organic, paid, social, referral, direct, email
17- **Dark traffic**: Unattributed visits labeled as "Direct / None"
18- **Attribution**: UTM tagging, segmenting, reporting accuracy
19 
20## Branded vs. Non-Branded Traffic (Organic)
21 
22| Type | Characteristics |
23|------|-----------------|
24| **Branded** | Higher CTR, conversion, purchase intent; users closer to funnel bottom |
25| **Non-branded** | Touchpoint with future users; most sites get more non-brand traffic; competition fiercer |
26 
27Brand traffic grows over time as brand awareness increases.
28 
29## Bot Traffic
30 
31A 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.
32 
33## Traffic Channels
34 
35| Channel | Typical Sources | Attribution |
36|---------|-----------------|-------------|
37| **Organic** | Google, Bing, other search | Referrer preserved |
38| **Paid (web)** | Google Ads, Meta Ads, etc. | UTM required |
39| **Paid (app)** | App install ads; Google App Campaigns, Apple Search Ads | UTM; in-app events |
40| **Paid (TV/CTV)** | Streaming ads; Hulu, Roku, YouTube TV | UTM for QR/URL; brand lift |
41| **Social** | Public posts (Facebook, LinkedIn, etc.) | Often preserved |
42| **Referral** | External sites, backlinks | Referrer preserved |
43| **Direct** | Typed URL, bookmarks | No referrer |
44| **Email** | Newsletters, campaigns | Often dark without UTM |
45 
46## Dark Traffic
47 
48### What It Is
49 
50Traffic without clear origin--analytics tools default to "Direct" when referrer is missing. Common causes:
51 
52- **Private/dark social**: WhatsApp, Messenger, Slack, Discord, TikTok shares
53- **Email clients**: Many strip referrer headers
54- **HTTPS->HTTP**: Referrer not passed
55- **Mobile apps**: In-app browsers often omit referrer
56- **Ad blockers, privacy tools**: Block tracking
57 
58### Misattribution (Research)
59 
60When traffic was sent from known sources, analytics often misattributed:
61 
62- **100% as direct**: TikTok, Slack, Discord, WhatsApp, Mastodon
63- **75%**: Facebook Messenger
64- **30%**: Instagram DMs
65- **14%**: LinkedIn public posts
66- **12%**: Pinterest
67 
68### Mitigation
69 
70| Action | Purpose |
71|--------|---------|
72| **UTM parameters** | Tag links in emails, social, campaigns: `?utm_source=X&utm_medium=Y&utm_campaign=Z` |
73| **Block internal IPs** | Exclude company visits from reports |
74| **Segment direct traffic** | Split by page type to estimate dark vs. genuine direct |
75 
76### Segmenting Direct Traffic
77 
781. **Expected direct**: Homepage, short URLs, brand pages--likely real direct
792. **Unexpected direct**: Long URLs, deep pages, product pages--likely dark traffic
803. **Report separately**: Use segments in GA4/analytics to avoid overcounting direct
81 
82## Attribution for Channel Optimization
83 
84Ads, 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.
85 
86| Use | Action |
87|-----|--------|
88| **Optimize ads** | Compare paid channels (Google, Meta, LinkedIn) by attributed conversions; reallocate budget to winners |
89| **Optimize growth channels** | Identify which medium (cpc, email, social, referral) drives conversions; scale what works |
90| **Multi-touch attribution** | Requires clean UTM data; inconsistent tagging (e.g., `facebook` vs `Facebook`) fragments reports and misattributes |
91 
92**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.
93 
94**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/)
95 
96## UTM Best Practices
97 
98| Parameter | Use | Example |
99|-----------|-----|---------|
100| `utm_source` | Origin | `newsletter`, `facebook`, `google` |
101| `utm_medium` | Channel type | `email`, `cpc`, `social` |
102| `utm_campaign` | Campaign name | `summer_sale`, `product_launch` |
103| `utm_content` | Variant (optional) | `banner_a`, `cta_button` |
104| `utm_term` | Paid keyword (optional) | `running_shoes` |
105 
106**GA4 alignment** (avoid Unassigned):
107 
108| Channel | utm_medium | utm_source |
109|---------|------------|------------|
110| Paid Search | `cpc` | `google`, `bing` |
111| Paid Social | `paid-social`, `cpc` | `facebook`, `instagram` |
112| Email | `email` | `newsletter`, `mailchimp` |
113| Organic Social | `social` | `twitter`, `linkedin` |
114| App install | `cpc`, `app` | `google`, `facebook`, `apple` |
115| CTV / Streaming | `video`, `ctv` | `hulu`, `roku`, `youtube` |
116| Display / Banner | `display`, `cpc` | Publisher or network name |
117| Directory ads | `paid`, `cpc` | `taaft`, `shopify`, `g2`, `capterra` |
118 
119- **Consistent naming**: Lowercase, hyphens; document conventions; never tag internal links (overwrites session attribution)
120- **Apply everywhere**: Every link in emails, social posts, ads
121- **Avoid**: Typos, inconsistent values; causes fragmentation
122 
123## Traffic Diversification
124 
125| Principle | Guideline |
126|-----------|-----------|
127| **Search share** | Keep organic search below ~75% of total traffic |
128| **Health** | Higher direct + referral share = healthier profile |
129| **Brand sites** | Diversified traffic is common for strong brands |
130| **Engagement** | Content, email, social, free tools drive return visits |
131 
132See **seo-monitoring** for full SEO data analysis framework.
133 
134## Natural Traffic Benchmark
135 
136**Location**: GA4 > Reports > Acquisition > Traffic acquisition
137 
1381. Review organic traffic trend
1392. Record baseline (e.g., monthly total)
1403. Compare periodically to detect growth or decline
141 
142## Output Format
143 
144- **Traffic source** breakdown
145- **Dark traffic** estimate and actions
146- **UTM** tagging recommendations
147- **Segmentation** approach for reporting
148 
149## Related Skills
150 
151- **analytics-tracking**: Implement UTM, events, conversions; attribution models
152- **google-ads, paid-ads-strategy**: Paid channels; attribution informs budget allocation
153- **ai-traffic-tracking**: AI search traffic
154- **google-search-console**: GSC performance and indexing analysis
155- **seo-monitoring**: Full SEO data analysis system, benchmark, article database
156- **email-marketing**: Email strategy; UTM for email links
157 
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License
MIT
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