traffic-analysis
/install kostja94-traffic-analysis
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 |
| 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 |
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
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
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install kostja94-traffic-analysis - 安装完成后,直接呼叫该 Skill 的名称或使用
/kostja94-traffic-analysis触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
traffic-analysis 是什么?
When the user wants to analyze website traffic sources, attribution, or dark traffic. Also use when the user mentions "traffic sources," "dark traffic," "dir... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 199 次。
如何安装 traffic-analysis?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install kostja94-traffic-analysis」即可一键安装,无需额外配置。
traffic-analysis 是免费的吗?
是的,traffic-analysis 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
traffic-analysis 支持哪些平台?
traffic-analysis 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 traffic-analysis?
由 Kostja Zhang(@kostja94)开发并维护,当前版本 v1.1.0。