traffic-analysis
npx machina-cli add skill kostja94/marketing-skills/traffic --openclawAnalytics: 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 | Google Ads, Meta Ads, etc. | UTM required |
| 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
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 |
- Consistent naming: Lowercase, underscores; document conventions
- 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 and event tracking
- 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
Source
git clone https://github.com/kostja94/marketing-skills/blob/main/skills/analytics/traffic/SKILL.mdView on GitHub Overview
This skill guides analyzing website traffic across organic, paid, social, referral, and direct channels. It covers traffic source attribution, dark traffic identification, and multi-channel reporting to improve decision-making and ROI.
How This Skill Works
It works by tagging links with UTMs, applying GA4 filters and segments, and interpreting channel data to attribute visits and conversions. Analysts combine source, medium, and campaign signals to build reliable multi-channel reports.
When to Use It
- When comparing organic vs paid traffic performance and ROI
- When diagnosing dark traffic and misattributed direct visits
- When auditing traffic sources through UTM tagging and naming conventions
- When building multi-channel attribution reports across organic, paid, social, and referrals
- When evaluating branded vs non-branded traffic and traffic diversification
Quick Start
- Step 1: Audit current traffic sources and assess UTM coverage
- Step 2: Implement consistent UTM tagging across emails, social, and ads
- Step 3: Create GA4 segments and reports to monitor channel attribution
Best Practices
- Use consistent, lowercase UTMs and document conventions (utm_source, utm_medium, utm_campaign)
- Tag every link in emails, social posts, and ads with UTMs
- Apply GA4 filters/segments to exclude or isolate bot traffic
- Segment direct traffic to separate genuine direct from dark traffic
- Block internal IPs to exclude company visits and keep reports clean
Example Use Cases
- Identify that portions of 'Direct' traffic are dark traffic coming from Instagram DMs
- Tag newsletters with UTM parameters and compare campaign performance
- Use GA4 segments to separate branded vs non-branded organic traffic
- Filter out bot traffic to reveal true human sessions in reports
- Mitigate misattribution by annotating campaigns and verifying referrers
