analytics-traffic

name	analytics-traffic
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," or "channel analysis."
metadata	{"version":"1.0.0"}

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

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
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

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 analytics-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 and event tracking
• analytics-ai-traffic: AI search traffic
• analytics-google-search-console: GSC performance and indexing analysis
• analytics-seo-monitoring: Full SEO data analysis system, benchmark, article database
• channels-email-marketing: Email strategy; UTM for email links