traffic-analysis▌
kostja94/marketing-skills · updated Apr 8, 2026
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Guides website traffic analysis across all channels (organic, paid, social, referral, direct). Covers traffic source attribution, dark traffic identification, and multi-channel reporting.
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
How to use traffic-analysis on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add traffic-analysis
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches traffic-analysis from GitHub repository kostja94/marketing-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate traffic-analysis. Access the skill through slash commands (e.g., /traffic-analysis) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
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Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.4★★★★★50 reviews- ★★★★★Ira Kim· Dec 28, 2024
traffic-analysis is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Aarav Srinivasan· Dec 28, 2024
Keeps context tight: traffic-analysis is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Pratham Ware· Dec 24, 2024
Solid pick for teams standardizing on skills: traffic-analysis is focused, and the summary matches what you get after install.
- ★★★★★Yuki White· Dec 20, 2024
Useful defaults in traffic-analysis — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Aarav White· Nov 19, 2024
I recommend traffic-analysis for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Nia Bhatia· Nov 15, 2024
Useful defaults in traffic-analysis — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Diya Malhotra· Nov 11, 2024
traffic-analysis is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Aarav Farah· Nov 11, 2024
traffic-analysis has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Li Robinson· Nov 7, 2024
Solid pick for teams standardizing on skills: traffic-analysis is focused, and the summary matches what you get after install.
- ★★★★★Aisha Lopez· Oct 26, 2024
Keeps context tight: traffic-analysis is the kind of skill you can hand to a new teammate without a long onboarding doc.
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