Guides website traffic analysis across all channels (organic, paid, social, referral, direct). Covers traffic source attribution, dark traffic identification, and multi-channel reporting.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiontraffic-analysisExecute the skills CLI command in your project's root directory to begin installation:
Fetches traffic-analysis from kostja94/marketing-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate traffic-analysis. Access via /traffic-analysis in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
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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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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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.
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.
| 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.
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.
| 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 |
Traffic without clear origin--analytics tools default to "Direct" when referrer is missing. Common causes:
When traffic was sent from known sources, analytics often misattributed:
| 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 |
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
| 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 |
| 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.
Location: GA4 > Reports > Acquisition > Traffic acquisition
Make data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
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traffic-analysis is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: traffic-analysis is the kind of skill you can hand to a new teammate without a long onboarding doc.
Solid pick for teams standardizing on skills: traffic-analysis is focused, and the summary matches what you get after install.
Useful defaults in traffic-analysis — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend traffic-analysis for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in traffic-analysis — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
traffic-analysis is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
traffic-analysis has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: traffic-analysis is focused, and the summary matches what you get after install.
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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