Source and Medium

Source and Medium are core analytics parameters that show where a visitor came from and how they got there. Together they form the foundation for measuring marketing channel performance.

Anatomy

Source: where from

Source identifies the platform or resource. A domain, search engine, social network, or any other origin.

Examples:

• google, bing, duckduckgo (search engines)
• facebook, instagram, linkedin (social)
• example.com (referring site)
• newsletter (email)
• (direct) (no identifiable source)

Medium: how

Medium defines the channel type or delivery method. Source answers "from where". Medium answers "how".

Standard values:

Medium	Description	Use case
organic	Organic search	Unpaid search results
cpc/ppc	Pay-per-click	Contextual advertising
referral	Referral link	Transition from another site
email	Email distribution	Email links
social	Organic social	Organic social posts
display	Display advertising	Banner advertising
affiliate	Partner traffic	Partner links
(none)	Undefined	Direct visits

Source/Medium and UTM

UTM parameters set Source and Medium explicitly for any link.

UTM link structure

example.com/landing?utm_source=facebook&utm_medium=cpc&utm_campaign=summer_sale

• utm_source=facebook: traffic from Facebook
• utm_medium=cpc: paid pay-per-click
• utm_campaign=summer_sale: summer sale campaign

Full UTM structure

Parameter	Required	Purpose	Example
utm_source	Yes	Source	facebook, google, newsletter
utm_medium	Yes	Channel type	cpc, email, social
utm_campaign	Yes	Campaign name	product_launch_2025
utm_content	No	Ad variant	banner_blue, text_link
utm_term	No	Keyword	web_analytics

Auto-detection vs manual tagging

Analytics systems try to detect Source and Medium for untagged traffic.

Auto-detection works for:

• Organic search (recognized engines)
• Referral traffic (extracted source domain)
• Direct visits (no referrer)

Manual tagging required for:

• Ad campaigns (accurate attribution)
• Email distributions (otherwise fall into Direct)
• Social (separate paid and organic)
• Partner programs (track partner performance)

Tagging rules

Naming standardization

Consistency is everything.

Common mistakes

Case issues:

• Wrong: Facebook, facebook, FACEBOOK (three sources)
• Right: facebook

Inconsistent names:

• Wrong: fb, facebook, Facebook_ads
• Right: facebook

Spaces in parameters:

• Wrong: utm_medium=paid social (truncates to "paid")
• Right: paid_social

Detail hierarchy

Different detail levels enable analysis at different depths.

BasicAdvancedExpert

Minimal detail for general analysis:

utm_source=facebook
utm_medium=paid

Detail for deeper analysis:

utm_source=facebook_feed
utm_medium=cpc_retargeting

Maximum detail:

utm_source=facebook_lookalike_us
utm_medium=cpc_conversion_optimized

Documentation

Source/Medium documentation is mandatory for team work.

Documentation template

Social:

• Facebook organic: source=facebook, medium=social
• Facebook ads: source=facebook, medium=cpc
• Instagram Stories: source=instagram, medium=stories

Email:

• Newsletter: source=newsletter, medium=email
• Trigger: source=automation, medium=email
• Promo: source=promo, medium=email

Partner programs:

• Main partners: source=[partner_name], medium=affiliate
• Referral links: source=[referrer_name], medium=referral

Performance analysis

Key metrics

Metric	What it shows	Read
Sessions	Volume	Source popularity
Bounce Rate	Relevance	Targeting quality
Conversion	Effectiveness	ROI potential
AOV	Visitor value	LTV forecast
Time on Site	Engagement	Content quality for the audience

Segmentation

graph TD
    A[Source/Medium Data] --> B{Segmentation}
    B --> C[By Device]
    B --> D[By Geography]
    B --> E[By Time]
    B --> F[By Landing Pages]

    C --> G[Mobile vs Desktop]
    D --> H[Countries and Regions]
    E --> I[Days and Hours]
    F --> J[Page Effectiveness]

Multi-channel funnels

Source/Medium reveals the full journey.

B2B conversion path

1. First touch: google / organic (solution search)
2. Research: linkedin / social (company research)
3. Comparison: capterra.com / referral (reading reviews)
4. Return: (direct) / (none) (direct visit)
5. Conversion: newsletter / email (purchase after email)

Email gets the conversion, but organic search started the journey.

Source/Medium by channel

Paid advertising

Accurate tagging is critical for ROI.

Google Ads:

utm_source=google
utm_medium=cpc
utm_campaign={campaign_name}
utm_content={ad_id}
utm_term={keyword}

Facebook Ads:

utm_source=facebook
utm_medium=paid_social
utm_campaign={campaign_name}
utm_content={ad_set_name}

Organic channels

Even free traffic needs tagging.

Blog and content marketing:

utm_source=blog
utm_medium=article
utm_campaign=seo_content
utm_content=guide_analytics

Organic social:

utm_source=linkedin
utm_medium=social_organic
utm_campaign=thought_leadership

Email marketing

Email without UTM falls into Direct, distorting reality.

Email structure

Welcome series:

utm_source=welcome_series
utm_medium=email
utm_campaign=onboarding
utm_content=email_{number}

Promo newsletter:

utm_source=promo_newsletter
utm_medium=email
utm_campaign=black_friday_2025
utm_content={link_position}

Limits and Statable improvements

Standard platform limits

• Parameter length limits: long values truncate
• Attribution loss: cross-domain transitions
• Retroactive analysis: can't reclassify historical data
• Limited customization: rigid grouping rules

Statable approach

Intelligent classification

ML auto-determines Source/Medium even without explicit tagging, using behavior patterns and contextual signals.

Flexible attribution

Dynamic attribution lets you apply different models to the same data without losing history.

Tagging automation

Tools for auto UTM generation with validation and corporate-standard compliance.

Practical recommendations

Launch checklist

• Naming convention document
• Templates for all channels
• Auto link generators
• Team training on tagging
• Regular parameter audits
• Monitoring dashboards
• Anomaly alerts

Tools

UTM link generators:

Reduce errors. Keep tagging consistent.

Bulk generation spreadsheets:

Excel or Google Sheets formulas auto-create tagged URLs for big campaigns.

Automation systems:

Integrate with ad platforms for dynamic parameter substitution.

Future

Privacy regulation

• Referrer blocking: browsers restrict source transmission
• Intelligent Tracking Prevention: auto-removes tracking parameters
• Consent-based tracking: explicit consent required

Adapting

Server-side tracking bypasses browser limits.

First-party attribution uses your own data and identifiers.

Probabilistic attribution applies statistical models to recover lost data.

Source/Medium is fundamental for measuring marketing performance. Multi-channel journeys and tightening privacy make it harder and more important. Investment in proper Source/Medium setup pays back in better marketing spend and clearer behavior insight.

About AI participation in writing articles

This article, like many others on our site, was created, written and proofread by a team of developers. Of course, not without the participation of AI assistants. We don't hide this and believe that modern systems are already quite good at handling simple tasks and, relatively speaking, writing an article about Viewport yourself is quite strange. It won't come out significantly better and will take a lot of time. But providing basic understanding to beginner webmasters is necessary. Of course, after the article is written by assistants - there's always proofreading, and this is where not one or two people participate, and only after that the article is published.

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