Why Campaign Details in utm_source Break Your GA4 Reports

You open GA4's Traffic Acquisition report to see how email is performing.

Instead of one clean "mailchimp" entry, you see:

• newsletter_january_2024 - 340 sessions
• newsletter_february_2024 - 298 sessions
• newsletter_march_2024 - 412 sessions
• promo_email_spring_sale - 521 sessions
• promo_email_black_friday - 789 sessions
• welcome_email_series - 156 sessions
• abandoned_cart_email - 203 sessions

That's 7 rows for what should be 1 row: "mailchimp."

Now multiply this by 12 months, 4 campaign types, and 3 email platforms.

You have 144 separate "source" entries when you should have 3.

Your reports are impossible to read. Your month-over-month comparisons are broken. You can't see overall channel performance.

This is what happens when you put campaign details in utm_source.

What utm_source Is Supposed to Be

utm_source should identify the platform or vendor sending traffic.

• mailchimp - Email platform
• facebook - Social platform
• google - Search engine
• impact - Affiliate network
• partnersite - Specific referral partner

utm_source answers: "Where did this traffic come from?"

It should be:

• Stable (doesn't change frequently)
• Generic (platform name, not campaign name)
• Consistent (same value across campaigns)

What Happens When You Add Campaign Details

When marketers put campaign-specific information in utm_source, they create this:

Email campaigns:

utm_source=newsletter_january_2024
utm_source=newsletter_february_2024
utm_source=promo_email_spring_sale
utm_source=promo_email_black_friday
utm_source=welcome_series_day_1
utm_source=welcome_series_day_7
utm_source=cart_abandonment_email

Social campaigns:

utm_source=facebook_spring_sale_2024
utm_source=facebook_product_launch
utm_source=facebook_retargeting_q1
utm_source=linkedin_webinar_promo
utm_source=linkedin_ebook_download

Affiliate campaigns:

utm_source=impact_bloggers_q1
utm_source=impact_influencers_spring
utm_source=shareasale_coupon_sites

Each campaign creates a new utm_source value.

Why This Destroys Your GA4 Reports

Problem 1: Impossible to See Platform Performance

You want to know: "How is email performing overall?"

GA4 Traffic Acquisition report shows:

Session source               | Sessions | Conversions
-----------------------------|----------|------------
newsletter_january_2024      | 340      | 8
newsletter_february_2024     | 298      | 6
newsletter_march_2024        | 412      | 11
promo_email_spring_sale      | 521      | 18
promo_email_black_friday     | 789      | 34
welcome_email_series         | 156      | 4
abandoned_cart_email         | 203      | 9
...42 more email source rows

Question: What's the total email performance?

Answer: You have to manually add 49 separate rows.

If utm_source was just "mailchimp":

Session source    | Sessions | Conversions
------------------|----------|------------
mailchimp         | 2,719    | 90

One row. Instant insight.

Problem 2: Broken Month-Over-Month Comparisons

You want to compare January vs February email performance.

January:

Session source               | Sessions
-----------------------------|----------
newsletter_january_2024      | 340
welcome_series_day_1_jan     | 89
promo_email_new_year         | 234

February:

Session source               | Sessions
-----------------------------|----------
newsletter_february_2024     | 298
welcome_series_day_1_feb     | 103
promo_email_valentines       | 401

There's no overlap. Every row is different.

You can't set up a month-over-month comparison in GA4 because the source values don't match across time periods.

Problem 3: Report Clutter (Pagination Hell)

GA4 Traffic Acquisition reports default to showing 10 rows.

With fragmented utm_source values:

• Page 1: Rows 1-10 (various newsletters)
• Page 2: Rows 11-20 (more newsletters)
• Page 3: Rows 21-30 (promotional emails)
• Page 4: Rows 31-40 (transactional emails)

You have to paginate through 5+ pages just to see all email traffic.

With clean utm_source:

• Row 1: mailchimp - 2,719 sessions (all email in one row)
• Row 2: facebook - 3,200 sessions (all social in one row)
• Row 3: google - 4,100 sessions (all search in one row)

Everything on page 1.

Problem 4: Segment and Filter Chaos

You want to create a GA4 segment for "All Email Traffic."

With fragmented utm_source, you have to add 49 separate conditions:

Session source = newsletter_january_2024
OR Session source = newsletter_february_2024
OR Session source = promo_email_spring_sale
OR Session source = promo_email_black_friday
...OR Session source = (45 more values)

Every time you launch a new email campaign, you have to update the segment.

With clean utm_source:

Session source = mailchimp

Done. One condition. Never needs updating.

Real Example: 347 Source Entries for 4 Actual Platforms

Client: B2B SaaS company Marketing channels: Email (Mailchimp), Paid Social (Facebook, LinkedIn), Affiliates (Impact)

What they expected in GA4:

Session source    | Sessions
------------------|----------
mailchimp         | 4,200
facebook          | 3,800
linkedin          | 2,100
impact            | 890

What GA4 actually showed:

Session source                              | Sessions
--------------------------------------------|----------
mailchimp-newsletter-january-2024           | 203
mailchimp-newsletter-february-2024          | 189
mailchimp-promo-spring-sale                 | 412
mailchimp-promo-product-launch              | 298
mailchimp-welcome-series-day1               | 67
mailchimp-welcome-series-day7               | 45
...87 more mailchimp source rows
facebook-spring-sale-2024                   | 521
facebook-product-launch-video               | 340
facebook-retargeting-cart                   | 289
...43 more facebook source rows
linkedin-webinar-q1-2024                    | 234
linkedin-ebook-download                     | 178
...31 more linkedin source rows
impact-bloggers-q1                          | 156
impact-influencers-spring                   | 103
...29 more impact source rows

Total source entries: 347 Actual platforms: 4

Client's frustration:

"I can't see which platform is performing best. I can't compare month-over-month. I can't filter reports. Every campaign creates a new source. It's chaos."

We consolidated utm_source to platform names only:

After fix:

Session source    | Sessions | Conversions | Cost per Session
------------------|----------|-------------|------------------
mailchimp         | 4,200    | 112         | $1.43
facebook          | 3,800    | 89          | $3.16
linkedin          | 2,100    | 67          | $4.76
impact            | 890      | 34          | $2.25

347 rows reduced to 4 rows.

Insights instantly visible:

• Mailchimp has lowest cost per session
• LinkedIn has highest cost per session but strong conversion rate
• Impact has highest conversion rate (34 conversions from 890 sessions = 3.8%)

Client shifted $8,000/month budget from LinkedIn to Impact based on ROAS. Would have been impossible to see with fragmented source data.

Why Marketers Make This Mistake

Reason 1: Trying to Be Too Descriptive

Intent: "I want to know exactly which campaign this traffic came from."

Wrong implementation:

utm_source=spring_sale_email_2024
utm_medium=email
utm_campaign=20_percent_off

The thinking: "More detail in utm_source means better tracking."

Reality: utm_campaign already provides this detail. Duplicating it in utm_source fragments reports.

Right implementation:

utm_source=mailchimp
utm_medium=email
utm_campaign=spring-sale-20-percent-off

Reason 2: Following Outdated Templates

Many UTM templates from 2015-2018 recommend putting campaign context in utm_source:

Old template example:

utm_source=[CAMPAIGN_NAME]_[PLATFORM]
utm_medium=[CHANNEL]
utm_campaign=[DATE]

Result:

utm_source=spring_sale_email
utm_medium=newsletter
utm_campaign=2024-03-15

This creates a new source value for every campaign.

Reason 3: Not Understanding UTM Parameter Hierarchy

utm_source, utm_medium, and utm_campaign work together as a hierarchy:

1. utm_source = Broad platform (stable)
2. utm_medium = Channel type (stable)
3. utm_campaign = Specific campaign (changes frequently)

When you put campaign details in utm_source, you reverse the hierarchy and break reporting.

Reason 4: Trying to Avoid Duplicate utm_campaign Values

Some marketers think: "I'm running Spring Sale campaigns on email AND social. If I use utm_campaign=spring-sale for both, won't they merge?"

Answer: No. GA4 tracks source + medium + campaign together.

Email campaign:

utm_source=mailchimp
utm_medium=email
utm_campaign=spring-sale

Social campaign:

utm_source=facebook
utm_medium=paidsocial
utm_campaign=spring-sale

GA4 sees these as two separate campaigns because source+medium differ.

You don't need unique utm_campaign names across channels. The combination makes them unique.

How to Check If You Have This Problem

Method 1: GA4 Traffic Acquisition Report (2 minutes)

1. GA4 → Reports → Traffic Acquisition
2. Change primary dimension to "Session source"
3. Scroll through the list

Look for patterns like:

• Multiple entries for the same platform (mailchimp-jan, mailchimp-feb, mailchimp-mar)
• Campaign names in source values (spring-sale-email, product-launch-email)
• Dates in source values (newsletter-2024-01, newsletter-2024-02)

If you see these patterns, you have campaign details in utm_source.

Method 2: Count Unique Sources (3 minutes)

1. GA4 → Explore → Create Free Form
2. Add dimension: Session source
3. Add metric: Sessions
4. Export to CSV
5. Count rows in Excel/Sheets

Healthy range:

• 10-30 unique sources (typical for small-to-medium businesses)
• 30-100 unique sources (large businesses with many partners)

Problem range:

• 100-500 unique sources → Likely have campaign details in utm_source
• 500+ unique sources → Definitely have this problem

Method 3: Pattern Analysis (5 minutes)

1. GA4 → Explore → Free Form
2. Dimension: Session source
3. Metric: Sessions
4. Sort by Sessions (descending)
5. Look at top 50 sources

Red flags:

• Sources with dates: newsletter-2024-01-15
• Sources with campaign names: spring-sale-facebook
• Sources that describe campaigns: black-friday-promo-email
• Sources with underscores separating multiple concepts: mailchimp_newsletter_january

The Fix: Separate Platform from Campaign

Step 1: Identify Current utm_source Patterns

Export all utm_source values from GA4:

1. GA4 → Explore → Free Form
2. Dimension: Session source
3. Download CSV
4. Group by platform type

Example:

Current utm_source                   | Platform | Campaign Detail
-------------------------------------|----------|------------------
newsletter_january_2024              | email    | january newsletter
newsletter_february_2024             | email    | february newsletter
promo_email_spring_sale              | email    | spring sale promo
facebook_spring_sale_2024            | facebook | spring sale 2024
facebook_product_launch              | facebook | product launch
linkedin_webinar_q1                  | linkedin | webinar q1

Step 2: Define Standard utm_source Values

For each platform, choose one stable utm_source value:

Step 3: Update All Campaign Templates

Email platform defaults:

Mailchimp:

1. Settings → Tracking → Google Analytics
2. Set utm_source default: mailchimp
3. Set utm_medium default: email
4. Leave utm_campaign variable (changes per campaign)

HubSpot:

1. Settings → Marketing → Tracking
2. Update default UTM parameters
3. utm_source: hubspot
4. utm_medium: email

Social media scheduler (Hootsuite/Buffer):

1. Settings → Link Tracking
2. utm_source: [platform] (use platform name token)
3. utm_medium: social or paidsocial

Step 4: Restructure Campaign Naming

Move campaign details from utm_source to utm_campaign.

Before (wrong):

utm_source=newsletter_spring_sale_2024
utm_medium=email
utm_campaign=march

After (correct):

utm_source=mailchimp
utm_medium=email
utm_campaign=spring-sale-2024-march

Before (wrong):

utm_source=facebook_product_launch_video
utm_medium=paidsocial
utm_campaign=awareness

After (correct):

utm_source=facebook
utm_medium=paidsocial
utm_campaign=product-launch-video-awareness

Best Practices: utm_source Naming Standards

Rule 1: Platform Name Only

utm_source should ONLY identify the platform or vendor:

• ✅ mailchimp, sendgrid, hubspot
• ✅ facebook, linkedin, tiktok
• ✅ google, bing
• ❌ mailchimp_spring_sale
• ❌ facebook_ads_2024

Rule 2: Lowercase, Hyphens for Multi-Word

• ✅ google-display
• ✅ partner-blog
• ❌ GoogleDisplay
• ❌ partner_blog (underscores fragment searches)

Rule 3: Consistent Across Campaigns

Use the EXACT same utm_source for every campaign from that platform:

Mailchimp campaigns:

• Newsletter → utm_source=mailchimp
• Promotional → utm_source=mailchimp
• Transactional → utm_source=mailchimp
• Welcome series → utm_source=mailchimp

All use the same source. Campaign details go in utm_campaign.

Rule 4: Don't Duplicate Platform in Source and Medium

Wrong:

utm_source=facebook
utm_medium=facebook-ads

Right:

utm_source=facebook
utm_medium=paidsocial

utm_source and utm_medium serve different purposes. Don't duplicate.

Rule 5: For Multiple Sub-Sources, Use Specific Names

If you have multiple partners or sub-platforms, use specific names in utm_source:

Affiliate programs:

• utm_source=impact (affiliate network)
• utm_source=shareasale (different network)
• utm_source=individual-blogger-name (specific partner)

Email platforms:

• utm_source=mailchimp (marketing emails)
• utm_source=sendgrid (transactional emails)

This is fine because each source is still stable across campaigns.

FAQ

Won't I lose campaign-level detail if I simplify utm_source?

No. Campaign details belong in utm_campaign, not utm_source. You get the same granularity with better organization:

Before:

utm_source=newsletter_spring_sale
utm_campaign=2024

After:

utm_source=mailchimp
utm_campaign=newsletter-spring-sale-2024

You can still filter by campaign name. But now email traffic is aggregated under one source.

What if I have campaign details already in utm_source for 2 years of historical data?

Historical data stays as-is. GA4 doesn't allow retroactive changes. Focus on fixing future campaigns. Over time, clean data will accumulate and fragmented old data will age out of default reporting windows.

How do I compare old fragmented data with new clean data?

Create two segments:

1. "Old Email (Fragmented)" → Include all old utm_source values
2. "New Email (Clean)" → utm_source = mailchimp

Use these segments for historical comparisons during the transition period.

Can I use custom dimensions instead of utm_source?

Yes, but utm_source is a default dimension in all GA4 reports. Custom dimensions require manual setup in Explorations. It's better to fix utm_source than work around it.

What about A/B tests? Should I put variant in utm_source?

No. Use utm_content for variants:

utm_source=mailchimp
utm_medium=email
utm_campaign=spring-sale
utm_content=variant-a (or variant-b)

GA4 will show utm_content as a secondary dimension for comparison.

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Related: Campaign Details in Source Rule Documentation