Generic UTM Source Names Kill Your Attribution Analysis

You send 4 email campaigns in January.

All use utm_source=email.

GA4 shows:

• email / email: 8,400 sessions

But you can't tell:

• Which campaign performed best
• Which subject line worked
• Which audience segment engaged
• Which sending time was optimal

The problem: Generic utm_source values (email, social, partner) lump all campaigns together.

You get volume data but lose performance analysis.

What Are Generic UTM Sources?

Generic source = Describes channel type, not specific origin

Examples:

• utm_source=email (which email platform? which list?)
• utm_source=social (which platform? Facebook? LinkedIn?)
• utm_source=partner (which partner? all 12 partners look identical?)
• utm_source=paid (which ad platform?)
• utm_source=newsletter (which newsletter send?)

Why they're problematic:

Multiple campaigns using same generic source appear as one blob in GA4:

January campaigns all using utm_source=email:

1. Welcome series (automated)
2. Product launch (one-time)
3. Weekly digest (recurring)
4. Re-engagement (win-back)

GA4 report:

• email / email: 12,400 sessions total

Can't answer:

• Which campaign drove the most traffic?
• Which converted best?
• Which should you send more of?

Real Example: $180K Campaign Lost in Generic Source Data

Client: B2B SaaS Email campaigns (January):

1. Product launch: Sent to 45,000 leads, $22,000 in closed deals
2. Weekly digest: Sent to 60,000 subscribers, $3,400 in closed deals
3. Re-engagement: Sent to 28,000 inactive users, $0 in closed deals
4. Webinar invitation: Sent to 18,000 prospects, $8,200 in closed deals

All campaigns used:

utm_source=email&utm_medium=email

GA4 showed:

• email / email: 14,200 sessions
• Revenue: $33,600

What they COULDN'T see:

• Product launch drove 64% of revenue
• Weekly digest underperformed (high sends, low revenue)
• Re-engagement campaign completely failed
• Webinar invites had highest ROI per send

Decision based on generic data: "Email works. Send more email."

Should have been: "Product launches work incredibly well. Weekly digest needs improvement. Kill re-engagement campaigns. Double down on webinar invites."

The fix:

Changed to specific sources:

utm_source=product-launch-email
utm_source=weekly-digest
utm_source=reengagement-campaign
utm_source=webinar-invite

Next month's data:

• product-launch-email: 5,200 sessions, $28,400 revenue
• weekly-digest: 6,800 sessions, $4,100 revenue
• webinar-invite: 2,100 sessions, $9,800 revenue
• reengagement-campaign: 400 sessions, $0 revenue

Decision based on specific data:

• Cancelled re-engagement campaigns (saving 10 hours/month)
• Reduced weekly digest frequency (diminishing returns)
• Increased product launch emails (highest ROI)
• Increased webinar invites (highest conversion rate)

Result: Email revenue increased from $33,600 to $58,200/month (+73%) with same total effort.

How to Fix Generic UTM Sources

Option 1: Use Specific Platform/Campaign Name

Instead of:

utm_source=social

Use:

utm_source=facebook
utm_source=instagram
utm_source=linkedin
utm_source=twitter

Instead of:

utm_source=email

Use:

utm_source=product-launch-email
utm_source=weekly-newsletter
utm_source=webinar-invite

Option 2: Keep Generic Source, Use Campaign for Specificity

If you prefer consistent source:

utm_source=newsletter&utm_medium=email&utm_campaign=product-launch-jan-2024
utm_source=newsletter&utm_medium=email&utm_campaign=weekly-digest-jan-08
utm_source=newsletter&utm_medium=email&utm_campaign=webinar-invite-jan-15

Benefits:

• All newsletter traffic grouped under one source
• Campaign parameter provides specificity
• Can analyze both aggregate (source level) and specific (campaign level)

Option 3: Use Both (Recommended for Large Programs)

Structure:

utm_source=[platform/list]
utm_medium=[channel-type]
utm_campaign=[specific-campaign]
utm_content=[variant/placement]

Example:

utm_source=klaviyo
utm_medium=email
utm_campaign=product-launch-jan-2024
utm_content=hero-cta

Enables analysis at multiple levels:

• Platform level: How does Klaviyo perform vs Mailchimp?
• Channel level: How does email perform vs social?
• Campaign level: Which specific email performed best?
• Variant level: Which CTA placement worked best?

Generic vs Specific Source Examples

Email Marketing

❌ Generic (bad):

utm_source=email
utm_source=newsletter
utm_source=mail

✅ Specific (good):

utm_source=welcome-series
utm_source=product-launch-email
utm_source=weekly-digest
utm_source=webinar-invite-email

✅ Best (platform + campaign):

utm_source=klaviyo&utm_campaign=welcome-series-day1
utm_source=mailchimp&utm_campaign=product-launch-jan

Social Media

❌ Generic (bad):

utm_source=social
utm_source=socialmedia

✅ Specific (good):

utm_source=facebook
utm_source=instagram
utm_source=linkedin
utm_source=twitter

✅ Best (platform + campaign):

utm_source=facebook&utm_campaign=product-launch-video
utm_source=linkedin&utm_campaign=thought-leadership-jan

Partner/Referral

❌ Generic (bad):

utm_source=partner
utm_source=referral
utm_source=affiliate

✅ Specific (good):

utm_source=acme-corp.com
utm_source=techpartner.io
utm_source=affiliate-john-smith

Paid Advertising

❌ Generic (bad):

utm_source=paid
utm_source=ads
utm_source=ppc

✅ Specific (good):

Use platform auto-tagging (gclid, fbclid) instead of manual UTMs

Or if manual UTMs required:

utm_source=google&utm_medium=cpc
utm_source=facebook&utm_medium=paid-social
utm_source=linkedin&utm_medium=paid-social

FAQ

Isn't utm_medium supposed to be the channel type?

Yes. Use utm_medium for channel (email, social, cpc, referral). Use utm_source for specific origin (facebook, newsletter, partner-domain).

What if I want to group all email together?

Use medium for grouping: utm_medium=email. Use source for specificity: utm_source=product-launch-email vs utm_source=weekly-digest.

Can I use generic source if I use specific campaign names?

Yes, but you lose the ability to quickly compare sources. Better to use specific sources AND specific campaigns for maximum analysis flexibility.

How specific should utm_source be?

Specific enough to distinguish performance. If you run 4 different email types, use 4 different sources (or source + campaign combinations).

What about historical data with generic sources?

Historical data stays as-is. Going forward, use specific sources. You'll see immediate improvement in new campaign analysis.

Prevention Checklist

✅ Setup:

• Document: "Never use generic utm_source values"
• Create source naming standards (specific, not generic)
• Update email platform defaults (specific source per campaign type)
• Train team on specificity importance

✅ Before Every Campaign:

• Check utm_source is specific (not "email", "social", "partner")
• Verify utm_campaign adds additional context
• Can you distinguish this campaign from others in reports?
• Test URL shows descriptive source in GA4 Realtime

Conclusion

Generic utm_source values kill attribution analysis.

Replace:

• utm_source=email → utm_source=product-launch-email
• utm_source=social → utm_source=facebook
• utm_source=partner → utm_source=acme-corp.com

Result: Individual campaign performance visible, enabling data-driven optimization.

Related: UTM Source Naming Best Practices