Most B2B marketers face the same frustrating reality: fragmented attribution data that makes it nearly impossible to justify marketing spend.

Here's the good news. Linear attribution offers a straightforward solution to this chaos. It won't solve every attribution challenge you face. But it will give you a clear, defensible view of how your campaigns contribute to pipeline.

This guide walks you through real examples, CRM implementation guidance, and a decision framework to help you determine if linear attribution fits your business. We'll cover Salesforce Campaign Influence, HubSpot Attribution Reporting, and the critical gaps most articles ignore.

Ready to stop guessing? Let's dig in.

What Is Linear Attribution? (And How Does It Calculate Credit?)

Linear attribution distributes conversion credit equally across all touchpoints in a customer journey. No weighting. No favoritism. Every interaction gets the same slice of the pie.

The formula couldn't be simpler:

Revenue Credit = Opportunity Value ÷ Number of Touchpoints

Consider a €12,000 deal with four touchpoints. Each touchpoint receives €3,000 in credit. A prospect who clicked a Google Ad, read your blog, downloaded a whitepaper, and booked a demo? Each of those interactions earns 25% of the revenue.

Salesforce users will recognize this model under a different name: Even Distribution in Campaign Influence settings. Same concept, different label.

Why does this matter? Because when your CFO asks which campaign drove that enterprise deal, you can point to data rather than gut instinct. Linear attribution won't tell you which touchpoint mattered most. But it will show you that every touchpoint mattered equally in the eyes of the model.

3 Linear Attribution Examples for B2B Marketing

Theory only gets you so far. Let's look at how linear attribution plays out in real B2B scenarios with actual revenue figures.

Example 1: Standard B2B Digital Journey (4 Touchpoints)

Scenario: A SaaS marketing intelligence platform closes a €12,000 annual deal. The prospect interacted with four marketing touchpoints before converting.

What this reveals: Linear attribution ensures your SEO content and nurturing campaigns receive the same credit as paid ads. For content teams fighting to justify investment, this visibility is invaluable. Your blog post didn't just "support" the deal. It earned €3,000 of credit.

The limitation: That initial ad click receives identical weight to the demo booking. Yet intuitively, we know someone requesting a demo signals stronger intent than someone clicking an ad. Linear attribution treats them as equals.

Example 2: Long B2B Sales Cycle with Offline Conversion (5 Touchpoints)

Scenario: An enterprise marketing platform closes a €20,000 deal after a six month sales cycle. The journey spans both digital and offline touchpoints.

What this reveals: CMOs defending organic investment love this view. That initial SEO visit? It contributed €4,000 to a €20,000 deal. Without linear attribution, first touch credit might vanish entirely in a long sales cycle.

The limitation: The model treats a passive blog visit and an active sales conversation as equivalent contributions. Most sales leaders would argue that their demo meeting carried more weight than a prospect skimming an article. Linear attribution disagrees.

Example 3: Salesforce Campaign Influence Setup (Even Distribution)

Scenario: Three Salesforce Campaigns influence a single Opportunity worth €5,000 in first year revenue.

Critical prerequisite: This example only works if your team maintains Contact Roles on every Opportunity. Here's what trips up most Salesforce orgs: if your Decision Maker isn't linked to the Opportunity via their Contact Role, their associated Campaign receives zero influence credit. Even with linear attribution enabled.

The system relies on the relationship between Contact Roles and Campaign Members. Break that link, and your attribution data falls apart.

Technical note: Salesforce and Pardot linear attribution cannot track SEO visits, ad clicks, or any touchpoint that occurs before form submission. The CRM only sees what happens after lead creation. Everything before that? Invisible.

When to Use Linear Attribution (And When to Avoid It)

Linear attribution isn't universally right or wrong. It's right for specific situations and wrong for others. Here's how to decide.

Use linear attribution when:

You're early in attribution maturity. If your team has never measured multi-touch attribution, linear offers a simple starting point. The math is defensible. The logic is easy to explain. Start here before graduating to weighted models.

Your sales cycle involves many touchpoints with unclear importance. When you genuinely don't know which interactions matter most, equal distribution makes sense. Better to credit everything equally than guess wrong about weights.

You want mid-funnel content to receive credit. Linear attribution protects your SEO team, your content writers, and your nurturing campaigns from being overshadowed by paid acquisition. If proving content ROI matters to your organization, this model delivers.

Your team lacks bandwidth for custom models. Maintaining weighted attribution models requires ongoing analysis and adjustment. Linear attribution runs itself. Set it once and let it calculate.

Avoid linear attribution when:

You have clear evidence that certain touchpoints outperform others. If your data shows demo requests convert at 10x the rate of whitepaper downloads, treating them equally misrepresents reality. Consider W-shaped or custom models instead.

Your sales cycle is short. One or two touchpoints don't need equal distribution. Last click attribution tells you what you need to know in a direct response scenario.

You need to prioritize budget toward high-impact channels. Linear attribution won't surface your best performers. It treats a viral LinkedIn post and a forgettable banner ad as equals. For optimization decisions, you need models that differentiate.

You're running complex ABM plays. Account-based marketing often requires position-based models that weight first touch and opportunity creation more heavily. Linear attribution ignores these strategic milestones.

The decision framework

Ask yourself one question: What's my primary goal?

If your goal is holistic visibility across all channels, linear attribution works beautifully. If your goal is optimization toward highest-performing channels, you need weighted models like W-shaped or data-driven attribution.

Linear Attribution vs. Other Models: A Quick Comparison

Words only go so far. Let's see how the same €12,000 deal with four touchpoints looks under different attribution models.

Notice how dramatically the numbers shift. Under first-click, your SEO blog and whitepaper earn nothing. Under time decay, your paid ad receives the least credit because it happened earliest. Under W-shaped, key conversion moments receive boosted weight.

The takeaway: Linear attribution is the "fair" model. Everyone gets equal credit. W-shaped attribution is often the most accurate for B2B SaaS companies with defined funnel stages. Neither is objectively correct. Both serve different analytical purposes.

The Pre-Lead Tracking Gap (What Salesforce & HubSpot Don't Show You)

Here's the uncomfortable truth most attribution articles skip: native CRM attribution tools only track touchpoints after a lead exists in your system.

Think about what that means. A prospect visits your website five times via organic search. They click three paid ads across two weeks. They watch your YouTube video. Then, finally, they fill out a form.

What does Salesforce Campaign Influence see? The form submission. That's it.

What does HubSpot Attribution Reporting see? The same. Everything before lead creation vanishes into the void.

For long B2B sales cycles, this blind spot is massive. Research suggests 60-80% of the buyer journey happens before someone identifies themselves. All those anonymous visits, ad clicks, and content interactions? Your CRM never captures them.

What this means for linear attribution: The model can only distribute credit among touchpoints it knows about. If pre-lead touches aren't captured, they're excluded from the equation entirely. Your linear attribution report might show three touchpoints earning 33% each. But in reality, there were eight touchpoints. Five of them simply don't exist in your data.

To get a complete picture, you need technology that captures anonymous touchpoints through UTMs, page visits, and ad clicks. Then stitches that data to the lead record at conversion. Without it, you're running attribution on incomplete information.

Setting Up Linear Attribution in Your CRM

Salesforce Campaign Influence

Salesforce calls linear attribution "Even Distribution" within Customizable Campaign Influence. To enable it:

1. Navigate to Setup and search for "Campaign Influence Settings"
2. Enable Campaign Influence and Additional Campaign Influence Models
3. Access Model Settings and activate "Even Distribution"
4. Add Campaign Influence related lists to your Opportunity and Campaign page layouts

The critical step most teams miss: Ensure every Opportunity has proper Contact Roles assigned. Without Contact Roles linking Contacts to Opportunities, Campaign Influence has no way to connect Campaign Members to revenue. Your reports will show blanks.

HubSpot Attribution Reporting

HubSpot offers linear attribution as a standard option within Attribution Reports (Marketing Hub Enterprise required):

1. Navigate to Reports and select Create Report
2. Choose Attribution Report and select your conversion type (Contact Create, Deal Create, or Revenue)
3. In the Attribution Model dropdown, select "Linear"
4. Configure dimensions and filters based on your analysis needs

HubSpot's linear model distributes credit evenly across all interactions associated with the contact record. Like Salesforce, it cannot track anonymous pre-lead touchpoints without additional tracking technology.

Linear attribution won't revolutionize your marketing measurement overnight. But it will give you something valuable: a clear, defensible, easy-to-explain view of how multiple touchpoints contribute to revenue.

The model works best when you need holistic visibility across channels. It struggles when you need to identify and prioritize top performers. And like all native CRM attribution, it misses the anonymous journey that happens before lead creation.

For most B2B marketing teams, linear attribution serves as an excellent starting point. It protects mid-funnel content from being overlooked. It gives every campaign a fair shot at proving value. And it provides numbers you can confidently share with finance.

Ready to move beyond guesswork? Start by enabling Even Distribution in Salesforce or Linear in HubSpot. Run reports for your closed-won opportunities. See which campaigns consistently appear across multiple deals.

Then ask yourself: is equal distribution telling the whole story? Or do certain touchpoints deserve more credit than others?

That question will guide your next step toward attribution maturity.

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