Introduction: Attribution is Mostly Vibes

In B2B SaaS, marketing attribution is difficult—and arguably philosophical. (Between the two of us, we’ve worked on over a dozen different models across go-to-market teams.) At its core, we’re trying to quantify the unquantifiable: human decision-making. How do you measure the impact of an in-person event conversation versus a LinkedIn ad impression? Or the cumulative effect of brand sentiment built quietly over months?

Here’s the truth most marketing leaders won’t admit: Attribution is more art than science. It’s educated guesswork, wrapped in dashboards and dressed up as data.

And speaking as a RevOps pro steeped in Salesforce fields and martech stacks: even the most expensive attribution software often amounts to a very sophisticated game of lick-your-finger-and-stick-it-in-the-air. We see the underbelly of the "algorithms," the trade-secret weighting formulas—and we know: a lot of it is just made up.

This guide breaks down the most common attribution models, while acknowledging their inherent limitations and the vibes-based reality of modern marketing.

What Is Marketing Attribution in B2B SaaS?

Marketing attribution attempts to assign credit to the touchpoints that influence a prospect's journey to becoming a customer. It tries to answer questions like:

• Which channels are generating qualified leads?
• What content or experiences actually influence purchase decisions?
• Where should we allocate our limited marketing budget?

But here's the reality: no attribution model perfectly captures how humans actually make decisions.

The Most Common Attribution Models (And Why They're All Flawed)

1. First-Touch Attribution

👉 "We got this lead from a LinkedIn ad."

Example: A marketing team at a Series A SaaS startup notices a spike in product signups after launching a LinkedIn ad campaign. Using first-touch attribution, they assign 100% of the credit to that campaign.

Pros:

• Great for evaluating awareness channels
• Simple to implement using UTM parameters

Con:

• Completely ignores all subsequent touchpoints
• Creates a false narrative about what actually drives decisions

The Vibe Reality: That LinkedIn ad might have been the first digital touch you tracked, but what about the podcast where your CEO was mentioned? Or the billboard on the 101? Or the conversation at a conference that wasn't logged?  First-touch models create an illusion of clarity while missing most of the iceberg.

2. Last-Touch Attribution

👉 "They converted from our pricing page."

Example: A prospect downloads a pricing PDF right before talking to sales and converting. The company attributes the deal to the PDF download campaign.

Pros:

• Identifies content that appears to close deals
• Highlights conversion-focused assets

Con:

• Misses the entire journey that led to that final touch
• Overvalues bottom-funnel content that might not even be scalable

The Vibe Reality: Attributing a $100K deal to a pricing page download is like crediting the cashier for your entire grocery purchase. They finalized it, sure, but they didn't create the hunger or help you choose what to buy.

3. Linear Attribution

👉 "Let's give equal credit to every touchpoint."

Example: A B2B SaaS company selling a team collaboration tool sees a lead go through: (1) Google ad → (2) webinar → (3) pricing page. They evenly distribute credit across all.

Pros:

• Kinda easy to implement
• Recognizes multiple influences

Con:

• Assumes every touch has equal value
• A passive blog view ≠ an hour-long demo

The Vibe Reality: This model pretends that scrolling past a social post has the same impact as a 45-minute interactive webinar. It's democratic but divorced from how influence works.

4. Time-Decay Attribution

👉 "Let's favor the recent touches that pushed them over the edge."

Example: A potential customer spends 3 months exploring a B2B analytics product. The model gives more credit to recent touches, like a demo or case study.

Pros:

• Recognizes recency bias in decision-making
• Accounts for urgency-driven actions

Con:

• Early awareness-building gets drastically undervalued
• That first impression might have been the most important one

The Vibe Reality: Time-decay makes intuitive sense—recent touches are fresher in memory. But it misses how that killer blog post three months ago, or the CEO’s video on LinkedIn that might have fundamentally reframed how the prospect views your entire category or you can argue that the budget has finally been freed up. This ignores the idiosyncratic factors that influence decision making.

5. U-Shaped Attribution

👉 "Let's highlight how we got the lead — and how we closed them."

Example: A marketing ops team credits 40% of a conversion to the first interaction (SEO blog), 40% to the last (pricing page), and 20% to the middle steps.

Pros:

• Emphasizes both acquisition and conversion
• Recognizes the beginning and end of the journey

Con:

• Middle-funnel nurturing gets minimized
• Sometimes the middle is where minds actually change

The Vibe Reality: The U-shaped model creates a tidy narrative, but decision-making isn't tidy. That "minor" webinar in the middle might have been where the real connection happened.

6. W-Shaped Attribution

👉 "Give credit to the first touch, lead creation, and opportunity creation."

Example: An enterprise SaaS company tracks:

• First touch = Google search (30%)
• Lead conversion = Whitepaper download (30%)
• Opportunity creation = Demo request (30%)
• Other touches = 10% combined

Pros:

• Tracks key marketing milestones
• Acknowledges major transition points

Con:

• Arbitrarily weights "milestone" touches
• Requires pristine tracking and definitions

The Vibe Reality: W-shaped attribution tries to map clean milestones onto messy human decisions. The prospect might have mentally committed after reading your thought leadership piece, but that won't show up in your funnel stages.

7. Account-Based Attribution

👉 "Multiple stakeholders across this account engaged with us."

Example: In a 6-month sales cycle, marketing touches 5 people at a company via ads, events, and email nurture. Attribution is mapped at the account level.

Pros:

• Reflects multi-stakeholder reality
• Crucial for complex buying committees

Con:

• Extremely difficult to implement well
• Requires sophisticated tracking

The Vibe Reality: This gets closer to reality but still treats digital touchpoints as the whole story. What about the FOMO when a prospect hears three competitors are using your solution? Or the informal peer recommendation that never appears in your CRM?

The Unquantifiable Elements of Marketing Attribution

Here's what makes marketing attribution more art than science:

1. The In-Person Experience Gap

That 15-minute conversation at a conference booth might be worth 100 LinkedIn ad impressions—but how do you quantify it? The deep engagement, the nuanced back-and-forth, the human connection... these don’t fit neatly into attribution models. Yet they’re often where the real influence happens.

Especially in the wake of COVID, there’s been a powerful resurgence of live events, dinners, and happy hours. And with it, a return of something marketers forgot how to track: the human interaction glow. That magnetic resonance someone carries after a compelling conversation? It doesn’t generate a UTM code. But it absolutely accelerates trust, shortens sales cycles, and fuels word-of-mouth buying momentum.

2. The Dark Social Problem

Prospects share your content in Slack channels, forward emails to colleagues, and discuss your product in closed-door meetings you’ll never be invited to. Studies suggest up to 70% of influence happens in these “dark social” channels—completely invisible to your attribution.

Let’s talk reality: A CTO hears your name in a RevOps Co-Op thread → gets a DM with your case study → emails it to their team → someone Googles you → fills out a form.

That’s the actual lead journey.

But your CRM? It blandly reports: “Came from Organic Search.” That tidy pie chart on your board slide? Fiction. The fat “Direct Traffic” slice? It’s where all the ghosts live.

Even when you run a clean paid search campaign with a form field like “How did you hear about us?”, you'll often learn that brand familiarity didn’t originate from Google—it came from someplace completely different.

In B2B, your brand is being whisper-vetted in private Slack communities like RevOps Co-Op, Women in Sales, and Pavilion. One negative rep experience shared by a respected operator? It can ripple silently through dozens of buying committees. On the flip side, unknown or early-stage tools get evangelized every day in these networks—leading to mysterious subscriber bumps that marketing never traces back to their source.

As Viral Nation aptly put it:

“Dark social is the conversation you’re not in—and that should scare every major brand.”

Dark social isn’t just a blind spot. It’s the gravitational force warping your entire attribution universe.

3. The Multi-Touch Reality

The average B2B purchase decision involves 27+ touchpoints according to Gartner. Your attribution model likely captures maybe 30% of these at best. It's like judging a movie after seeing random 5-minute clips.

4. The Brand Halo Effect

How do you attribute the value of brand recognition? When a prospect thinks "Oh, I've heard good things about them" before engaging with your content, that perception colors everything—again, it's nearly impossible to measure.

Making Peace with the Vibes

So how do we approach attribution, knowing it's fundamentally flawed?

1. Use Multiple Models Simultaneously

No single model tells the whole story. Look at first-touch, last-touch, and multi-touch models side by side to triangulate reality. The truth is somewhere in the overlap.

2. Supplement with Qualitative Data

Simply ask your customers: "How did you hear about us?" and "What convinced you to buy?" Their answers often reveal touchpoints your attribution missed entirely.

You can use tools like Attention or Gong to search recordings or enable it as an open text field on a form. Justworks rolled out “How did you hear about us?” as an open text field for a few months on paid landing pages and learned that the point of conversion and the moment of brand discovery were often very different. Referral and Social Media played a stronger role than the attribution model was giving credit for.

3. Acknowledge the Limitations

Be transparent with stakeholders about what your models can and cannot capture. Attribution should inform decisions, not dictate them.

4. Embrace the Art

The best marketers combine data with intuition. They use attribution as a starting point but factor in the unquantifiable human elements that no model can capture.

Conclusion: Vibes Meet Data

Marketing attribution isn't about perfection—it's about clarity within constraints. The models are flawed, the data incomplete, and human decision-making stubbornly complex.

The most sophisticated marketing teams understand this fundamental truth: attribution is directional, not definitive. It provides clues, not conclusions.

Because some of your most powerful marketing moments will never show up in any dashboard. And that's okay.

If This Isn’t Enough, Try:

• Shopify’s CMO on the Science of Data Driven Marketing
• Dark Social Is Driving 95% of Your Reach — And You’re Ignoring It