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Let's start with the #3 edition of the Content Marketing Challenges series: How to showcase the impact of content on the pipeline based on basic attribution.

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If you’re in B2B SaaS long enough, you must have heard this question: “Okay, but how much pipeline did content influence?”

If you often struggle to answer this question, this edition is for YOU! I have talked about it all in bits and pieces before. This time I am compiling it all in this same edition.

Today, I’ll show you how to break it down across:

• TOFU
• MOFU
• BOFU
• Thought-leadership

Using nothing more than GA4, GSC, CRM data, AI-search tracking, and a simple sheet (Template below).

📚 If you have specific questions related to content attribution: Book a 30-minute consultation call with me!​

First thing first: Stop measuring “Content.” Start measuring funnel behavior.

The biggest mistake I see (and have made in the past): marketers trying to attribute pipeline to content as a whole. Wrong framing.

Pipeline influence shows up differently at each stage:

• TOFU seeds accounts
• MOFU shapes evaluation
• BOFU accelerates deals
• Thought-leadership reduces friction

If you measure them all using “leads generated,” you’ll underreport 75% of your impact.

So the strategy is simple: match the metric to the job of the content.

TOFU: Prove it brings the right accounts in

TOFU’s job is not conversion. It’s a qualified entry.

What to track strategically:

1. Which blogs are driving first-touch sessions for accounts that later enter CRM?
2. Are those blogs ranking for category-shaping queries (including AI Overview visibility)?
3. Is organic growth happening on pages aligned with your ICP?

For example, if a blog ranks for “topic cluster SEO” and appears in AI Overview, that’s not just traffic. That’s being part of early research conversations.

Now the key move: once a month, pick 10 new pipeline accounts and check their first-touch page. If the same TOFU pages appear repeatedly, that’s evidence of pipeline seeding.

You don’t need perfection. You need repetition.

That’s how you show TOFU influence without pretending it closes deals.

💭 Personally, I am not a big believer in TOFU content. I wrote a post on why TOFU should be replaced by Thought-leadership. You might want to read it!​

MOFU: Prove it changes buyer intent

MOFU is where people move from “interesting” to “we should evaluate this.”

This is where engagement depth matters more than volume.

What to look for:

• Higher-than-average engagement time on educational content
• Resource downloads from strategic blogs
• Users moving from educational pages to product or comparison pages
• Repeated visits within 7–14 days

If a blog has lower traffic but high engagement and consistent conversions, that’s not underperformance. That’s consideration-stage gravity.

A strong MOFU signal looks like this: Blog → Newsletter → Return Visit → Demo Page View

If that pattern exists, MOFU is influencing the pipeline. Your job isn’t to attribute revenue to the blog. It’s to show it sits in the decision path.

BOFU: Prove acceleration, not just conversion

BOFU is the easiest layer to validate — but only if you ask the right question.

The right question is NOT: “Did this page convert?”

You should rather ask: “Did this page show up in deals that moved forward?”

Here’s what works in practice:

1. Review 5–10 progressing deals each month.
2. Check which content was visited during the open pipeline.
3. Ask AEs which content helped internally (case studies, ROI blogs, comparisons).

If the same 2–3 assets repeatedly show up in progressing deals, that’s pipeline acceleration.

Want something stronger? Compare deal velocity between deals that used BOFU content and those that did not. Even a 10–15% faster close time is powerful proof.

BOFU rarely creates demand. It removes friction. That’s measurable.

📚 I have covered BOFU Content attribution in detail in my e-book. Check it out here!​

Thought-Leadership: Prove category authority

This is where I have struggled a lot because the impact is indirect. But indirect does not mean unmeasurable.

Thought-leadership affects:

• Branded search growth
• Direct traffic trends
• LinkedIn-driven inbound
• AI citations for opinion-based queries
• Sales credibility in calls

✅ If LinkedIn carousels consistently drive subscribers and inbound leads, that’s not “engagement.” That’s demand capture.

✅ If branded queries increase month-over-month after consistent thought-leadership publishing, that’s brand gravity.

✅ If prospects mention “I saw your LinkedIn post” in CRM notes, screenshot it. That’s attribution evidence.

You don’t need volume. You need documented influence.

Build evidence stacks

Attribution without expensive software is not about precision. It’s about pattern recognition.

You build an evidence stack across:

• Entry (TOFU)
• Depth (MOFU)
• Movement (BOFU)
• Trust (Thought-leadership)

When you see patterns like:

• The same blog appears in first-touch for new accounts
• The same MOFU asset appears in assisted conversions
• The same BOFU page appears in progressing deals
• Branded search is increasing alongside LinkedIn momentum

That’s pipeline influence.

What leadership really cares about (Especially in startups)

They care about:

• Are better accounts entering?
• Are deals moving faster?
• Are sales using the content?
• Is brand authority increasing?
• Are we seeing more inbound vs outbound dependency?

And yes — the template!

The sheet is just documentation.

It helps you:

• Track traffic shifts
• Identify high-impact pages
• Monitor AI visibility
• Tie channels to leads
• Assign fixes and owners

But the strategy comes first.

• Measure behavior
• Spot patterns
• Document influence.

That’s basic attribution done properly.

🗃️ More resources for content marketers from SaaS Splash Bulletin Archive

• ​What metrics should you track throughout your blog lifecycle?​
• ​A Practical Method to Validate BOFU’s Pipeline Influence​
• ​5 Different ways content marketers can use Google Analytics Data to their favor (+Steps)​

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Onwards and upwards,

Sreyashi

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