From MQLs to Buying Groups: How Palo Alto Networks Modernized Its GTM Engine
A conversation with Jeremy Schwartz, Sr. Manager, Global Lead Management & Strategy at Palo Alto Networks
In a rapidly evolving B2B landscape, where multiple stakeholders now shape buying decisions, relying solely on traditional MQL-based models no longer cuts it. At Palo Alto Networks, Jeremy Schwartz, Senior Manager of Global Lead Management & Strategy, has been spearheading a transformation—shifting the company from an outdated lead-centric model to a buying group-focused motion.
This move hasn’t just modernized their go-to-market strategy; it’s delivered tangible business results. In this blog, we break down Palo Alto Networks’ journey, the challenges they faced, and the playbook they followed to build a scalable, revenue-generating buying group engine.
The Problem: A Funnel Full of Waste
Jeremy had a front-row seat to the inefficiencies of the MQL model. From his experience as a campaign strategist and now as a lead management leader, one thing was clear: MQLs were often vanity metrics.
“You drive great MQLs that either don’t convert or get thrown back. The lowest person on the totem pole is often the MQL—and sales doesn’t want to waste time on them.” – Jeremy Schwartz
Campaigns generated leads, but many never matured into opportunities. Even when they did, sales would frequently reject them, seeing little value in a lone networking admin reaching out.
The funnel was leaking at every stage.
The Aha Moment: Forrester’s B2B Revenue Waterfall
The real turning point came when Jeremy attended a Forrester conference and learned about their B2B Opportunity Waterfall model. It flipped the focus from individuals to buying groups.
Inspired, Jeremy returned and pitched the idea internally. His leadership responded with: “Run a pilot and show us what you find.”
Phase 1: Building the Pilot
Palo Alto’s pilot kicked off with a 3-month research phase. The team mapped out what people, processes, and systems would be impacted, then aligned with Forrester to tailor the buying group model to their environment.
People First
They recruited BDRs across multiple GTMs (product go-to-markets), geographies, and segments to get a representative pilot group. At the same time, they analyzed two years of closed-won data to identify real buying group personas.
“You don’t need to hire a consultancy to identify your buying groups. Look at your closed-won data—it’s all there.” – Jeremy Schwartz
Process Discovery
They identified two key BDR motions:
Create new opportunities with multiple stakeholders.
Add new engaged personas to existing opportunities.
Both processes, however, were painfully manual—10+ steps each.
Phase 2: Launch and Learn
They ran the pilot for a full quarter. Initial triggers still came via MQLs, but BDRs were trained to:
Check intent platforms (like Demandbase)
Identify other engaged personas at the same account
Multi-thread their outreach
This approach led to:
More meetings booked
Better response rates (especially when referencing colleagues)
Higher acceptance by AEs (thanks to meetings involving multiple roles)
“Mentioning a colleague in an outreach email is real personalization. And it worked.” – Jeremy Schwartz
The kicker? Deals with multiple stakeholders started closing—faster and at higher values.
They presented the early pilot results to their CMO. The response?
“That’s cute.”
So the team partnered with data science to extrapolate the results across all opportunities. The model predicted a 13% revenue lift—assuming full buying group coverage.
That got attention.
“Suddenly, our CMO said, ‘Do more of that.’” – Jeremy Schwartz
Phase 3: Automation and Scale
To make the process scalable, they built automation in their internal cloud app:
When a lead was accepted by a BDR, the system automatically identified other engaged personas from that account.
These individuals were assigned to the same BDR for follow-up.
Adding someone to an existing opportunity became a one-click process that even notified the AE.
They also created custom dashboards to track metrics like:
Number of opportunities with buying groups
Deal size and velocity
Incremental pipeline created
Coverage across accounts and products
By the end of their fiscal year, these automations were live globally across all BDR teams.
Results That Mattered
Here’s what Palo Alto Networks achieved by moving to a buying group model:
| Metric | Improvement |
|---|---|
| Deal Size | 2.6x increase (in certain segments) |
| Conversion to Pipeline | Significant lift over MQL-only opps |
| Closed-Won Rates | Higher for opportunities with buying groups |
| Pipeline Quality | Larger, multi-threaded deals |
| Coverage | 12% of Q2 opps had buying groups; target = 15% |
They also introduced new marketing metrics:
Campaign-to-Opportunity: Replacing MQL-to-Opportunity
Buying Group Coverage: How many personas per deal
Buyer Representation Spread: Ensuring campaigns target multiple personas, not just admins
“Our leadership is still MQL-obsessed, but now we’re reporting incremental pipeline and seeing influence in closed-won deals.” – Jeremy Schwartz
Building the Future: A Signal-Based Scoring Model
Palo Alto’s next frontier? Replacing lead scores with signal-based models using four dimensions:
Fit: ICP match
Intent: 1st, 2nd, and 3rd-party signals
Engagement: Website visits, downloads, event participation
Completeness: Buying group coverage per account
“If three or more people are showing up from an account, with different titles, that’s a signal. You don’t wait for an MQL to act.” – Jeremy Schwartz
Lessons Learned: What Jeremy Would Do Differently
Push for executive alignment earlier
Involve campaign marketers sooner after pilot results
Don’t overdesign—start small, learn fast, course-correct
Accept the reality of system complexity (especially in older enterprises)
“Martech stacks are like Rome—layers upon layers built by different people over time. Nothing is clean.” – Jeremy Schwartz
Advice for Companies Starting the Journey
Start small with a controlled pilot.
Use your own data to identify buying groups.
Get BDRs involved first—they’re closest to pipeline creation.
Automate before scaling.
Show revenue impact, not just lead volume.
“Even if your leadership still chases MQLs, show them better conversion, deal size, and real revenue impact. That’s what moves the needle.” – Jeremy Schwartz
Final Thoughts
Palo Alto Networks didn’t just adopt a trendy new model. They operationalized a seismic shift in how revenue is created—by recognizing buying groups as the real unit of conversion in B2B.
Whether you’re just starting or halfway through your own transformation, Jeremy’s journey is a masterclass in strategy, persistence, and practical execution.
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More Resources
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