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AI in the Investment Playbook: A Must-Have, Not a Nice-to-Have

Nav explains that for modern investors, AI has become embedded in every phase of the deal lifecycle. No longer just an idea or a pilot, AI is now core to how firms like Active Growth Partners source, underwrite, and operate their investments.

This shift goes beyond efficiency, it’s about using AI to find value in places traditional diligence might overlook. From automating research on customer trends to surfacing hidden patterns in financials, Nav sees AI as table stakes for forward-thinking investment firms.

Beyond Efficiency: AI as a Growth Engine Post-Close

While many investors talk about AI as a tool to cut costs, Nav believes the bigger opportunity is to drive top-line growth. He shares how Active Growth looks for ways to embed AI directly into the GTM stack of portfolio companies, creating new revenue streams and customer experiences.

Nav sees AI not just as a margin play, but as a lever for creating compounding value post-close, whether through smarter cross-sell or more data-driven pricing.

This means more precise targeting, faster deal cycles, and ultimately more conviction in the investment thesis, even in high-stakes environments.

Balancing Risk and Innovation in Deal Execution

Nav acknowledges that AI also brings a risk of hype and noise. He talks about how investors must separate real AI opportunities from the buzzwords—ensuring that any AI investment has a clear path to ROI and customer value.

For Active Growth, this means rigor around where and how AI gets deployed—focusing on real-world impact and long-term defensibility.

From Efficiency to GTM Acceleration: AI in Portfolio Operations

Post-close, Nav sees AI as a game-changer for revenue growth—not just internal efficiency. He explains how AI can inform customer segmentation, identify the best-fit go-to-market motion, and even forecast churn risk with more precision.

He frames this as a new era of portfolio management—where the goal isn’t just to maintain margins, but to unlock new pathways to growth and market leadership.

Final Thoughts

Nav Rajput’s perspective is a timely reminder that AI is no longer optional—it’s foundational. For private equity leaders, GTM strategists, and portfolio operators, the takeaway is clear: using AI to automate is only the start.

The real differentiator is using it to create new reven

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From Global Brands to Local Champions: Finding the Right Fit

Kate’s career path took her from some of the world’s biggest names to supporting local tech communities and scaling startups. She shares how the discipline and process of global brands gave her a foundation for creating customer-obsessed cultures at smaller organizations.

Her approach blends the best of both worlds—process where it matters, and flexibility where it counts.

For Kate, sales leadership is first and foremost about listening and observing. In a world obsessed with demos and metrics, she believes that empathy and curiosity are what truly build trust and unlock opportunity.

She shares how this mindset has helped her teams not only close more deals, but create genuine, lasting partnerships.

Final Thoughts

Kate Parashina’s story is a reminder that great GTM leadership isn’t about having all the answers - it’s about creating space for others to show up as themselves.

From building brand-consistent processes to nurturing authentic relationships, Kate’s approach is equal parts discipline, empathy, and impact. If you’re looking for a perspective that blends global experience with local heart, this episode is a must-listen.

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The GTM Model as the Execution Layer of Revenue Architecture

The GTM Model is where all the theory becomes tangible. While the first five models of Revenue Architecture define the who, what, and why of your go-to-market, the GTM Model defines the how. It’s the layer where strategy becomes process, and process becomes pipeline.

Mats explains that many GTM issues aren’t due to poor execution, but to misapplied or disconnected motions. When done right, the GTM Model becomes the operating system for repeatable, scalable revenue.

Motion-Segment Fit: Choosing the Right Motion for the Right Job

GTM success hinges on what Mats calls motion-segment fit, aligning the right sales or marketing motion with the right type of customer and opportunity. He warns that even strong motions fail when misapplied to the wrong segment.

Rather than chasing trends like PLG or outbound, companies need to diagnose customer size, sales cycle complexity, and deal velocity, then match motions like No Touch, Low Touch, or High Touch accordingly. The GTM Model provides that clarity.

Enablement is the Make-or-Break for GTM Success

Strategy sounds good in a workshop. But GTM lives or dies in execution. Mats points out that most breakdowns happen not because of poor planning, but because frontline teams weren’t enabled to run the motion.

For a GTM Model to work, every motion needs content, workflows, CRM triggers, and training mapped to it. Otherwise, you’re just handing your team a playbook they can’t run.

RevOps as the GTM Engineer

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In Season 4, Episode 4 of Force and Friction, we continue our Winning by Design Revenue Architecture Series with Jos de Wit, certified Revenue Architect and founder of MNTM.

Jos has helped SaaS and RevOps teams across Europe and North America dismantle faulty assumptions, realign broken processes, and build go-to-market systems that scale with precision.

In this episode, Jos delivers a masterclass on what it really means to “architect” your revenue engine, from foundational data models to unified customer journeys, segmentation, handoffs, and the role of AI in automation.

If your GTM strategy feels like it’s held together with duct tape and dashboards, this conversation will show you how to rebuild it from first principles.

What is the Data Model?

Think of the Data Model as the blueprint of your GTM engine. It maps out what should be happening, how often, how well, and how fast, across every part of the customer journey. 

It’s built on three core metric types:

• Volume Metrics (VM)
  Volume Metrics tell us how much is happening at each key stage of the GTM journey. They’re often counted in units (leads, opportunities, deals) or revenue (MRR, ARR, LTV), and serve as the raw material of your pipeline. These are the hard numbers. But without context, they mean little. That’s where conversion comes in.
• Conversion Metrics (CR)
  Conversion Metrics show how well each stage turns into the next. They tell you how efficient your GTM engine is, from top-of-funnel to onboarding to expansion. These are expressed as percentages. Drop-offs between CRs signal friction. Weak CR4? It’s your sales process. Poor CR6? Onboarding or product value isn’t landing.
• Velocity Metrics (Δt)
  Velocity Metrics measure time. They capture how fast leads and customers move through each phase, and where things might be getting stuck. These are critical for improving cycle time, onboarding experience, and expansion timing.
• If your Δt4 is too long, you burn pipeline. If your Δt6 drags, onboarding churn follows. Velocity fuels scale.

Each metric connects directly to a key moment in the Bowtie model, which includes both acquisition (pre-sale) and expansion (post-sale).

Together, these metrics allow RevOps and GTM leaders to not only measure performance, but diagnose what’s breaking, where friction lives, and how to optimize sustainably.

These three categories—Volume, Conversion, and Velocity—form the operational core of your GTM engine. You can’t just focus on one. You need to measure them together, look for gaps, and run diagnostics continuously.

Because here’s the truth:

Growth isn’t random. It’s architected.

And the architecture starts with a model that actually mirrors how your revenue factory works.

Here are the core areas we discuss in today's episode:
Architect Before You Execute: Why GTM Starts with Data Design

Jos introduces the foundational mindset of Revenue Architecture: You don’t start with the funnel, you start with the Bowtie.

The Hidden GTM Risk: Bad Assumptions at the Core

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From Crisis to Breakout: Franz’s Unexpected Journey into GTM

Franz shares how a failed startup and a global pandemic unexpectedly led him into the Hopin rocketship, where he learned to build under pressure and follow signals others missed, like the rise of agencies during virtual event chaos.

“We didn’t have enough capacity. Agencies had too much. Partnerships became the bridge.”

Lessons from Hopin: The 1,000 Leads a Day Playbook

At the height of COVID-19, Hopin was fielding over 1,000 inbound leads per day. Franz describes how the team scaled fast, iterated faster, and turned chaos into clarity by leaning into rapid-fire experimentation and partner ecosystems.

The Myth of ‘Too Early’ for Partnerships

Through experience and community research, Franz debunks the idea that partnerships come after product-market fit. He reveals why early-stage companies that start small and stay focused can see huge long-term leverage.

Barney Partnerships and the Customer Blind Spot

Franz warns against “Barney Partnerships” feel-good, founder-to-founder deals that never deliver. The biggest red flag? No customer overlap.

Operational Rigor: The 15-Minute Partner SLA

Drawing on a standout case study from Olga Laikova at monday.com, Franz highlights how operational excellence, like responding to partners in 15 minutes can lead to measurable revenue gains and become a true differentiator.

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From WordStream to Customers.ai: A Shift Toward Accuracy-First Marketing:

Larry shares his journey from building WordStream into a $150M exit to launching Customers.ai, based on the insight that remarketing and website visitor identity are the true low-hanging fruit for marketers, if the data is trustworthy.

The Big Problem: Why Visitor ID Technology Hasn’t Gone Mainstream

Visitor ID sounds amazing, but the industry hasn’t delivered. Larry breaks down the painful truth:

• Traditional visitor ID vendors have 70–95% error rates.
• Most businesses churn within 4–5 months because the data simply isn’t accurate enough.
• Bad visitor ID data harms deliverability, poisons CRM systems, and sabotages ad campaigns.

• Tanks email deliverability
• Corrupts CRM and marketing databases
• Destroys AI ad training models on platforms like Google and Meta

Their in-house model delivers 70–85%+ accuracy consistently, changing the game for visitor identification.

Proof in Performance: The Jordan Craig Case Study

Larry shares the powerful Jordan Craig case study undertaken using Customers.ai:

• Customers.ai delivered a 2.79% conversion rate from visitor ID leads.
• Competitors delivered less than 0.01% to 0.24%.
• Revenue per ID was 15x higher using Customers.ai data.

The Future of Visitor ID: Infrastructure, Not an Add-On

Larry believes visitor ID has been niche because of bad data—but high-accuracy solutions like Customers.ai will soon become core infrastructure for every serious GTM team.

As the technology matures, it could become as essential as CRM or paid search..

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Here are the core areas we discuss in today's episode:

Bridging the GTM Divide: Conversations First, Revenue Follows

Jason’s journey from nonprofit work to sales and partnerships taught him the long-game value of connection. His mantra: revenue begins with conversations—and conversations require trust.

“Partnerships are a long game. They’re a compounding motion that starts with a conversation, not a contract.”

Rather than chasing quick hits, Jason emphasizes the importance of ecosystem relationships as pipeline multipliers and trust accelerators.

The Arcadia Vision: Unifying Revenue Teams through Harmony:

Born from a desire to eliminate GTM silos, Arcadia is Jason’s answer to a misaligned revenue world. Rather than treating Sales, Marketing, Customer Success, and Partnerships as separate functions, Arcadia’s mission is to bring harmony over handoffs.

“The Arcadia experience is about slowing down to speed up—creating space for GTM leaders to reconnect, realign, and build something better together.”

The initiative also blends nature, intention, and leadership development to shift how we show up in the boardroom and the field.

The Side-of-Desk Problem: Why Partnerships Need a Seat at the Table:

Jason challenges the industry’s tendency to treat partnerships as an afterthought, offering a clear distinction between companies that are “partner-curious” versus those that are “partner-committed.”

“If partnerships are going to work, they can’t be one person's hustle. They need executive support, systems, and shared success metrics.”

Without alignment from Sales and RevOps, partnerships will stay siloed—and revenue potential will remain untapped.

Injecting Partner Plays into Outbound:

The Three I’s Framework:

Jason introduces a repeatable, low-lift method for infusing partnership value into existing sales plays: the Three I’s:

• Intel - Partner-driven context and insight on key accounts
• Intros - Warm handoffs that replace cold outreach
• Influence - Advocacy and trust that accelerates deals

“It’s not about replacing what works - it’s about making what works, work better through the partner ecosystem.”

This model helps GTM teams reduce friction, improve pipeline velocity, and win with more confidence.

Partner Enablement is Internal Too:

One of Jason’s strongest points: most partner motions fail not because of poor strategy—but because internal teams don’t know how to work with partners. He advocates for regular enablement across sales, marketing, and CS to help them:

• Understand the partner motion
• Know when and how to involve a partner
• See clear attribution to deals

“The biggest lift in partnerships comes when internal sellers understand how to leverage partner plays naturally.”

Build Ecosystems Around Customer Need, Not Cool Logos:

Not all partners are created equal. Jason urges teams to build ecosystems intentionally, starting with what your customers actually want, and who they already trust.

“Your best ecosystem strategy starts with customer insight. Where are they already spending time? Who do they already trust? Build from there.”

This approach shifts the partnership conversation from “Who do we want to work with?” to “Who adds the most value to our customer journey?”

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Why Traditional CRMs Don’t Work for Partnerships

Fredrik opens with a personal revelation: despite years of working with top-tier CRMs, partnerships teams were still stuck managing workflows with spreadsheets and manual workarounds.

JourneyBee serves as middleware between organizations and their partners, automating the messy admin and bringing transparency to co-selling motions.

Partnerships Deserve Their Own Stack:

Partnerships are evolving—but the tools haven’t. Fredrik argues that partnerships require a designated tech stack just like sales, marketing, and support.

• CRMs handle customer workflows.
• Marketing automation serves content and lead gen.
• But partnerships? Still underserved and duct-taped together.

JourneyBee changes that by offering a dedicated platform for tracking, managing, and scaling ecosystem-led GTM strategies.

The Rise of Buyer-Led GTM: Flipping the Traditional Sales Model:

So, what is buyer-led GTM, and how does it differ from the seller-led model we’ve relied on for decades?

Traditional Seller-Led GTM:

• Sales reps blast emails, calls, and LinkedIn messages
• Buyers get flooded with unsolicited outreach
• 95% of buyers aren’t ready to purchase—but they’re still getting pitched

The New Buyer-Led GTM:

• Buyers raise their hand when they are actively looking
• They conduct their own research instead of relying on vendor messaging
• Sellers earn trust through valuable, unbiased content and partnerships

Santosh explains how AI-powered buyer research tools will replace traditional lead-gen tactics, ensuring buyers get the insights they need without spammy outreach.

AI-Powered Agents: The Future of GTM is Automated & Intelligent:

As AI advances, agents will begin replacing manual outreach and traditional sales reps. Santosh predicts that:

• AI agents will replace SDR outreach – Instead of cold emails, AI will handle buyer engagement
• Buyers will use AI for vendor research – They’ll get real-time, unbiased insights before making decisions
• Seller & buyer agents will negotiate deals – AI-powered assistants will interact to simplify transactions

The implication? Sales teams must adapt now. Companies that don’t integrate AI-driven research into their GTM strategies will struggle to compete.

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Unlocking Hidden Pipeline with Data-Driven Co-Selling:

Many SaaS companies struggle to effectively leverage partnerships because of manual processes, disconnected data, and unclear alignment between partner sales teams.

Cassandra explains how PartnerTap enables businesses to:

1: Map millions of accounts to uncover new sales opportunities.
2: Identify overlap between partners’ install bases.
3: Automate warm introductions between sales teams.
4: Track co-selling efforts with clear revenue attribution.

The key takeaway? Stop treating partners like commission-only resellers, real partnerships are built on shared pipeline and mutual success.

The Give-to-Get Mentality - Playing the Long Game in Partnerships:

Many companies approach partnerships with a "What can I get?" mindset, which often leads to short-term, transactional relationships. Cassandra flips the script, advocating for a "Give-to-Get" approach.

She shares a powerful example from Dreamforce, where PartnerTap, as a startup, fed leads to a much larger partner, which later turned into one of their biggest customers.

The lesson? Think long-term. Partnerships should be built on trust, not immediate transactions.

Fempire: Creating an Ecosystem for Women in Leadership:

Beyond PartnerTap, Cassandra is passionate about shifting capital toward women-led businesses. She founded Fempire, a growing network of women in leadership, to create opportunities for female executives and founders.

What started as a small dinner with 8 women turned into a movement backed by Microsoft, Nvidia, and ServiceNow.

The Fempire dinners help women leaders forge powerful connections, drive new business, and support each other in navigating corporate and startup challenges.

The Evolution of Partnerships: From Resellers to Ecosystem-Led Growth:

Cassandra breaks down how the nature of partnerships has fundamentally changed, shifting from reseller-based models to ecosystem-driven co-selling strategies.

• Old Model: Resellers sell software and receive a commission.
• New Model: Partners actively collaborate on sales cycles, sharing data and pipeline.

She emphasizes the need for data-driven partner collaboration to maximize deal flow and influence buying decisions.

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The Evolution of GTM: From Relationship-Driven Sales to AI-Driven Intelligence:

Over the past 15 years, sales has evolved from a relationship-based model to a data-driven, automated approach. Santosh shares how he witnessed this transformation firsthand while working with ZoomInfo and Apollo, helping sales teams leverage real-time data and automation.

While automation initially helped sales teams become more efficient, it has now reached a breaking point—buyers are bombarded with outreach, and response rates are plummeting.

The Sales Saturation Problem: Why Traditional GTM is Breaking Down:

Sales teams today have more data and automation than ever before, yet 79% of reps are missing their quota (Epsta research, 2024). Why?

1: Too many sellers, not enough buyers – Thousands of companies are sending millions of outreach messages daily.
2: Buyers are overloaded – 20+ calls and 100+ emails a day have made outreach ineffective.
3: Trust is declining – With so much noise, buyers no longer believe in vendor-driven messaging.

This shift has opened the door for buyer-led GTM—a strategy where buyers drive the process and sellers must earn trust to gain engagement.

The Rise of Buyer-Led GTM: Flipping the Traditional Sales Model:

So, what is buyer-led GTM, and how does it differ from the seller-led model we’ve relied on for decades?

Traditional Seller-Led GTM:

• Sales reps blast emails, calls, and LinkedIn messages
• Buyers get flooded with unsolicited outreach
• 95% of buyers aren’t ready to purchase—but they’re still getting pitched

The New Buyer-Led GTM:

• Buyers raise their hand when they are actively looking
• They conduct their own research instead of relying on vendor messaging
• Sellers earn trust through valuable, unbiased content and partnerships

Santosh explains how AI-powered buyer research tools will replace traditional lead-gen tactics, ensuring buyers get the insights they need without spammy outreach.

AI-Powered Agents: The Future of GTM is Automated & Intelligent:

As AI advances, agents will begin replacing manual outreach and traditional sales reps. Santosh predicts that:

• AI agents will replace SDR outreach – Instead of cold emails, AI will handle buyer engagement
• Buyers will use AI for vendor research – They’ll get real-time, unbiased insights before making decisions
• Seller & buyer agents will negotiate deals – AI-powered assistants will interact to simplify transactions

The implication? Sales teams must adapt now. Companies that don’t integrate AI-driven research into their GTM strategies will struggle to compete.

Learn more at www.forceandfrictionpodcast.com