Ryan Milligan's team at QuotaPath hit 100% blended quota attainment eight of the past ten quarters. The way they got there wasn't by adding headcount. It was by looking at every step in the funnel where a rep was spending time on something that wasn't uniquely human, and putting AI on it. The result: reps went from spending 25% of their time selling to closer to 50%, and ARR per rep tripled.

In this episode, Eddie Reynolds sits down with Ryan Milligan, CRO of QuotaPath, for a conversation on how his team uses Momentum to auto-update 75+ CRM fields from call recordings so reps can carry 40 deals instead of 20, the AI-powered multithreading play that gets senior stakeholders into deals on day 3 instead of day 73, and why the early "AI slop" false starts almost derailed the whole thing.

Resources Mentioned in This Episode:

GTM Ops Frameworks

00:22 - The results: 3x ARR per rep, 40% higher ASP, doubled win rate

01:37 - From data science to rev ops to CRO

03:41 - Reps spend 25% of their time selling — how to double it

07:34 - Team structure and sales motion at QuotaPath

08:35 - Is AI easier to implement in high-velocity sales?

13:29 - How Momentum auto-updates 75+ CRM fields from call data

16:49 - Why those 75 fields matter: the handoff problem

21:50 - Carrying 20 deals vs. 40 deals

24:15 - Prompts are everything and data for data's sake is noise

28:53 - What is Dust and how the micro-agents work

35:20 - AI-generated business cases and ROI narratives

42:27 - The multithreading play: day three vs. day 73

45:15 - Hallucinations and where to accept the risk

47:12 - The two things that drove the most impact

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GTM STRATEGY & AI ENGINEERING FOR B2B TECH

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Duane Dufault was staring at a trial registration flow that took ten days to get a lead in front of a rep, attribution data that was 80% wrong, and a founder who was ready to shut off marketing based on numbers that weren't real. He could have started layering AI on top of all of it and joined the chorus. Instead, he spent six months fixing the plumbing. The result: ACV up 30%, sales cycles cut by 30 to 40 days, and a foundation that actually made AI work when he finally turned it on.

In this episode, Eddie Reynolds sits down with Duane Dufault, CRO of Time Doctor, for a conversation on how he drove a 30% ACV increase and cut sales cycles by 30 to 40 days in six months, why none of the AI work that followed would have been possible without rebuilding the foundation first, how his team uses AI prep agents to generate showstopper discovery questions, and the black swan churn problem he's trying to solve next.

Resources Mentioned in This Episode:

GTM Ops Frameworks

00:22 - The story: 30% higher ACV and 30-40 fewer days in the sales cycle

02:09 - Finding the biggest domino to knock down first

06:13 - Speed to lead was ten days and why

09:57 - 80% of attribution was wrong and the founder almost killed marketing

14:52 - Golden BBs, not silver bullets

16:38 - ICP as a living document that shifts every six months

25:44 - Use case over ICP definition

34:36 - Nothing in AI would have been possible without the foundation

35:43 - 50% of your time should be coaching

39:43 - AI prep agents and showstopper discovery questions

41:34 - The black swan churn problem: negative intent above your champion

46:40 - Why the CRO has to roll up their sleeves on AI

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GTM STRATEGY & AI ENGINEERING FOR B2B TECH

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Sangram Vajre has been asking rooms full of CEOs and revenue leaders the same question for the past year: how many of you are using AI? Every hand goes up. How many of you are seeing an impact? Every hand goes down. The disconnect isn't that AI doesn't work. It's that companies are layering it on top of a foundation that was never built in the first place. And no amount of copilots, agents, or automation is going to fix a broken ICP, heroic sales culture, or a go-to-market team that doesn't operate as a team.

In this episode, Eddie Reynolds sits down with Sangram Vajre, CEO of Go to Market Partners, former CMO at Pardot/Salesforce, and co-founder of Terminus, for a conversation on why 99% of companies are using AI for efficiency instead of effectiveness, the CMO who got fired three weeks after posting record pipeline because it was built on the wrong ICP, five years of research revealing the same three problems killing every go-to-market org, and why the foundation has to come before the technology every single time.

Resources Mentioned in This Episode:

GTM Ops Frameworks

00:27 - The question that makes every hand go down

03:21 - Using AI to grow vs. using AI to cut costs

08:26 - Efficiency vs. effectiveness: 99% are focused on the wrong one

11:00 - Phase one vs. phase two AI and the foundation problem

13:07 - The GTM Operating System: eight questions across a thousand companies

25:50 - $35M pipeline, fired three weeks later

29:41 - Only 28% of pipeline is ICP fit

33:28 - The top three GTM problems that haven't changed in five years

41:37 - Heroic sales as the clearest sign of a broken foundation

44:11 - Revenue per employee as the AI impact metric

48:14 - Service-as-a-software: the model that's booming while SaaS struggles

52:08 - Do we still need Salesforce?

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GTM STRATEGY & AI ENGINEERING FOR B2B TECH

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More than half of net new revenue last year came from existing customers. Yet most companies still treat expansion as a side effect of good relationships instead of a deliberate, measurable motion with its own process, capacity plan, and target list. The reason is simple: expansion is harder to measure than new business. There's no clean CAC payback formula for convincing your CFO to fund more CSMs, and the whitespace data your reps need to have intelligent conversations is probably sitting in a backend system they've never seen.

In this episode, Eddie Reynolds and Rachael Bueckert break down how to build a real expansion engine, starting with why ICP needs to account for retention and expansion potential and not just acquisition ease. The conversation covers how Salesforce doubled customer spend within the first 12 months and the playbook behind it, product and stakeholder whitespace analysis, how to build a capacity plan for expansion the same way you would for new business, and why the crawl-walk-run version of customer health scoring is a CSV and a red-yellow-green column.

Resources Mentioned in This Episode:

GTM Efficiency Pyramid Framework

GTM Ops Frameworks

01:28 - Why expansion gets ignored even though it's over half of revenue

04:52 - Where the execution bottleneck actually lives

06:19 - Healthy vs. unhealthy customers: two completely different playbooks

07:38 - Redefining ICP for expansion, not just acquisition

10:17 - How Eddie validated USC's ICP using nine years of customer data

19:43 - How Salesforce doubled customer spend in the first 12 months

22:29 - Product whitespace, stakeholder whitespace, and the CFO play

30:06 - What teams miss when they think they've already mapped expansion

33:17 - Single product vs. multi-product: why expansion looks completely different

39:06 - Who should own expansion and how to inspect it

41:07 - The expansion layer of the GTM Efficiency Pyramid

55:13 - Why AI can't replace the institutional knowledge problem

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GTM STRATEGY & AI ENGINEERING FOR B2B TECH

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Michael Maimone walked into Lucid Link expecting to build on top of what was already there. The company had product-market fit, real market pull, and was growing. But when he looked under the hood, there was no segmentation model, no defined ICP tied to actual data, and reps were fishing in each other's ponds. Junior reps were working enterprise accounts while strategic reps chased mid-market deals. The data couldn't tell him what was working because the foundation underneath it had never been built.

In this episode of CRO Stories, Rachael Bueckert sits down with Michael Maimone, CRO of Lucid Link, for a conversation on what it took to rebuild the go-to-market engine underneath a company that was already moving fast, the data modeling exercise that narrowed 200,000 accounts down to 50,000, how fixing segmentation drove a 23% win rate increase and 20% higher ASPs, the 30 enterprise MSAs that were sitting untouched, and why his biggest lesson was "don't start in the middle."

Resources Mentioned in This Episode:

GTM Ops Frameworks

00:22 - Intro to Michael Maimone and Lucid Link

01:14 - What he thought the job was vs. what it actually was

03:51 - No segmentation: the first thing that wasn't there

05:36 - How bad segmentation corrupts every metric downstream

08:47 - Six months to get a clean baseline

10:31 - Rebuilding ICP from closed-won and closed-lost data

12:46 - 30 enterprise MSAs sitting untouched

17:18 - Capacity modeling: working backwards from the AOP

18:45 - 200K accounts narrowed to 50K

24:57 - 23% win rate increase and 20% higher ASPs

26:47 - Pipeline Council and the dropped trade show lead list

34:42 - "Don't start in the middle"

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GTM STRATEGY & AI ENGINEERING FOR B2B TECH

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Amy Konary coined the term "SaaS" when she was an industry analyst at IDC. She sized the first market at $40 million, watched it grow into a multi-hundred-billion-dollar industry, and spent nearly two decades advising the companies that built it. Now she's watching the same dynamics that killed the perpetual license model start to eat SaaS from the inside: 6x renewal increases that customers won't absorb, AI features nobody's adopting fast enough to justify the price hike, and a generation of buyers who are starting to ask whether they could just build it themselves.

In this episode, Rachael Bueckert sits down with Amy Konary, SVP of Marketing at Zuora and founder of the Subscribed Institute, for a conversation on why the extractive SaaS pricing model is hitting a wall, what symbiotic business models actually look like in practice, how to iterate on pricing without bloating your product catalog, the five-stage subscription maturity model she's used with hundreds of companies, and why your competitive moat matters more right now than your AI roadmap.

Resources Mentioned in This Episode:

GTM Ops Frameworks

01:19 - Intro to Amy Konary and how she coined "SaaS"

08:15 - Why the extractive pricing model is at its breaking point

10:39 - The shift to hybrid: platform fees, usage, and outcomes

12:49 - Trust architecture and the relationship fundamentals behind retention

19:02 - Why customers aren't adopting AI features fast enough

30:49 - AI features that are actually working right now

39:13 - Who should own pricing and how to iterate without chaos

42:07 - Why hybrid monetization models are so hard to operationalize

53:00 - The five-stage subscription maturity model

01:01:05 - What CROs should be paying attention to: your competitive moat

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GTM STRATEGY & AI ENGINEERING FOR B2B TECH

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Every CRO knows that retaining customers is cheaper than acquiring new ones. But when it comes time to ask the CFO for budget to hire more CSMs or invest in retention programs, the conversation stalls. New business ROI is simple math. Customer success ROI is not. The numbers are always moving, attribution is murky, and the CFO is looking at you wondering whether that $500K spend is actually going to move anything or whether the product team would have fixed it anyway.

In this episode, Eddie Reynolds sits down with Ben Murray, The SaaS CFO, to break down exactly how to quantify the ROI of customer success investments from the perspective of the person who actually approves the budget. The conversation covers where CS should sit on the P&L and why it matters, the simple formula for comparing a CS investment against the retention revenue it would protect, why the compounding effect of saved revenue changes the math entirely, how CFOs actually evaluate the pitch when the data isn't perfect, and where to set the payback bar for CS the same way you would for new business.

Resources Mentioned in This Episode:

Quantifying Investments in Customer Success and Retention (Ben Murray)

The SaaS CFO

GTM Ops Frameworks

00:36 - Why customer success is always underfunded

01:46 - Why CS ROI is harder to calculate than new business

05:38 - Where CS belongs on the P&L

07:40 - Splitting CS from account management

14:13 - The simple ROI formula: $500K spend vs. $5M saved

23:17 - Magic number, rule of 40, and the high-level barometers

27:36 - Breaking down the retention math step by step

32:37 - How CFOs evaluate the pitch when data isn't perfect

36:13 - Setting the payback bar for CS investments

40:18 - Weighted average cost of capital and the minimum return

44:14 - Segmenting your customer base to isolate CS impact

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GTM STRATEGY & AI ENGINEERING FOR B2B TECH

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Mark Kosoglow has built revenue organizations at every stage; from a 100% commission territory seller to first employee at Outreach to CRO at Catalyst to founding Operator. Now eight months into running revenue at Docebo, a publicly traded LMS company doing $230M ARR, he's applying everything he's learned across both sides of the bow tie.

In this episode of CRO Stories, Rachael Bueckert sits down with Mark for a conversation on the forecasting system that eliminated the "haircut of the haircut" problem, the enablement nine-box matrix that caps rep training at 20 points per quarter, how signal-based outbound took reply rates from 2% to 16%, why he inspects his own managers twice a year, and the post-sales framework he says most CROs completely ignore.

Resources Mentioned in This Episode:

Mark Kosoglow's Rep Assessment Matrix (30 Minutes to President's Club)

USC Frameworks

01:51 - What changed and what stayed the same across every CRO role

05:41 - From 100% commission seller to first employee at Outreach

11:37 - First 90 days at Docebo: observe first, then build

13:04 - 3% forecast accuracy and the system behind it

14:30 - The haircut problem and why most forecasts are fiction

18:33 - Inspecting the inspectors: coaching managers on deal reviews

19:27 - The enablement nine-box matrix

26:03 - Signal-based outbound: 2% to 16% reply rates

32:41 - Three reasons most outbound fails

35:22 - Multi-threading and why champions are a false sense of security

46:01 - The two frameworks behind every revenue org he builds

48:11 - Moments of Impact: proactive value creation in post-sales

50:36 - Why most CROs have no clue about post-sales

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GTM STRATEGY & AI ENGINEERING FOR B2B TECH

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Jessica Robertson is 11 months into her first CRO role and she's building a go-to-market engine around something most revenue leaders talk about but never operationalize: relationships. After scaling Accessibly from under $10M to $50M as VP of Sales, she watched the outbound playbook she'd relied on for years stop working. The 1:1 capacity math that used to be predictable fell apart, and no amount of headcount fixed it. So she made the jump to CRO at an early-stage startup to build a GTM motion from scratch that treats existing relationships as a real revenue channel.

In this episode of CRO Stories, Rachael Bueckert sits down with Jessica Robertson, CRO of Orb, for a conversation on what it looks like to build a relationship-led GTM engine from zero, the culture shock of going from a scaled org back to startup basics, how she uses network mapping to turn existing customers into new pipeline, why her curated dinner events convert when most events don't, and what she's learned about navigating sales and CS misalignment as the person who owns both.

Resources Mentioned in This Episode:

USC Frameworks

00:36 - Intro to Jessica Robertson and Orb

06:06 - From SDR to VP of Sales to first-time CRO

07:26 - Why she left a $50M org for a startup

12:09 - The culture shock of going back to ICP basics

17:05 - How relationship mapping actually works in practice

23:48 - Using your own product to build pipeline

29:14 - The GTM motions driving Orb's growth

31:19 - Why their curated events convert when most don't

36:09 - Tripling revenue as a year-two goal

42:41 - Advisors: Warren Zena and Bridget Winston

47:41 - Navigating sales and CS misalignment as the CRO

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GTM STRATEGY & AI ENGINEERING FOR B2B TECH

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Every CRO has been here: you ask your ops team for a read on the pipeline and the numbers come back looking reasonable on the surface. But then you dig in and one rep is sitting at an 85% close rate while another is at 10%. Half the pipeline is zombie deals past twice the average sales cycle that nobody wants to mark as lost. The blended metrics look passable, but they're masking what's actually happening. And when your annual plan, your hiring decisions, and your board forecast are all built on top of that data, you're flying blind.

In this episode, Eddie Reynolds and Rachael Bueckert break down how CROs and GTM Ops should actually analyze revenue metrics, starting with why most reporting is useless until the process underneath it is fixed. The conversation covers the basic questions that uncover more than any dashboard, how to read your funnel from right to left to find the real bottleneck, how ZoomInfo cut 4,000 leads and made more revenue with the remaining 2,000, and why your annual plan is only as good as the data it's built on.

Resources mentioned in this episode:

USC Frameworks

GTM Efficiency Pyramid Framework

02:38 - Why your pipeline report never tells the full story

06:45 - Zombie deals and the 2x sales cycle test

08:46 - One rep at 10%, another at 85%

11:32 - The marginal gains philosophy for GTM

15:05 - Give your Rev Ops team protected time

16:42 - The GTM Efficiency Pyramid foundation

20:17 - Why CS belongs in the ICP conversation

24:38 - Segmenting data to find hidden conversion gaps

27:20 - Reading your funnel right to left

29:14 - Annual planning on bad data

33:49 - Pipeline generation isn't always the real problem

39:23 - Bad leads or bad follow-up: how to test it

43:27 - ZoomInfo cut 4,000 leads and made more money

45:34 - Where to set the MQL qualification bar

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GTM STRATEGY, GROWTH PLANNING, & REVOPS SERVICES

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