John Barrows has trained sales teams at Salesforce, LinkedIn, Google, and Amazon. He's watched every wave of outbound innovation since before predictable revenue was a playbook. And right now, he has a challenge for anyone claiming AI has tripled their results: show me the numbers. Because what he's seeing across hundreds of companies is that we're still in the efficiency phase of AI, not the results phase. Reps are sending faster, but they're not selling better. And 14 out of 20 reps who booked a call with him couldn't even tell him what he does for a living.

In this episode, Eddie Reynolds sits down with John Barrows, CEO and founder of JB Sales, for a candid conversation on what's actually working in outbound right now and what isn't. The conversation covers the "give a shit" factor that separates reps who get responses from reps who don't, why the SDR model was never really profitable and where it goes from here, how to run sales hackathons that get your whole GTM team building AI solutions together, why email might be about to become the most valuable outbound channel again, and the ICP and segmentation foundation that has to exist before any of it matters.

Resources Mentioned in This Episode:

GTM Ops Frameworks

00:23 - AI and outbound: separating signal from noise

03:56 - Still in the efficiency phase, not the results phase

06:51 - Why top-down AI adoption fails

10:04 - Turn your sales org into a sales hackathon

22:01 - The SDR model was never really profitable

27:12 - The "give a shit" factor and the Morgan story

32:16 - 14 out of 20 reps couldn't tell John what he does

33:43 - Why email is about to become the most valuable channel again

36:41 - The foundation: ICP, personas, and segmentation before AI

40:50 - Eddie's reps switched to templates and the meetings dried up

41:50 - Why hiring outside tech might be the answer

52:33 - Happiness, core values, and the unsexy path to winning

_______________________________________________________________

GTM STRATEGY & AI ENGINEERING FOR B2B TECH

● Website

● LinkedIn

● TikTok

For ten years, the partner channel has been the single largest source of revenue for Union Square Consulting. Not marketing, not outbound, not referrals from happy customers. Partners. And for most of those ten years, Eddie was reaching out to the wrong ones. Thousands of conversations with partners who looked right on paper but never sent a single deal. It took years of trial and error to land on the three criteria that actually predict whether a partner will deliver. And if any one of those is missing, it's a waste of everyone's time.

In this episode, Eddie Reynolds and Rachael Bueckert break down how to define your ideal partner profile with the same rigor you'd put into your ICP. The conversation covers the three criteria that separate partners who send deals from partners who send pleasantries, how to think about partner benefit when there's no revenue share in the equation, why even internal partners at companies like Salesforce and Wells Fargo compete for mindshare the same way external ones do, and how to operationalize your IPP into a continuously improving system that actually drives revenue.

Resources Mentioned in This Episode:

GTM Ops Frameworks

01:25 - Why we don't talk about the partner channel enough

02:38 - The three criteria for an ideal partner

06:28 - Why direct benefit matters more than revenue share

09:24 - Wells Fargo: 186 lines of business, 35 business cards, zero mindshare

10:11 - Salesforce: internal partners competing for attention

11:31 - Why $500 in quota relief doesn't move the needle

14:37 - Where people go wrong defining their partner profile

21:21 - What enablement for partners actually looks like

22:14 - The La Bernardine dinner story

31:37 - AI for keeping your ideal partner profile current

37:15 - How to measure whether your partner program is worth it

45:24 - Turning the IPP into a continuous improvement system

_______________________________________________________________

GTM STRATEGY & AI ENGINEERING FOR B2B TECH

● Website

● LinkedIn

● TikTok

Jeff Perry joined Carta in late 2018 when it was a 275-person startup selling cap tables to founders. Eight years later, it's a $650 million private markets platform with 50,000 companies on the platform, a fund administration business for venture and PE firms, a total compensation product, tax advisory, and a recently acquired law firm. The cap table business is still healthy, but it has a ceiling. Every dollar of growth beyond that core product came from building or buying entirely new revenue lines for entirely new types of customers.

In this episode, Rachael Bueckert sits down with Jeff Perry, CRO of Carta, for a conversation on how to keep growing when your core TAM runs out, the specialization mistake that taught them to simplify instead of overengineer, and how a $50K customer becomes a $1M customer over time through multi-product cross-sell.

Resources Mentioned in This Episode:

GTM Ops Frameworks

00:26 - Intro to Jeff Perry and the Carta growth story

01:13 - What Carta looked like at $20M and 275 people

05:06 - Why the cap table TAM ran out and what came next

07:39 - Build vs. buy: what's harder, new products or acquisitions?

09:50 - The Manhattan takeover and guerrilla marketing for PE firms

13:40 - How customer conversations drive the product roadmap

17:53 - One-call closes and two-year enterprise cycles in the same company

21:18 - The customer symposium where the CPO built features before dinner

23:28 - Enabling reps to sell across a widening product portfolio

32:50 - Territory and capacity planning across multiple business lines

34:55 - The separate sales team mistake and why they simplified

40:09 - Comp plan evolution: product-specific quotas vs. one quota

46:13 - Expansion: how a $50K customer becomes $1M

50:09 - Advice for CROs hitting a TAM ceiling

_______________________________________________________________

GTM STRATEGY & AI ENGINEERING FOR B2B TECH

● Website

● LinkedIn

● TikTok

On paper, everything looks healthy. Reps are hitting activity. Leads are coming in. Pipeline looks full. And yet deals are slipping, cycles are running long, and customers keep churning out the back. So much of that comes back to an ICP definition that's too broad, too shallow, and stuck in a doc that nobody uses.

In this episode, Eddie Reynolds and Rachael Bueckert break down how to turn your ICP from a static document into a living system that sharpens itself every quarter. The conversation covers how to identify which customers are actually your best, why the one differentiating data point matters more than 50 generic ones, how to build an account scoring model reps will actually trust, and how to build the continuous improvement engine that feeds every new lead and lost deal back into the definition.

Resources Mentioned in This Episode:

The AI-Driven Continuously Self-Improving ICP (Newsletter)

150+ ICP Data Points List

GTM Ops Frameworks

01:02 - Pipeline looks full but nothing is converting

01:50 - Why a written ICP isn't enough

03:29 - How to identify which customers are actually the best

06:50 - The biggest customer isn't always the best customer

09:09 - Going deeper than firmographics to find what really differentiates

12:08 - 150+ data points you could consider

14:53 - If it describes 80% of your lost deals too, it's not differentiating

16:54 - Survivorship bias: what the planes that don't come back tell you

19:26 - Manual vs. AI: when to use each and why you spot check everything

22:58 - Deterministic data first, fuzzy data second

27:28 - How changing content voice fixed lead quality overnight

30:17 - Fit vs. timing and why both belong in the ICP definition

33:56 - Building the account scoring model reps will actually trust

50:03 - AI provides the signal, humans make the decision

_______________________________________________________________

GTM STRATEGY & AI ENGINEERING FOR B2B TECH

● Website

● LinkedIn

● TikTok

Miro had 60-70 million users, world-class UX, and reps were overachieving on their numbers. Then the pandemic tailwind died and the product became an easy target to replace with free alternatives. The problem wasn't that people didn't love Miro. The problem was that nobody had ever tied it to anything strategic enough to survive a renewal conversation. Pipeline looked great because the team was monetizing usage. But usage without a business case doesn't survive a CFO asking "what do we actually need this for?"

In this episode, Rachael Bueckert sits down with Sangeeta Chakraborty, former CRO of Miro and current CRO of Amagi, for a conversation on how she rebuilt Miro's entire go-to-market motion from the ground up. The conversation covers how she redesigned ICP, the use-case sales plays, and how the value engineering function helped buyers build business cases they'd never built before.

Resources Mentioned in This Episode:

GTM Ops Frameworks

00:22 - 70M users loved the product but renewals were breaking

01:39 - Walking into the first QBR and seeing the cracks

04:40 - Monetizing usage vs. selling outcomes

06:41 - Finding the preponderance of use case across 70M users

18:03 - Command of the Message and building use-case sales plays

18:26 - Why the ICP became the product manager

19:06 - Pepsi: a potato chip that took 3 years cut to 10 months

26:04 - Value engineering: helping buyers build business cases

34:11 - Entry and exit gates at every stage of the sales process

42:04 - A cheaper competitor came knocking

43:54 - How competitive pressure made the team stronger

46:17 - "Don't get fooled by vanity metrics"

_______________________________________________________________

GTM STRATEGY & AI ENGINEERING FOR B2B TECH

● Website

● LinkedIn

● TikTok

Anders Krohn spent years deploying AI into enterprise go-to-market organizations and kept hitting the same wall. The models weren't the problem. The data was. When his team anonymized and aggregated proof-of-concept data across dozens of companies, they found that 86% of CRM records had some kind of entity data error. Not missing fields or stale phone numbers. Structural errors at the entity layer: accounts mapped to the wrong parent companies, subsidiaries treated as headquarters, local offices confused with global entities because they share the same domain. And every enrichment tool, every territory plan, every AI agent built on top of that data inherits the same errors downstream.

In this episode, Rachael Bueckert sits down with Anders Krohn, founder and CEO of Kernel, for a conversation on why the entity and hierarchy layer is the root cause of broken CRM data, how 20% of accounts assigned to reps are flat wrong, why companies spending millions on data providers are still unhappy, how AI exposed a problem that humans used to work around, and what it actually takes to fix the foundation before layering anything else on top of it.

Resources Mentioned in This Episode:

GTM Ops Frameworks

01:15 - Every revenue leader has had this moment

04:06 - Garbage in, garbage out: learning the hard way

05:49 - 86% of CRM records have entity data errors

08:18 - Spending millions on data and still unhappy

08:40 - Territory planning and AI: the two triggers that expose bad data

10:22 - How deep the entity layer problem actually goes

14:57 - 20% of accounts assigned to reps are wrong

20:21 - The domain problem: Starbucks HQ vs. Starbucks around the corner

21:13 - Two parts to solving a data problem

22:51 - Data governance vs. letting reps loose: when each makes sense

23:20 - Data debt and why it compounds as companies scale

39:21 - What this means for AI deployment right now

_______________________________________________________________

GTM STRATEGY & AI ENGINEERING FOR B2B TECH

● Website

● LinkedIn

● TikTok

Buyers are doing what Doug Landis calls an "invisible evaluation." They're using ChatGPT, Claude, and Perplexity to research solutions, build shortlists, and form opinions without ever visiting your website, downloading your content, or triggering a single intent signal. By the time they show up on a discovery call, they've already decided what they believe. The old linear, seller-controlled sales process wasn't built for this. And running your reps through a stage-gated pipeline that assumes the buyer is starting from zero is why your deal reviews feel like theater.

In this episode, Eddie Reynolds sits down with Doug Landis, CRO and co-founder of StoryPath, former Chief Storyteller at Box, and former Growth Partner at Emergence Capital, for a conversation on what selling actually looks like when the buyer controls the process. Doug walks through the concept of situational fluency, the Buyer Situation Operating Model he's built to replace the traditional sales process, why "what does the buyer need to believe next?" is the only question that matters in a deal review, and how stories are the mechanism that actually moves buyers from one belief to the next.

Resources Mentioned in This Episode:

GTM Ops Frameworks

01:13 - The sales process is dead

04:15 - The invisible evaluation: buyers research without triggering any signal

06:33 - Situational fluency vs. process compliance

08:33 - "What buying situation are we actually in?"

12:15 - Problem aware but not urgency aware

14:26 - How call prep has to change when the buyer already has beliefs

21:05 - Building the Buyer Situation Operating Model

22:29 - The top ten buyer situations every org faces

25:34 - Stories create belief: the mechanism behind every deal

29:40 - Redesigning deal reviews around buyer reality

33:36 - "What does the buyer need to believe next?"

49:55 - Where to start: one change CROs can make tomorrow

_______________________________________________________________

GTM STRATEGY & AI ENGINEERING FOR B2B TECH

● Website

● LinkedIn

● TikTok

Emir Atli started his first product at 18 from his parents' living room in Turkey. Now he's co-founder and CRO at HockeyStack, where he's scaled to over 300 enterprise customers in under two years, multiplied revenue 4.5x in a single year, and just closed a $50 million funding round. When he first built the SDR team, he watched reps spend 80% of their time clicking between ZoomInfo, the CRM, and Outreach. Not selling. So he ripped the whole motion apart and rebuilt it from scratch with AI handling everything that wasn't a human conversation.

In this episode of CRO Stories, Rachael Bueckert sits down with Emir for a conversation on how he built the outbound motion alongside AI from day one, the experiment framework he uses to prove an AI motion works before rolling it out, why delegating AI experiments entirely to leadership is the single biggest mistake, and how making sales engineers full-cycle solved the handoff problem that was killing expansion.

Resources Mentioned in This Episode:

GTM Ops Frameworks

01:06 - Intro to Emir Atli and HockeyStack

02:21 - 4.5x revenue in one year and the GTM engine behind it

03:13 - Building outbound on top of inbound, not instead of it

07:10 - 80% of SDR time was clicking buttons, not selling

09:02 - Building the automation from Clay to custom APIs

14:27 - Cold outbound vs. warm outbound: two different systems

16:15 - Advice for legacy outbound teams layering on AI

17:53 - Quota relief: how to get reps to actually run the experiment

19:31 - The biggest mistake in designing AI experiments

22:12 - Results: what the first 30 days should actually look like

27:22 - Where AI handles outbound vs. where humans stay

39:24 - Full-cycle SEs and fixing the expansion handoff problem

46:04 - The metrics on his office TVs and why he ignores quarterly forecasts

48:38 - Study your top 20 deals and build the blueprint

_______________________________________________________________

GTM STRATEGY & AI ENGINEERING FOR B2B TECH

● Website

● LinkedIn

● TikTok

This episode is a guest appearance by Eddie Reynolds, CEO of Union Square Consulting, on the Selling AI podcast with Warren Kucker. You can find the original episode on Apple Podcasts.

Eddie digs into why most CRM implementations fail before they start, what happens when sales behavior and data entry aren't aligned, and how AI fits into a go-to-market engine only after the foundational processes and definitions are in place. The conversation covers the real challenges behind deal qualification and pipeline visibility, how AI tools can automate the parts of selling that reps shouldn't be doing manually, the role of customer journey mapping in building a GTM strategy that actually holds up, and why CROs need to think like systems architects before they think like closers.

Resources Mentioned in This Episode:

GTM Ops Frameworks

_______________________________________________________________

GTM STRATEGY & AI ENGINEERING FOR B2B TECH

● Website

● LinkedIn

● TikTok

You invested six figures in Salesforce, hired a rev ops team to build dashboards, and six months later nobody's looking at them. Or worse, people are looking at them but spending every team meeting arguing about whether the numbers are right instead of deciding what to do about them. One rep shows an 85% close rate, another shows 15%, and the blended number looks fine on paper. The CEO says visibility is their number one priority. The CRO says they know their deals. And the data underneath all of it is fiction.

In this episode, Eddie Reynolds and Rachael Bueckert break down why most go-to-market reporting is useless and what it actually takes to get data you can trust. The conversation covers the definition debates that burn entire team meetings, the real story behind massive close rate gaps, why your best rep might be ignoring half her territory and you'd never know it, how to build reporting that an average rep on an average day can feed accurately, and why focusing on one metric at a time beats trying to fix everything at once.

Resources Mentioned in This Episode:

GTM Ops Frameworks

01:11 - The problem with GTM reporting right now

02:13 - Visibility is the CEO's #1 priority but nobody trusts the data

05:54 - The 18-month CRO cycle and why reporting never matures

09:02 - The MQL definition debate that burns every team meeting

11:54 - One rep at 15%, another at 85%: both numbers are fiction

16:32 - Your best rep is ignoring half her territory

21:13 - Stop looking for rainmakers, build for the average rep

23:09 - What it takes to build reporting you can actually trust

45:28 - What actually belongs on an executive dashboard

46:53 - The Moneyball approach to go-to-market data

50:06 - Pick one metric and fix it before touching anything else

_______________________________________________________________

GTM STRATEGY & AI ENGINEERING FOR B2B TECH

● Website

● LinkedIn

● TikTok