GTM Science - A show for GTM and RevOps leaders

Sam Jacobs teaches that product market fit isn't a vibe and it's not a feeling. It's a function of your unit economics, and it isn't permanent either. You can fall out of it when your acquisition costs climb or your retention slips, and that is the signal to pull back on growth spending rather than push harder.
In this episode, Eddie Reynolds sits down with Sam Jacobs, founder and CEO of Pavilion, to discuss what it takes to make revenue predictable and why predictability is what a buyer is actually paying for. Sam walks through the LTV to CAC range he wants a company sitting in and how fast he expects acquisition costs to be paid back, why one private equity backed business sold at roughly half the multiple its owners had expected, and the trade a founder has to accept to build a machine that runs without them. They also get into where AI genuinely helps a sales org and where Sam thinks it shouldn't be, and he closes on why your ownership structure is the most consequential long term decision you will make.
Resources Mentioned in This Episode:
Sundays with Sam #21: Predictable Revenue
Pavilion University (Intro to P&L Fluency, CRO School, AI in Go to Market School)
USC Frameworks

02:28 - The rule of 60 company that wasn't
03:18 - How bankers stage a business like a house
06:25 - Why pre-AI SaaS is reverting to 4 to 6 times revenue
08:37 - Why investors actually pay for predictability
11:49 - AI native reps closing $10M deals
14:30 - Product market fit is not a vibe
18:27 - How you fall out of product market fit
19:48 - The LTV to CAC and payback numbers he wants
25:36 - Treating your business like a code base
27:03 - The close rate a founder has to give up
29:59 - When the person with clout breaks the rules
32:30 - Strategy is deciding what money to turn away
38:10 - Where AI belongs: enrichment and list building
40:30 - Where AI does not belong
49:28 - Your cap table is your corporate strategy
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GTM STRATEGY & AI ENGINEERING FOR B2B TECH
● Website
● LinkedIn
● TikTok

Richard Perez leads the sales and go to market practice at Apax Partners, a private equity firm, where he works with their portfolio companies on how they sell. We asked which motions he'd back at the enterprise end, which at the SMB end, and what he wouldn't spend his own money on. Almost every answer came back with conditions attached.
In this episode, Eddie Reynolds sits down with Richard to discuss the GTM motions and channels working right now. You'll hear where he thinks ABM stops working, the three things that decide whether a conference booth pays off, why he's skeptical of most intent platforms, and the number that tells him a sales organization hasn't been engineered properly.
Resources Mentioned in This Episode:
USC Frameworks
01:14 - Motions vs channels, and why the label matters less
06:46 - Why LLMs are now a channel you have to plan for
08:51 - $10K in seven days vs $500K in 19 months
10:28 - What's working at the enterprise end
12:08 - Buyers who know your competitive position better than you
14:19 - The events he likes best
15:25 - Three things that decide whether a booth pays off
17:46 - Why execution beats channel choice
25:25 - What has to be true before you deploy AI
26:41 - What's working at the SMB end
30:22 - Where ABM stops working
32:30 - Why warm and cold leads need different reps
37:57 - Why he's skeptical of intent platforms
40:36 - The cost of a dollar of new logo revenue
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GTM STRATEGY & AI ENGINEERING FOR B2B TECH
● Website
● LinkedIn
● TikTok

SaaStr surveyed companies that had implemented AI SDRs and found only 3% had any revenue to show for it. Eddie's read is that this is the same pattern as Outreach and Salesloft a few years ago, and Gmail and Salesforce before that. So we mapped the system that has to be built around an ai-powered outbound motion before it will actually work.
In this episode, Eddie Reynolds and Gerry Marletta, SVP of Revenue Operations Systems at USC, walk through how to build an AI-native outbound engine, agent by agent. You'll hear how they got around the catch-22 of deciding which accounts to enrich before you've enriched them, when to hand a step to an LLM and when to use an orchestration tool instead, what the agent that grades every rep email actually checks for, and the updates Gerry says a machine should never be allowed to make.
Resources Mentioned in This Episode:
Building an AI-Native Outbound Engine (Full Written Article)
The AI-Driven Continuously Self-Improving ICP
Free Outbound Pipeline Inspection
USC Frameworks
04:18 - Only 3% of AI SDR buyers saw any revenue
08:18 - Why reps get 2,000 accounts and work 200
10:44 - The targeting agent and the data source waterfall
16:17 - Triggers and signals, and why one alone isn't enough
20:19 - The tool stack and why Salesforce stays the source of truth
23:33 - Why separate agents beat one big one
26:00 - When to use an LLM and when to use n8n
30:15 - The catch-22 of what to enrich first
39:50 - Scoring: start with a hypothesis and iterate
47:55 - What a good sales email actually looks like
56:57 - Who gets a fully personalized message and who doesn't
01:03:59 - The updates a machine should never make
01:04:36 - The first question for your AI analyst: did we execute
01:12:35 - The GTM council meeting that forces the loop
_________________________________________________________
GTM STRATEGY & AI ENGINEERING FOR B2B TECH
● Website
● LinkedIn
● TikTok

New logos get most of the attention in a revenue org. Robert Clarkson calls that the most obvious of three growth levers, and it's the one he spends the least time on. He has run revenue at PayPal, Stripe, Payoneer and now Fiserv, which moves $4.6 trillion in payment volume a year. At one company he joined that had grown 16% to 19% a year for three straight years, he stopped measuring the sales team on what it sold and started measuring it on what customers actually got out of it. It grew 26% the next year and never had a year under 30% after that.
In this episode, Rachael Bueckert sits down with Robert, Chief Revenue Officer for SMB and Clover at Fiserv, to walk through the model he has carried from company to company. They cover how he writes a customer success measure into the sales compensation plan, how he splits his team into hunters and growers, and why he will accept almost any CAC as long as the long term value holds up.
Resources Mentioned in This Episode:
USC Frameworks
01:15 - The three growth levers every CRO has
04:53 - Inheriting a quilt when you need a mosaic
13:21 - Giving SMBs the analytics only enterprises had
23:27 - The model he runs at every company
27:36 - Putting customer success in the sales comp plan
32:23 - Why net dollar retention has to clear 100%
40:19 - Hunters and growers
41:59 - Six features sold, five in use
46:38 - From 19% to 26% to never under 30%
49:28 - Uber didn't build a better taxi
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GTM STRATEGY & AI ENGINEERING FOR B2B TECH
● Website
● LinkedIn
● TikTok

We get asked what's actually working in outbound constantly, and specifically what works for companies that don't have a great brand. So we read the industry reports, more than 100 million emails worth of data, and traced every stat we could back to its original source. The surprising finding was how unreliable the data is.
In this episode, Eddie Reynolds and Rachael Bueckert go tactic by tactic through all six most common outbound strategies: targeted, warm signals, trigger based, third party intent, autonomous AI SDRs and spray and pray. You'll hear which one doubled reply rates, the templated LinkedIn message Eddie used to source millions in business, and the one signal he says he would spend his money on last.
Resources Mentioned in This Episode:
What's Working in Outbound in 2026 (Full Written Report)
Free Outbound Pipeline Inspection
01:36 - 100 million emails and a fake return address
03:45 - Why we went digging for real data
08:53 - Targeted outbound: double the reply rate
10:02 - It's not six tactics, it's three
13:19 - Why Eddie won't use Outreach for this
15:56 - The segmentation step everyone skips
20:56 - Vendors claim 20%, we saw 2 to 5%
27:16 - The bar every hot list has to clear
31:37 - The LinkedIn message that sourced millions
36:49 - Who paid for the intent data studies
43:40 - 3% of AI SDR teams saw any revenue
51:09 - Does bad outbound burn your reputation?
54:17 - Spray and pray works, and that's the problem
___________________________________________________________
GTM STRATEGY & AI ENGINEERING FOR B2B TECH
● Website
● LinkedIn
● TikTok