Eddie Reynolds

Over +20 years in sales, customer success and marketing, I’ve developed a passion for data-driven strategy and process. I’ve always been fascinated by the edge it can give an IC or an entire company. 

Ten years ago, I joined Salesforce as an AE covering high-growth, VC-backed B2B SaaS companies. I met with hundreds of executives and revenue leaders and they all wanted this edge. They wanted to hear how Salesforce and my other customers operated, not how the software worked. 

Our consulting partners, however, were solely focussed on the software, often missing the broader strategy. This inspired me to start a unique consulting firm, merging system implementation with data-driven GTM strategy. 

Since then, I’ve seen some of the deepest ingrained revenue growth problems plaguing B2B SaaS – and we’ve developed a system to solve them.

𝘾𝙍𝙊𝙨, 𝘾𝙈𝙊𝙨, 𝘼𝙉𝘿 𝙑𝙋𝙨:

Does this sound familiar?

💭“I don’t understand what my data is telling me. I’m not even sure it’s accurate.”
💭“We’re getting tons of leads but they’re not converting enough to outpace churn.”
💭“We’ve spent so much money on tech, marketing, training, etc. – but there’s no ROI.”

Or maybe even…

“I don’t want to end up like those guys ☝️ How do I get in front of this?”

𝙔𝙊𝙐’𝙍𝙀 𝙄𝙉 𝙏𝙃𝙀 𝙍𝙄𝙂𝙃𝙏 𝙋𝙇𝘼𝘾𝙀

I founded Union Square Consulting to help B2B recurring revenue brands increase profitability by targeting the source of their revenue engine issues (not just the symptoms).

𝙒𝙃𝘼𝙏 𝙒𝙀 𝘿𝙊

Fractional RevOps that delivers both systems implementation and go-to-market strategy.

𝙒𝙃𝙊 𝙒𝙀’𝙑𝙀 𝙃𝙀𝙇𝙋𝙀𝘿

High-growth brands from Series A to C and beyond like Techstars, Luminate, and Federato.

𝙂𝙀𝙏 𝘼 𝙁𝙍𝙀𝙀 𝘾𝙊𝘼𝘾𝙃𝙄𝙉𝙂 𝙎𝙀𝙎𝙎𝙄𝙊𝙉

Sit down with one of my Senior Revenue Strategists for a personalized Revenue Operations Coaching Session. Walk away with advice you can use immediately.

👉 CLICK HERE: unionsquareconsulting.com/workshop

𝙎𝙐𝘽𝙎𝘾𝙍𝙄𝘽𝙀 𝙏𝙊 𝙊𝙐𝙍 𝙍𝙀𝙑𝙊𝙋𝙎 𝙉𝙀𝙒𝙎𝙇𝙀𝙏𝙏𝙀𝙍

Get actionable and practical tips on optimizing your marketing, sales, and customer success engines.

👉 CLICK HERE: unionsquareconsulting.com/newsletter

Host

RevOps Corner is a podcast we produce at Union Square Consulting to share best practices for Strategic Revenue Operations. 

We do this by interviewing amazing guests, ranging from Revenue Operations Professionals to Revenue Leaders to Venture Capitalists and many other experts in the B2B SaaS community. 

We also share what we're seeing in the trenches every day in our work as Revenue Operations Consultants here at Union Square Consulting.

Listen to the Podcast on:
Spotify: https://open.spotify.com/show/1CM3rmelcdtm6gJVL0PtMK?si=00aae750ea7a4937
Apple: https://podcasts.apple.com/us/podcast/revops-corner/id1619571311

We've updated our core GTM Framework. 
The foundation of ALL our work in GTM!!!!

v3.0 of how we prioritize what to fix in GTM first!

𝐇𝐞𝐫𝐞'𝐬 𝐰𝐡𝐚𝐭 𝐈 𝐡𝐞𝐚𝐫 𝐨𝐧 𝐜𝐚𝐥𝐥 𝐚𝐟𝐭𝐞𝐫 𝐜𝐚𝐥𝐥 𝐰/ 𝐂𝐑𝐎𝐬
- Reps chasing deals they'll never close
- Inbound leads not getting followed up
- Customers churning before renewal starts
- Expansion is an afterthought
- No one trusts the forecast

𝐓𝐡𝐚𝐭'𝐬 𝐚 𝐥𝐨𝐭 𝐨𝐟 𝐢𝐬𝐬𝐮𝐞𝐬 𝐚𝐜𝐫𝐨𝐬𝐬 𝐆𝐓𝐌!

𝐖𝐞 𝐜𝐚𝐧'𝐭 𝐟𝐢𝐱 𝐞𝐯𝐞𝐫𝐲𝐭𝐡𝐢𝐧𝐠 𝐚𝐭 𝐨𝐧𝐜𝐞
 - We need to prioritize one item at a time

So we built the 𝗚𝗧𝗠 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 𝗣𝘆𝗿𝗮𝗺𝗶𝗱 𝘃𝟯.𝟬

𝐈𝐭 𝐬𝐭𝐚𝐫𝐭𝐬 𝐰𝐢𝐭𝐡 𝐨𝐧𝐞 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧:

𝗪𝗵𝗮𝘁 𝘄𝗼𝘂𝗹𝗱 𝗶𝗺𝗽𝗮𝗰𝘁 𝗿𝗲𝘃𝗲𝗻𝘂𝗲 𝗺𝗼𝘀𝘁?
- More New Customers?
- Or more Net Revenue Retention?

𝐓𝐡𝐞𝐧 𝐰𝐞 𝐛𝐫𝐞𝐚𝐤 𝐢𝐭 𝐝𝐨𝐰𝐧 𝐟𝐮𝐫𝐭𝐡𝐞𝐫:
- Closing Deals vs. Generating Pipeline
- Inbound vs. Outbound vs. ABM vs. Partners
- Reducing Churn vs. Expanding Customers

What's the one thing that would have the most impact on revenue the fastest?

𝐓𝐡𝐞𝐧 𝐰𝐞 𝐰𝐨𝐫𝐤 𝐭𝐡𝐫𝐨𝐮𝐠𝐡 𝟒 𝐬𝐭𝐚𝐠𝐞𝐬:

𝟭. 𝗙𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀
- Do we really know our ICP?
- What's the step by step process?
- Is that process built into our systems?

𝟮. 𝗔𝗱𝗼𝗽𝘁𝗶𝗼𝗻
- Is the team trained on the process?
- Do we have reporting to track execution?
- Is management reviewing execution regularly?

𝟯. 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻
- What's working and what's not?
- Are the right people analyzing the data?
- Translating data into real insights on GTM?
- Are GTM leaders meeting to act on insights?

𝟰. 𝗔𝗺𝗽𝗹𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻
- What busywork can we automate?
- Where can AI amplify what's working?
- Where do we deploy agentic workflows?

🚩 *Warning: Don't amplify a motion that's not working!

𝐇𝐞𝐫𝐞'𝐬 𝐰𝐡𝐲 𝐭𝐡𝐞 𝐨𝐫𝐝𝐞𝐫 𝐦𝐚𝐭𝐭𝐞𝐫𝐬

When we Amplify too early:
- AI amplifies what's broken
- We run full speed the wrong way

When we Optimize too early:
- Our data is unreliable
- So we can't see what's working
- Until we fix the foundation first

When we adopt too early:
- Reps are all running their own process
- Everyone is rowing in different directions

 We've found that we can often take a very broken GTM Engine and get through Fundamentals and Adoption in as little as a few weeks, at least for one part of GTM for a small team. 

It can take quarters or years to fully optimize and amplify those motions. 

But getting the foundation in place can do wonders for revenue

𝐖𝐡𝐚𝐭'𝐬 𝐧𝐞𝐰 𝐢𝐧 𝐯𝟑.𝟎
- Broke out Pipe Gen Channels more
- Split CS into Renewals and Expansion
- Made it more robust and simpler as well

-------------------------- 

 More in tomorrow's 𝗚𝗧𝗠 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 𝗣𝘆𝗿𝗮𝗺𝗶𝗱 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸  

👉 Subscribe to get it tomorrow: https://bit.ly/4biNF3G

𝗪𝗮𝗻𝘁 𝘁𝗵𝗲 𝗵𝗶𝗴𝗵-𝗿𝗲𝘀 𝐢𝐦𝐚𝐠𝐞?
- Comment "High Res" below
- Send a connection request if we're not connected
- Share the post for priority
- We'll DM it to you

✌️

CEO | GTM Strategy & Ops for B2B SaaS CROs

Kyle Norton’s team used AI call scoring to improve Close Rates from 38% to 53% in one quarter!

They already had a 38% Close Rate.
That's already 2x-4x the average.

Imagine saying.... 
"That's not good enough."
"We could do a LOT better."

Sounds crazy. 
But that's exactly what they did. 

They found a way to close 40% MORE deals!

𝐇𝐨𝐰?

His team deconstructs their funnel monthly
- Even when things are going well
- They're always looking for places to optimize

𝐓𝐡𝐞𝐲 𝐚𝐬𝐤𝐞𝐝 𝐰𝐡𝐢𝐜𝐡 𝐫𝐞𝐩 𝐛𝐞𝐡𝐚𝐯𝐢𝐨𝐫𝐬 𝐰𝐢𝐧 𝐝𝐞𝐚𝐥𝐬.
𝐓𝐡𝐞𝐲 𝐬𝐜𝐨𝐫𝐞𝐝 𝟏𝟓𝟎+ 𝐫𝐞𝐩 𝐜𝐚𝐥𝐥𝐬 𝐰𝐢𝐭𝐡 𝐀𝐈 𝐭𝐨 𝐟𝐢𝐧𝐝 𝐨𝐮𝐭.

𝗪𝗵𝗮𝘁 𝗱𝗼 𝘆𝗼𝘂 𝘁𝗵𝗶𝗻𝗸 𝗶𝘁 𝘄𝗮𝘀?
What behaviors win deals?

𝐌𝐨𝐬𝐭 𝐰𝐨𝐮𝐥𝐝 𝐬𝐚𝐲 𝐝𝐢𝐬𝐜𝐨𝐯𝐞𝐫𝐲
 - Heck, I would say discovery.
 - And I would be wrong here.

𝐇𝐞𝐫𝐞'𝐬 𝐰𝐡𝐚𝐭 𝐭𝐡𝐞𝐲 𝐟𝐨𝐮𝐧𝐝:
 - 12 skills correlated with winning deals
 - 10 were end-of-call or closing behaviors 
 - 0 skills were discovery

These are the skills that worked for Owner.com:

𝗧𝗵𝗲𝘀𝗲 𝗮𝗿𝗲 𝘁𝗵𝗲 𝟭𝟮 𝘀𝗸𝗶𝗹𝗹𝘀 𝘁𝗵𝗮𝘁 𝘄𝗼𝗻 𝗱𝗲𝗮𝗹𝘀:

1️⃣ Ask for the sale
2️⃣ Book the next call (at least a placeholder)
3️⃣ Help prospect see the value of continuing
4️⃣ Agree on a solid purpose for the next call
5️⃣ Gauge whether the prospect is leaning in
6️⃣ Navigate buying journey, ask for next meeting
7️⃣ Next steps include clear reasons & value
8️⃣ Make an assumptive close
9️⃣ Concise, transparent pricing that reiterates value
1️⃣0️⃣ Prospect has a clear idea of next steps
1️⃣ 2️⃣ Rep in control of the call throughout
1️⃣ 3️⃣ Read the audience, simplify when needed

𝐓𝐡𝐞 𝐩𝐨𝐢𝐧𝐭 𝐢𝐬𝐧'𝐭 "𝐝𝐢𝐬𝐜𝐨𝐯𝐞𝐫𝐲 𝐝𝐨𝐞𝐬𝐧'𝐭 𝐦𝐚𝐭𝐭𝐞𝐫"
- For a lot of companies, it's a #1 skill

𝐓𝐡𝐞 𝐩𝐨𝐢𝐧𝐭 𝐈𝐒 𝐭𝐡𝐚𝐭 𝐢𝐭'𝐬 𝐝𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐭 𝐟𝐨𝐫 𝐞𝐯𝐞𝐫𝐲 𝐜𝐨𝐦𝐩𝐚𝐧𝐲
 - Use your OWN data to find what matters for you

Kyle would've kept optimizing for the wrong skill if he'd just followed the industry playbook. 

Everyone would've been happy with 38% win rates. 
Never knowing that 53% was within reach.

Usually we only fix things when they're broken.

Why do you think we don't fix things that are working more?

 🤔

We'll break this down more in tomorrow's 📰𝙏𝙝𝙚 𝙂𝙏𝙈 𝙎𝙘𝙞𝙚𝙣𝙘𝙚 𝘽𝙧𝙞𝙚𝙛📰

We'll also share how Kyle trained his team on these skills. 

Subscribe to get it here: https://bit.ly/49RCm0h

Or listen to the podcast episode: https://bit.ly/4b28Nwn

✌️

undefined undefined

Certified Alternative Investment Analyst

Series 63

Series 7

•  Started University at age 16, after one year of high school, and finished at age 20.
•  Attained a 5/5 in A.P. Calculus as a freshman in high school and took Calculus II and III as electives at Indiana.
•  Kelley is ranked a top-ten undergraduate program for both finance and entrepreneurship by U.S. News & World Report.

Relevant University Coursework
- Venture Capital and Entrepreneurial Finance		
- Intermediate Accounting		
- Real Estate Analysis		
- International Finance

Strategic RevOps Consulting for B2B SaaS

CAIA (Certified Alternative Investment Analyst)

The RevOps Weekly Newsletter

The RevOps Corner Podcast

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📈 CRO 📈 @ Owner.com, Host of the Revenue Leadership Podcast & SaaS GTM Advisor & Investor

If AI agents sit on top of CRMs...
Why do we need Salesforce or Hubspot?

Let's think about this...
 - Users interact with the AI
 - It queries the CRM for data
 - It translates that data into meaning
 - It updates that data so users don't have to
 - Ideally, no one would ever login to Salesforce

That's just a database. 

Why do we need an expensive CRM? 

I say this as someone who's spent the last 16 years as a Salesforce employee, partner, and customer. I've been a big fan of Salesforce for a long time. 

But....

1. I don't want to login to Salesforce if I don't have to

2. And I don't want to pay Salesforce license fees if I don't have to

So, if AI becomes my sole interface.....

Why do I need a CRM?

🤔 

(To be clear, I'm talking ideal future state, not today.)

✌️

We analyzed 7 "State of GTM" reports.
Here's what stood out.

𝗡𝗲𝗴𝗹𝗲𝗰𝘁𝗶𝗻𝗴 𝗽𝗼𝘀𝘁-𝘀𝗮𝗹𝗲 𝗶𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 𝗶𝘀 𝗰𝗼𝘀𝘁𝗶𝗻𝗴 𝘂𝘀
- 87% of enterprises missed their number
- But 52% of new revenue is from expansion
- Meanwhile, 71% of companies use AI for calls
- But only 25% use it for churn prediction

The best revenue source (customers) get's the least AI. 

𝗜𝗖𝗣 𝗳𝗶𝘁 𝗶𝘀 𝗮 𝗻𝗲𝗴𝗹𝗲𝗰𝘁𝗲𝗱 𝗴𝗼𝗹𝗱𝗺𝗶𝗻𝗲
- High-ICP-fit accounts are 8x more sales efficient
- Yet they make up a fraction of qualified pipeline
- And most CROs aren't confident in the definitions
- That's a huge missed opportunity

𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗴𝗮𝗽𝘀 𝘀𝗶𝗴𝗻𝗮𝗹 𝗽𝗿𝗼𝗰𝗲𝘀𝘀 𝗴𝗮𝗽𝘀
- 65% revenue generated by top 10% of reps
- This is one of the most common red flags we see
- These reps have a better process than their peers
- Because that process is not defined well or managed

𝗘𝗮𝗰𝗵 𝗿𝗲𝗽𝗼𝗿𝘁 𝗶𝘀 𝘄𝗼𝗿𝘁𝗵 𝗿𝗲𝗮𝗱𝗶𝗻𝗴 𝗼𝗻 𝗶𝘁𝘀 𝗼𝘄𝗻.
Scale VP. Pavillion. ICONIQ. Clari. Ebsta. Crossbeam. Fullcast.

But we were curious what the data looks like when you lay them side by side.

In recent report, we covered all 7 sources:
- Where they agree
- Where they disagree
- What it means for us

Which of these findings is most surprising for you?

🤔

More on this in 📰𝙏𝙝𝙚 𝙂𝙏𝙈 𝙎𝙘𝙞𝙚𝙣𝙘𝙚 𝘽𝙧𝙞𝙚𝙛📰
Access the report here: https://bit.ly/49RCm0h

✌️

Every post on LI: "Our AI bot created $100 billion in pipeline last week"

Every CRO: "AI is making us more efficient but not more revenue yet."

It's like two completely different worlds. 

Here's a post I saw the other day. 

"In the last 90 days our AI created $11m in Sales Qualified pipe."

Me: How much ARR did you close? 
Poster: 2X our Target!

Me: What was your target?
Poster: Crickets...........

So so so much hype. 

Meanwhile, people actually seeing results with AI
 - People like Jason M. Lemkin
 - Are not making these crazy claims
 - They're saying this is a LOT harder
 - You need the right foundation in place
 - You need well defined ICP and Buyer Personas
 - You need to have your processes dialed in
 - That process needs to work with humans
 - And you need an accurate layer of data
 - And then you need to iterate repeatedly
 - You need someone dedicated to making it work

We all want a magic bullet. 

And there are 7 trillion posts on LI promising this. 

But it's not the reality. 

We're starting to see the REAL stories though!

Kyle Norton recently shared on our Podcast how his team used AI to improve Close Rates from an already amazing 38% to an astounding 53%!

He broke this down in great detail and shared not just what AI they used and how it generated results but a lot of what they had to do to make it a real success. 

See comment below for links if you want to listen. 

✌️

Here's why I think Salesforce is tanking
It's not AI

Mature B2B GTM Teams 
 - Want Sales Cloud 
 - And almost nothing else 
 - From Salesforce's products

By tanking, I mean the stock
 - Down over 5 years
 - While the market has boomed
 - Because growth was 30% and now <10%

Look I've been a fanboy for ~20 years. 
 - I worked for a Salesforce ISV Partner
 - Then I was a customer in two companies
 - Then I worked at Salesforce for three years
 - Then I was a Salesforce customer another time
 - And now we've been a Salesforce Partner for 10
 - Implementing Salesforce for hundreds of companies

I want to like Salesforce
 - But it's harder every day

Our customers want...
 - Hubspot, not Pardot
 - Outreach, not High Velocity Sales
 - ZoomInfo, not Data dot com
 - Gong, Clari, 6Sense, etc etc
 - And all the new AI tools
 - But not AgentForce

To be honest, I hear about Salesforce's products so infrequently these days I don't even know the names of half of them. 

That's kinda crazy considering we don't have a single customer not using Salesforce. 

Our customers are mature B2B GTM Teams
 - Usually $50M to $500M in ARR
 - Not Series A Startups
 - But also not Fortune 500

Every single one has Sales Cloud
 - And that's about it from Salesforce. 

Everyone is talking about the SaaSpocalypse
 - About how AI is killing SaaS
 - And maybe this is happening
 - But there are also just bad products

For Salesforce, I wish they would focus on making their core products better. 

IDK why Sales Cloud can't be drastically better. 
IDK why Salesforce can't be better than Hubspot Marketing Hub
IDK why they can't beat Outreach, ZoomInfo, etc. 
You would think they could. 

But they seem too busy with the next acquisition. 
And rebranding everything every six months

✌️

AI has me excited about GTM again.
But probably not for the reasons you think. 

𝗜 𝘀𝘁𝗮𝗿𝘁𝗲𝗱 𝘁𝗵𝗶𝘀 𝗰𝗼𝗺𝗽𝗮𝗻𝘆 𝗮𝗹𝗺𝗼𝘀𝘁 𝟭𝟬 𝘆𝗲𝗮𝗿𝘀 𝗮𝗴𝗼. 

𝗠𝘆 𝘃𝗶𝘀𝗶𝗼𝗻 𝘄𝗮𝘀 𝘁𝗼 𝗯𝘂𝗶𝗹𝗱 𝗚𝗧𝗠 𝗹𝗶𝗸𝗲 𝗮𝗻 𝗙𝟭 𝗿𝗮𝗰𝗲 𝗰𝗮𝗿. 

I saw some of this internally as an employee at Salesforce and some of this in my best customers (mature VC/PE backed B2B SaaS companies on the cutting edge.) I wanted to implement all these fancy tools, collect a mountain of data, and then tweak and test everything in GTM to build a finely tuned engine, just like an F1 team does. (TY 🦄Pablo Dominguez and Matthew May for this visual from your book.)

𝗨𝗻𝗳𝗼𝗿𝘁𝘂𝗻𝗮𝘁𝗲𝗹𝘆, 𝗜 𝗯𝗲𝗰𝗮𝗺𝗲 𝗱𝗶𝘀𝗲𝗻𝗳𝗿𝗮𝗻𝗰𝗵𝗶𝘀𝗲𝗱 𝗾𝘂𝗶𝗰𝗸𝗹𝘆.

I saw company after company implement Salesforce and Outreach/Salesloft/Apollo and ZoomInfo quick and dirty, without thinking about their fundamental GTM Strategy and Process, to just spray and pray their entire TAM. 

I saw marketing pump out shitty gated content and ads so they could hit their MQL number and feed reps more people that didn't want to talk to them to feed the automated spam cannon. 

I saw CS try to cut costs by automating away their customer experience, engineering the entire post sale process to benefit the company, not the customer. 

All of this was grounded in a lack of fundamentals, a woeful ignorance of the process these companies knew in their heads was necessary to win and wow customers. Instead of codifying that knowledge and systematizing it into consistent execution, they slapped together tools and GTM motions in the "Growth at All Costs" era. 

𝗦𝗼, 𝗜 𝗽𝗶𝘃𝗼𝘁𝗲𝗱 𝘁𝗼 𝗚𝗧𝗠 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆. 𝗜𝘁'𝘀 𝗯𝗲𝗲𝗻 𝗿𝗼𝘂𝗴𝗵. 

So, we pivoted. We hired experienced VPs of RevOps that truly understood GTM Strategy and I spent 90% of my time trying to learn, understand, codify, and refine that GTM Strategy. We landed partnerships with many of the top PE/VC firms in the world and landed CROs in their portfolio companies as customers. 

We did great work and helped many of them build GTM that was strategy and process first. 

We've had a lot of success.

𝗕𝘂𝘁 𝗺𝗮𝗻 𝘁𝗵𝗶𝘀 𝗳𝗲𝗲𝗹𝘀 𝗹𝗶𝗸𝗲 𝗮𝗻 𝘂𝗽𝗵𝗶𝗹𝗹 𝗯𝗮𝘁𝘁𝗹𝗲. 

For every CRO that embraces this concept, it feels like we have to turn away 5 others. 

5 other CROs that just want to slap together tools, delegate GTM Architecture to someone with no experience and then check out.  

I empathize with these CROs. They have a target on their back and 70 hrs per week of work just hiring, training, and closing deals. I get it. 

But..

𝗜 𝘁𝗵𝗶𝗻𝗸 𝗔𝗜 𝗺𝗶𝗴𝗵𝘁 𝗰𝗵𝗮𝗻𝗴𝗲 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴

AI is going to amplify everything. Every best practice and every bad practice. 

I think CROs and their CEOs will have no choice but to adapt to this new reality. 

They have to build the right foundation.

The right process that delivers the right customer experience. 

AI will amplify good process and bad.

But what do you think?

🤔

The old-school GTM playbooks are failing
But what do we replace them with?

With data and AI we can build out own
Custom to our unique GTM

How?

Kyle Norton, CRO at Owner.com, shared his approach on our Podcast. 
An approach that took Close Rates from 38% to 53%

They used AI Call Scoring to identify the Top 12 skills to win deals.
 - Not in sales
 - Not in the industry
 - But in their unique business 

But he didn't stop there. 

He shared how they approach GTM differently.

Here's a breakdown:

1️⃣ 𝐒𝐚𝐥𝐞𝐬 𝐏𝐥𝐚𝐲𝐛𝐨𝐨𝐤 𝐃𝐞𝐬𝐢𝐠𝐧: Use your own data

Common way: 
Adopt industry best practices and train the team on them.

𝗨𝗽𝗴𝗿𝗮𝗱𝗲: 
Find which behaviors correlate with YOUR wins, build a playbook based on your own data

Kyle used AI call scoring on 150+ rep calls to find which behaviors actually won deals. 
10 of 12 critical skills were end-of-call behaviors — not discovery.

2️⃣ 𝐄𝐱𝐞𝐜𝐮𝐭𝐢𝐧𝐠 𝐏𝐫𝐨𝐜𝐞𝐬𝐬 𝐂𝐡𝐚𝐧𝐠𝐞: Depth over breadth

Common way: 
Roll out multiple changes at once, Slack/email, train once, and move on.

𝗨𝗽𝗴𝗿𝗮𝗱𝗲: 
Depth over breadth, manager-led coaching, don't move on until it's adopted.

Kyle built a 10-week rollout — three modules, one skill at a time — and made it the only thing his org worked on.

3️⃣ 𝐑𝐞𝐢𝐧𝐟𝐨𝐫𝐜𝐞𝐦𝐞𝐧𝐭: Repetition & hands-on learning

Common way: 
Train once, hope reps remember, check results next quarter.

𝗨𝗽𝗴𝗿𝗮𝗱𝗲: 
Reinforce against the Forgetting Curve
Have reps apply skills according to Bloom's Taxonomy.

Kyle had reps build their own call plans, practice in small groups, and got daily scores.

4️⃣ 𝐃𝐚𝐭𝐚 𝐃𝐢𝐬𝐜𝐢𝐩𝐥𝐢𝐧𝐞: Analyze before things break

Common way: 
Dig into the data when something breaks or numbers are low.

𝗨𝗽𝗴𝗿𝗮𝗱𝗲: 
Monthly deconstruction of your sales motion
Even when things are going well.

 - Their win rate was already a strong 38%. 
 - He found the path to 53% because he went looking
 - Not because something was broken.

We broke down the full story in yesterday's 📰𝙏𝙝𝙚 𝙂𝙏𝙈 𝙎𝙘𝙞𝙚𝙣𝙘𝙞𝙚 𝘽𝙧𝙞𝙚𝙛 📰

 👉 Read it here: https://bit.ly/4aCK7c7

Or listen to the podcast episode: https://bit.ly/4b28Nwn

✌️

Idk who needs to hear this but AI isn’t killing software. AI is software. 

It’s not only a dumb click-baitey claim. 
It’s also fundamentally misguided. 

Did SaaS kill software?
No, it mostly killed on-prem

Will AI kill SaaS? No. 
 - It might kill the pricing model. 
 - It might kill a LOT of features. 
 - It WILL kill most SaaS that doesn’t innovate. 

But SaaS didn’t kill MSFT
 - The least innovative company in history 

I think (know) AI is in the dot com boom now
 - The height of hype
 - Amped up to let us down soon

And what happened with the dot coms? 

The bubble burst
 - Investors made dumb bets
 - On dumb companies
 - With dumb valuations 
 - And dumb execution 
 - And it blew up

Then it recovered 
 - Amazons stuck plummeted 
 - But they had paying customers
 - Their fundamentals were strong
 - And now they’ve taken over the world
 - Pets dot come crashed and did not recover
 - But today you can buy pet stuff from Amazon

AI will be the same

But let’s not get confused 

Especially in B2B SaaS GTM

1. The Product will change 
 - This has always been the case
 - Nothing new here, except the pace

2. A LOT of crappy AI products will sell
 - Crappy AI products with crappy GTM
 - It’s a gold rush right now. Simply that. 

3. Don’t look at AI Native for GTM best practices
 - They’re selling DESPITE their GTM
 - People are begging for their products
 - Good for them but an example not to follow

I'm hearing this directly from their VC/PE firms. 

Companies exploding to $300M in ARR in zero time without any GTM. Just a super hot product and viral WOM turning into hot leads that are completely mismanaged but enough of them are still closing. This isn't the model to follow in GTM. It might be the model to follow in product development, but not in GTM. 

Just like the dot com crash, we will have a reset. 

The companies with their fundamentals in place will survive that reset. 

That's my two cents. 

✌️

Will AI replace Salesforce?

Today, I say no. 
Tomorrow, IDK, maybe.  

Let me explain. 

𝗜𝗱𝗲𝗮𝗹 𝗖𝗥𝗠 𝗨𝘀𝗲𝗿 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲

As a CEO and also a salesperson, here's what I want:

1. Accounts and Contacts added for me
2. Leads come in and convert automatically
3. Opportunities are created from email/Slack
4. Emails, Calls, Meetings all added automatically
5. Daily reminders on who I need to follow up with
6. My meeting prep for each meeting is done for me
7. Any time I need a report I just send a Slack/ask a bot
8. And AI analyzes that report and gives me insights first
9. So I basically never need to login to Salesforce ever ever

Basically I spend all day in email/slack/meeting notes. 
 - Which means....
 - If I'm in sales, I'm selling
 - If I'm in management, I'm managing
 - All day long, instead of managing Salesforce

Everything else is done for me. 

How do I know this is what I want?

𝗜 𝗔𝗹𝗿𝗲𝗮𝗱𝘆 𝗛𝗮𝘃𝗲 𝗧𝗵𝗶𝘀

For the most part I have this now.
 - Automation does a lot of the above
 - My EA does most of the rest manually
 - And my team runs and analyzes reports

This isn't new. 

Everyone that can do this, does do this. 

The gap is just building the AI to do it all and correctly.

And when we do.......we just need a database to house the data. 

Do we need Salesforce then?

Or just a solid database?
 - Something with security
 - And proper architecture
 - To house all the data
 - And feed the reports
 - And the AI Agents

I'm struggling to understand why we will need to spend $200,000 just to store this data for 100 salespeople. 

IDK.

What do you think is going to happen?

Will we still be paying for Salesforce in ten years?

🤔

87% of teams missed revenue targets in 2025.
7 reports worth of data told us why.

Not because of bad reps.
Not because of bad tools.

𝗕𝗲𝗰𝗮𝘂𝘀𝗲 𝗺𝗼𝘀𝘁 𝘁𝗲𝗮𝗺𝘀 𝗱𝗼𝗻'𝘁 𝗵𝗮𝘃𝗲 𝘀𝘁𝗿𝗼𝗻𝗴 𝗲𝗻𝗼𝘂𝗴𝗵 𝗚𝗧𝗠 𝗢𝗽𝘀 𝗱𝗶𝘀𝗰𝗶𝗽𝗹𝗶𝗻𝗲. 

We pulled apart the 7 biggest 2025 GTM reports

Scale VP, ICONIQ, Clari, Ebsta, Fullcast, Crossbeam, and Pavilion.

Different data sets. Different methodologies.
Same five problems showing up everywhere.

1. 𝐓𝐡𝐞 𝐝𝐚𝐭𝐚 𝐢𝐬𝐧'𝐭 𝐀𝐈-𝐫𝐞𝐚𝐝𝐲
48% of enterprises admit it
44% of seller contacts aren't even in the CRM
We're buying AI tools to run on broken data

2. 𝐀𝐈 𝐢𝐬 𝐬𝐭𝐮𝐜𝐤 𝐨𝐧 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐯𝐢𝐭𝐲
85% see productivity gains
Only 43% measure revenue impact
AI focused on outcomes 3-5x more likely to grow revenue

3. 𝐈𝐂𝐏 𝐝𝐢𝐬𝐜𝐢𝐩𝐥𝐢𝐧𝐞 𝐢𝐬 𝐦𝐢𝐬𝐬𝐢𝐧𝐠
High-ICP-fit accounts are 8x more sales efficient
But only make up 23% of the average pipeline
56% of teams still define ICP on gut feeling

4. 𝐄𝐱𝐩𝐚𝐧𝐬𝐢𝐨𝐧 𝐢𝐬 𝐮𝐧𝐝𝐞𝐫𝐟𝐮𝐧𝐝𝐞𝐝
52% of revenue comes from existing accounts
45% win rate vs. 19% on new logos
Most teams still over-resource new business

5. 𝐇𝐚𝐧𝐝𝐨𝐟𝐟𝐬 𝐚𝐫𝐞 𝐛𝐫𝐨𝐤𝐞𝐧
Aligned teams are 67% more likely to hit targets
54% of teams lack functional handoffs
46% have moved to a new model to get around it

None of these are new problems.
That's the point.

𝗪𝗵𝗮𝘁 𝗰𝗮𝗻 𝘄𝗲 𝗳𝗶𝘅 𝗻𝗼𝘄 𝘁𝗼 𝗵𝗶𝘁 𝟮𝟬𝟮𝟲 𝗻𝘂𝗺𝗯𝗲𝗿𝘀?

We wrote the full analysis:
- Breakdown of key findings over 7 reports
- A detailed look at the patterns that stood out
- Our take on what to prioritize going forward

Subscribe to 📰𝙏𝙝𝙚 𝙂𝙏𝙈 𝙎𝙘𝙞𝙚𝙣𝙘𝙚 𝘽𝙧𝙞𝙚𝙛📰 to get it in your inbox Saturday: https://bit.ly/49RCm0h
And/or....
Comment "Report" and we'll send it to you now

♻️ Repost for priority access

✌️

There's an entire generation of salespeople that can't prospect. 
It's a serious problem with a domino effect many miss. 

It's not just that we have less pipeline.

It goes much deeper......

1️⃣ 𝟳𝟳% 𝗼𝗳 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗶𝘀 𝗻𝗼𝗻-𝗜𝗖𝗣 𝗔𝗰𝗰𝗼𝘂𝗻𝘁𝘀 

High-ICP-fit accounts are 8x more sales efficient but made up only 23% of the pipeline for the average company in 2025. This is partially because sales reps are solely dependent upon marketing and SDRs to feed them and have to accept low quality deals and accounts into the pipeline. They have no way to say "I'd be better off spending my time prospecting into a better account."

2️⃣ 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆 𝗦𝘂𝗳𝗳𝗲𝗿𝘀

Close Rates are half of what they should be (10%-20% on average) so reps are working 2x the opportunities. This means that have half the time to do the same job, which means they don't prepare adequately and run mediocre discovery. 

3️⃣ 𝗣𝗼𝗼𝗿 𝗔𝗰𝗰𝗲𝘀𝘀 𝘁𝗼 𝗞𝗲𝘆 𝗦𝘁𝗮𝗸𝗲𝗵𝗼𝗹𝗱𝗲𝗿𝘀

When reps don't prospect, they can't afford to rock the boat and risk losing deals. This means they can't push to get access to key stakeholders. If they upset their champion and lose the deal they can't replace it by prospecting. 

4️⃣ 𝗗𝗲𝗮𝗹𝘀 𝗔𝗿𝗲 𝗦𝗺𝗮𝗹𝗹𝗲𝗿 𝗮𝗻𝗱 𝗠𝗼𝗿𝗲 𝗧𝗿𝗮𝗻𝘀𝗮𝗰𝘁𝗶𝗼𝗻𝗮𝗹

When reps are chasing the wrong accounts and talking to the wrong people, even when they win, they win smaller more transactional deals. 

5️⃣ 𝗦𝗮𝗹𝗲𝘀 𝗖𝘆𝗰𝗹𝗲𝘀 𝗔𝗿𝗲 𝗟𝗼𝗻𝗴𝗲𝗿

When they're not talking to the right people, deals drag on. Sales cycles get much longer. 

6️⃣ 𝗖𝗹𝗼𝘀𝗲 𝗥𝗮𝘁𝗲𝘀 𝗮𝗿𝗲 𝗠𝘂𝗰𝗵 𝗟𝗼𝘄𝗲𝗿 

This is a big part of why Close Rates are half what they should be. Reps can't walk away from unqualified deals, can't get access to the right people, can't run proper discovery, and can't challenge their prospects. As a result, they chase a lot of deals and win few of them. 

7️⃣ 𝗖𝗵𝘂𝗿𝗻 𝗶𝘀 𝗛𝗶𝗴𝗵𝗲𝗿

When reps land non-ICP accounts into small transactional deals without key stakeholders fully bought in churn skyrockets. I've seen this first-hand myself. I've sold and implemented Salesforce for 15 years now and the #1 differentiator between success and failure is having executive sponsorship. 

8️⃣ 𝗘𝘅𝗽𝗮𝗻𝘀𝗶𝗼𝗻 𝗶𝘀 𝗡𝗲𝗴𝗹𝗲𝗰𝘁𝗲𝗱 (𝗗𝗲𝘀𝗽𝗶𝘁𝗲 𝗕𝗲𝗶𝗻𝗴 𝘁𝗵𝗲 𝗕𝗲𝘀𝘁 𝗦𝗼𝘂𝗿𝗰𝗲 𝗼𝗳 𝗥𝗲𝘃𝗲𝗻𝘂𝗲)

52% of revenue comes from existing accounts
45% win rate vs. 19% on new logos

Expansion is the best source of revenue. It's far easier and close rates are ~3x but it requires prospecting skills to get in front of new stakeholders in an organization and expand the relationship. This is woefully neglected right now. 

How long can this last? 

🤔

I pulled many of these stats from a report we're releasing this week. 

If you want it......

Subscribe to 📰𝙏𝙝𝙚 𝙂𝙏𝙈 𝙎𝙘𝙞𝙚𝙣𝙘𝙚 𝘽𝙧𝙞𝙚𝙛 📰 to get it in your inbox Saturday: https://bit.ly/49RCm0h

And/or....

Comment "Report" and we'll send it to you now

✌️

We need to adapt to the new State of GTM.
GTM teams will miss 2026 targets because:

- They're using AI to solve the wrong problems
- Their data isn't ready for the AI they're buying
- Deals are dying between departments
- Their pipeline is full of bad-fit deals
- Expansion is underfunded

We consolidated 7 of the biggest GTM reports from 2025 to find out what went wrong.

Avoid making last years mistakes in 2026:

𝟭. 𝗨𝘀𝗲 𝗔𝗜 𝘁𝗼 𝗱𝗿𝗶𝘃𝗲 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗼𝘂𝘁𝗰𝗼𝗺𝗲𝘀
- "Phase 2 AI" is 3-5x more likely to grow pipeline
- It goes beyond solving for just productivity
- Use cases like microsegmentation, call scoring

𝟮. 𝗔𝘂𝗱𝗶𝘁 𝘆𝗼𝘂𝗿 𝗱𝗮𝘁𝗮 𝗯𝗲𝗳𝗼𝗿𝗲 𝘆𝗼𝘂 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲
- 48% of enterprises don't have AI-ready data
- Every AI tool you buy runs on this data
- Can't trust inputs = useless outputs

𝟯. 𝗚𝗲𝘁 𝘀𝗲𝗿𝗶𝗼𝘂𝘀 𝗮𝗯𝗼𝘂𝘁 𝘆𝗼𝘂𝗿 𝗜𝗖𝗣
- High-ICP-fit accounts are 8x more sales efficient
- 63% of CROs don't trust their ICP definition
- Analyze accounts, revise definitions, align
- Real ICPs are easy to close and hard to churn

𝟰. 𝗚𝗶𝘃𝗲 𝗲𝘅𝗽𝗮𝗻𝘀𝗶𝗼𝗻 𝗿𝗲𝗮𝗹 𝗿𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀
Faster cycles, higher win rates, fewer stakeholders
- Yet expansion is treated like an afterthought
- Treat it like a motion with ownership and process

𝟱. 𝗙𝗶𝘅 𝘁𝗵𝗲 𝗵𝗮𝗻𝗱𝗼𝗳𝗳𝘀
- 54% of teams have no functional handoffs between marketing and sales
- Deals die in these gaps every quarter
- Audit break points, build the process

The teams that fix these things will pull ahead.
The others will have the same problems next year.

What did we miss?

🤔

𝗪𝗲 𝘄𝗿𝗼𝘁𝗲 𝘂𝗽 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗮𝗻𝗮𝗹𝘆𝘀𝗶𝘀 𝘄𝗶𝘁𝗵 𝗼𝘂𝗿 𝗿𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝟮𝟬𝟮𝟲.

Subscribe to 📰𝙏𝙝𝙚 𝙂𝙏𝙈 𝙎𝙘𝙞𝙚𝙣𝙘𝙚 𝘽𝙧𝙞𝙚𝙛📰 to get it in your inbox Saturday: https://bit.ly/4b0hPs6

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♻️ Repost for priority access

✌️

7 Reports Infographic

First 90 days in GTM ops will make or break credibility. 
Most people spend it playing whack-a-mole.

𝐘𝐨𝐮'𝐫𝐞 𝐠𝐨𝐢𝐧𝐠 𝐭𝐨 𝐢𝐧𝐡𝐞𝐫𝐢𝐭 𝐚 𝐦𝐞𝐬𝐬
- Outbound is broken
- 55k "leads" (4 year old Zoominfo list)
- Pipeline full of deals that are 300 days old
- Pressure to implement AI  
- (Nobody can tell you what problem it'll solve)

The instinct is to try to fix all of it. 
- I still have to fight that instinct too

𝐃𝐨𝐧'𝐭 𝐭𝐫𝐲 𝐭𝐨 𝐟𝐢𝐱 𝐞𝐯𝐞𝐫𝐲𝐭𝐡𝐢𝐧𝐠 𝐚𝐭 𝐨𝐧𝐜𝐞.

The real work isn't documenting a process or updating Salesforce. That's the easy part. 

The hard part is getting an entire team to change what they do every day. 
 - That takes everything you've got. 
 - Which is exactly why you can't do five things at once.

𝐎𝐧𝐞 𝐩𝐫𝐢𝐨𝐫𝐢𝐭𝐲. 𝐎𝐧𝐞 𝐪𝐮𝐚𝐫𝐭𝐞𝐫. 𝐑𝐞𝐩𝐞𝐚𝐭.
- Pick one priority
- One improvement to GTM
- Document the process
- Build it into the systems
- Drive adoption
- Get management inspecting it consistently

𝐃𝐚𝐲 𝟗𝟎 = 𝐚 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞 𝐫𝐞𝐩𝐨𝐫𝐭 𝐲𝐨𝐮 𝐭𝐫𝐮𝐬𝐭
(As an example)

The end goal here is to pull up a report and actually believe what you see.

𝐓𝐡𝐚𝐭 𝐬𝐞𝐭𝐬 𝐭𝐡𝐞 𝐟𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧 𝐟𝐨𝐫 𝐞𝐯𝐞𝐫𝐲𝐭𝐡𝐢𝐧𝐠

Accurate forecasting. Better coaching. 
Reps who aren't chasing deals that will never close.

𝐃𝐨 𝐭𝐡𝐚𝐭 𝐟𝐨𝐫 𝐨𝐧𝐞 𝐚𝐫𝐞𝐚 𝐢𝐧 𝟗𝟎 𝐝𝐚𝐲𝐬

Then the next area the following quarter. 
6-12 months later your entire GTM engine looks completely different.

We explain the whole playbook on 🎙𝙂𝙏𝙈 𝙎𝙘𝙞𝙚𝙣𝙘𝙚🎙
"The GTM Ops First 90 Days Playbook"

👉 Listen here: https://bit.ly/4b28Nwn

 👉 Or read the newsletter here: https://bit.ly/4cNCWQY

✌️

How-GTM-Ops-Should-Run-Their-First-90-Days.pdf

CROs make the biggest impact in their first 90 days by fixing the fewest things. 

Most do the opposite.

𝐄𝐯𝐞𝐫𝐲𝐨𝐧𝐞 𝐭𝐫𝐢𝐞𝐬 𝐭𝐨 𝐟𝐢𝐱 𝐞𝐯𝐞𝐫𝐲𝐭𝐡𝐢𝐧𝐠 𝐚𝐭 𝐨𝐧𝐜𝐞

You walk in and the list hits you immediately
- Outbound is broken
- Inbound leads aren't getting follow up
- Pipeline is full of deals w/ no chance
- Oh and we need to implement AI 
- Whatever that means

𝗧𝗵𝗲 𝗶𝗻𝘀𝘁𝗶𝗻𝗰𝘁 𝗶𝘀 𝘁𝗼 𝘁𝗮𝗰𝗸𝗹𝗲 𝗮𝗹𝗹 𝗼𝗳 𝗶𝘁.

I've made that mistake. 

I used to do live white-boarding sessions
 - With CROs and all revenue leaders
 - It would quickly turn into a mess
 - Just as I described above
 - Problems all across GTM

I left these meeting with zero conclusions. 
 - Just a jumbled mess of things to fix. 

It made everyone more anxious.
 - Zero clarity gained
 - Everything was a priority
 - So nothing was a priority

𝐏𝐢𝐜𝐤 𝐨𝐧𝐞 𝐭𝐡𝐢𝐧𝐠. 𝐆𝐞𝐭 𝐢𝐭 𝐫𝐢𝐠𝐡𝐭. 𝐌𝐨𝐯𝐞 𝐨𝐧.

Not inbound AND outbound AND onboarding
AND pipeline AND AI implementation

One thing
- Get the process documented
- Get it built into the systems
- Get the team executing it the same way
- Get management inspecting it consistently
- Get to a point where you trust the reports

𝗧𝗵𝗮𝘁'𝘀 𝗶𝘁. 𝗧𝗵𝗮𝘁'𝘀 𝟵𝟬 𝗱𝗮𝘆𝘀.

Then do it again next quarter with the next thing on the list.

Actually I'm being conservative here.
 - We often tackle two areas in one quarter
 - Ex) Outbound AND Pipeline Management
 - If the team/motions aren't too big/complex
 - But we are laser focussed on those two things
 - And just on getting the foundation set in place
 - Then we can tackle two more in the next quarter

𝐓𝐡𝐚𝐭'𝐬 𝐡𝐨𝐰 𝐲𝐨𝐮 𝐫𝐞𝐯𝐚𝐦𝐩 𝐆𝐓𝐌 𝐢𝐧 𝐚 𝐲𝐞𝐚𝐫

The ones that try to fix everything?

I talk to them a year later and they still have the same problems.

We broke all of this down on the 🎙𝙂𝙏𝙈 𝙎𝙘𝙞𝙚𝙣𝙘𝙚🎙Podcast
- How to pick your first priority
- What "done" actually looks like at day 90
- Why clean reports > perfect processes
- How to say no when the ad hoc requests threaten to derail GTM Ops momentum

 👉Listen to "GTM Ops First 90 Days Playbook" here: https://bit.ly/4b28Nwn

 👉Or read the newsletter here: https://bit.ly/4cNCWQY

✌️

Only amateurs think Salesforce is too complicated. 

Let me explain with an analogy. 

Let's talk about modern farming. 

𝗠𝘆 𝗴𝗿𝗮𝗻𝗱𝗳𝗮𝘁𝗵𝗲𝗿 𝗳𝗮𝗿𝗺𝗲𝗱 𝟰𝟬 𝗮𝗰𝗿𝗲𝘀 𝘄𝗶𝘁𝗵 𝗮 𝗺𝘂𝗹𝗲.
 - Okay more like 100 acres
 - And I think he had a basic tractor. IDK.
 - But nothing like what farmers do today. 

I don't know a lot about farming. 
 - But I visited two farms recently. 

𝗙𝗮𝗿𝗺 #𝟭 - 𝟭𝟳,𝟬𝟬𝟬 𝗮𝗰𝗿𝗲𝘀 - 𝟭 𝗴𝘂𝘆
𝗙𝗮𝗿𝗺 #𝟮 - 𝟯𝟱,𝟬𝟬𝟬 𝗮𝗰𝗿𝗲𝘀 - 𝟯 𝗴𝘂𝘆𝘀

Notice the INSANE difference?

𝗔𝗹𝘀𝗼, 𝟱𝘅 𝗶𝗻𝗰𝗿𝗲𝗮𝘀𝗲 𝗼𝗻 𝘆𝗶𝗲𝗹𝗱 𝗽𝗲𝗿 𝗮𝗰𝗿𝗲

So......

That 1 guy with 17,000 acres.....

𝗛𝗲'𝘀 𝗽𝗿𝗼𝗱𝘂𝗰𝗶𝗻𝗴 𝟴𝟱𝟬𝘅 𝘄𝗵𝗮𝘁 𝗺𝘆 𝗴𝗿𝗮𝗻𝗱𝗳𝗮𝘁𝗵𝗲𝗿 𝗽𝗿𝗼𝗱𝘂𝗰𝗲𝗱. 
 - 170X acres x 5X yield/acre = 850X production

That's INSANE!

𝗡𝗼𝘄, 𝗹𝗲𝘁'𝘀 𝘁𝗮𝗹𝗸 𝗮𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝘁𝗲𝗰𝗵

What does this 1 guy use to farm 17,000 acres? 
 - He has a +$2,000,000 satellite connected tractor
 - He has millions more in other equipment 
 - He has GMO engineered seed as well

Is he complaining this is too complicated?

Or did he roll up his sleeves and basically get a PhD in farming technology so he could outproduce my grandfather by 850x?

If you think Salesforce is too complicated, just hire someone that knows what they're doing. 

Or find a tool that helps you produce more revenue. 

So you (Mr./Ms. CRO) can focus on scaling GTM. 

But don't complain about the complexity. 

(Part of) it is there for a reason. 

Same for every other tool and now, AI. 

✌️

"38% win rate? Those are rookie numbers."
- Kyle Norton's team increased theirs to 53%!

𝗛𝗶𝘀 𝘁𝗲𝗮𝗺 𝗱𝗲𝗰𝗼𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝘀 𝘁𝗵𝗲𝗶𝗿 𝗳𝘂𝗻𝗻𝗲𝗹 𝗺𝗼𝗻𝘁𝗵𝗹𝘆, 𝗲𝘃𝗲𝗻 𝘄𝗵𝗲𝗻 𝗻𝗼𝘁𝗵𝗶𝗻𝗴'𝘀 𝗯𝗿𝗼𝗸𝗲𝗻. 

They scored 150+ calls with AI, found that 10 of 12 winning behaviors were end-of-call skills, and coached accordingly.

𝟑𝟖% → 𝟓𝟑% 𝐰𝐢𝐧 𝐫𝐚𝐭𝐞𝐬 𝐢𝐧 𝐨𝐧𝐞 𝐪𝐮𝐚𝐫𝐭𝐞𝐫.

Kyle Norton, CRO at Owner.com, sat down with us on the GTM Science podcast. 

𝐓𝐡𝐞 𝐜𝐨𝐧𝐯𝐨 𝐰𝐚𝐬 𝐠𝐨𝐥𝐝:
- Why most enablement "totally sucks"
- How he trains reps so skills actually stick
- Why he doubled enablement + hired fewer reps
- How he decides what to fix and what to ignore
- Why the CRO job at $5M is a sales manager job
- How he scaled from $2.5M to $60M+ in 3 years

Kyle told us this conversation is basically Owner.com's secret sauce.

His words, not ours.

"CRO Stories: The Investments and Priorities That Took Owner.com to $60M ARR " on 🎙𝙂𝙏𝙈 𝙎𝙘𝙞𝙚𝙣𝙘𝙚🎙 
 
👉 Listen on Spotify: https://bit.ly/4b28Nwn
👉 Listen on Apple: https://apple.co/3y8lch6

✌️

Increasing I think 20 hrs/wk is the ideal workload. 

𝗦𝗽𝗲𝗰𝗶𝗳𝗶𝗰𝗮𝗹𝗹𝘆, 𝟮𝟬 𝗵𝗿𝘀/𝘄𝗸 𝗼𝗳 𝗿𝗲𝗰𝘂𝗿𝗿𝗶𝗻𝗴 𝗮𝗰𝘁𝗶𝘃𝗶𝘁𝗶𝗲𝘀

Been working on this w/ my marketing manager
 - Every week she has ~20 hrs/week of work
 - This is down from maybe ~30 hours
 - Because she was stressed

How is that possible?
 - 30 hours of recurring activities
 - Plus one-time initiatives
 - Plus emergencies
 - Plus getting sick
 - Plus holidays
 - Plus plus

This left her in a constant state of feeling behind

So, we're working on three things. 

𝟭. 𝗚𝗲𝘁 𝘁𝗼 ~𝟮𝟬 𝗵𝗿𝘀/𝘄𝗸 𝗼𝗳 𝗿𝗲𝗰𝘂𝗿𝗿𝗶𝗻𝗴 𝗮𝗰𝘁𝗶𝘃𝗶𝘁𝗶𝗲𝘀
 - Try to do these tasks first
 - This is our content engine
 - Stuff that has to go out weekly

If this is done by noon on Wednesday, we can all breath a sigh of relief here. If one piece of content takes longer, we have a healthy margin for error. 

𝟮. 𝗦𝗲𝗽𝗮𝗿𝗮𝘁𝗲 𝗼𝗻𝗲-𝘁𝗶𝗺𝗲 𝗮𝗰𝘁𝗶𝘃𝗶𝘁𝗶𝗲𝘀
 - The website breaks
 - We onboard a new agency
 - We decide to start doing ads
 - And also building the backlog
 - Producing 2x content in one week
 - That's also not indefinitely recurring

The list of this stuff is endless and it often interferes with the recurring tasks such that she is (as am I) scrambling at hit important deadlines for the things that HAVE to go out. 

Some of this stuff has to get fixed ASAP (like the website breaking) but other things like launching our first ad campaign can wait a couple of days. 

𝟯. 𝗣𝗿𝗼𝘃𝗶𝗱𝗲 𝘁𝗶𝗺𝗲 𝘁𝗼 𝘁𝗵𝗶𝗻𝗸
 - Get workload down
 - Remove needless pressure
 - So people have time to think

This is the only way anyone can "be strategic." We all need time to breath. With the above structure, she can work on one-time activities and have time to breath so she can think about the bigger picture. 

𝗪𝗵𝘆 𝗶𝘀 𝘁𝗵𝗶𝘀 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁? 𝗖𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝗰𝘆 𝗶𝘀 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴. 

I've been doing this for 6-12 months myself and I'm realizing that the only way to stay consistent, to wake up every single day and go to the gym, post on LinkedIn, do my sales activities, manage the business, etc. is to get this to ~20 hours per week or less. 

If we push this to 30, 40, 50, then there is no time for anything else. That means that onboarding a new hire, redesigning the website, etc. etc. means that my consistency falls off. 

Something has to give. 

This for me is the most productive work structure. 

But what works for you and/or your team?

🤔

No one's been a CRO in 2026 before.
This is all new ground for us, things are changing.

It's not that the old playbooks are obsolete
But they're not how things get done anymore.

Jody Geiger, co-founder of AI Revenue Studio discussed these changes on our podcast.

𝐓𝐡𝐞 𝐛𝐞𝐬𝐭 𝐆𝐓𝐌 𝐨𝐫𝐠𝐬 𝐚𝐫𝐞𝐧'𝐭 𝐛𝐮𝐢𝐥𝐭 𝐨𝐧 𝐭𝐨𝐨𝐥𝐬

They're built on:
- Clarity
- Trust
- Rhythm

RevOps taught us the power of systems.
But also the limits.

You can't dashboard your way to growth.

𝐖𝐡𝐚𝐭 𝐰𝐢𝐧𝐧𝐢𝐧𝐠 𝐭𝐞𝐚𝐦𝐬 𝐝𝐨 𝐝𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐭𝐥𝐲
- They build lightweight systems
- Systems that create space to think
- Not just click without context

"I want them to turn their brains on," Jody says.

AI can automate busy work.

But it won't automate:
- Judgment
- Empathy
- Curiosity

Those things win deals.

𝐋𝐨𝐬𝐢𝐧𝐠 𝐭𝐞𝐚𝐦𝐬 𝐜𝐡𝐚𝐬𝐞 𝐬𝐩𝐞𝐞𝐝 𝐛𝐞𝐟𝐨𝐫𝐞 𝐭𝐫𝐮𝐬𝐭

The winning teams move fast because:
- They ground themselves in understanding
- They build from connection and curiosity
- They create space for experimentation
- They make mistakes ("first pancake is burnt")

𝐈𝐧 𝐲𝐞𝐬𝐭𝐞𝐫𝐝𝐚𝐲'𝐬 🎙𝙂𝙏𝙈 𝙎𝙘𝙞𝙚𝙣𝙘𝙚🎙𝗣𝗼𝗱𝗰𝗮𝘀𝘁...

We covered:
- Why process isn't the enemy
- Building systems with learning loops
- Finding friction in your GTM motion
- Making space for team experimentation
- The skills that define elite sellers
- Context beats content every time
- Creating a culture of agency
- How to chart a path that doesn't exist yet

We're in a new world.
Leaders need to shift and grow.

𝗛𝗼𝘄 𝗮𝗿𝗲 𝘆𝗼𝘂 𝗰𝗿𝗲𝗮𝘁𝗶𝗻𝗴 𝘀𝗽𝗮𝗰𝗲 𝘁𝗼 𝘁𝗵𝗶𝗻𝗸?

🤔

Listen to the episode "Building a Culture of Innovation with AI" on 🎙𝙂𝙏𝙈 𝙎𝙘𝙞𝙚𝙣𝙘𝙚🎙 here: https://bit.ly/4b28Nwn

✌️

I teach revenue teams how to use AI | 20+ years leading and scaling sales orgs | Co-Founder, AI Revenue Studio

AI Revenue Studio

Our board wants revenue impact THIS quarter.
Not 90 days from now.

𝐁𝐮𝐭 𝐨𝐮𝐫 𝐭𝐞𝐚𝐦 𝐡𝐚𝐬 𝟏𝟎𝟎 𝐭𝐡𝐢𝐧𝐠𝐬 𝐭𝐨 𝐟𝐢𝐱
- Visibility gaps
- Pipeline struggles
- Lost deals and churn
- Missed expansion
- AI implementation
- And zero direction on where to start

We can't fix 100 things at once.
But we CAN find quick wins with longterm impact.

How?

𝐒𝐭𝐞𝐩 𝟏: 𝐅𝐢𝐧𝐝 𝐭𝐡𝐞 𝐛𝐢𝐠𝐠𝐞𝐬𝐭 𝐠𝐚𝐩

Where is the most revenue at stake?
- New business or NRR?
- Close rates or more pipeline?
- Reduce churn or expand more?
- Inbound or outbound?

𝐈𝐭'𝐬 𝐮𝐬𝐮𝐚𝐥𝐥𝐲 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞 𝐦𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭

When CROs say they need more pipeline, we push back.
- A broken sales process wastes pipeline
- Gaps exist in both new biz and expansion
- Fix pipeline management first

Here's a quick way to determine the priority:
- Gross Retention well below 90% → Renewals
- Net Retention well below 100%  → Expansion
- Low close rates, long cycles → Pipeline Mgmt
- Strong close rates, thin pipe → Pipeline Gen

𝐒𝐭𝐞𝐩 𝟐: 𝐒𝐭𝐚𝐫𝐭 𝐚𝐭 𝐭𝐡𝐞 𝐛𝐨𝐭𝐭𝐨𝐦 𝐨𝐟 𝐭𝐡𝐞 𝐩𝐲𝐫𝐚𝐦𝐢𝐝

Fundamentals and Adoption can take weeks.
Optimization and Amplification can take years.

Cover your biggest priority areas in 1-2 quarters:
- Pipeline Mgmt → Inbound/Outbound
- Then Renewals → Expansion
- Or whatever your biggest gap is

Quick wins live at the bottom of the pyramid.

𝐒𝐭𝐞𝐩 𝟑: 𝐁𝐮𝐢𝐥𝐝 𝐚 𝐫𝐨𝐚𝐝𝐦𝐚𝐩

Get CRO, leadership, and ops on one plan:
- Prioritize initiatives
- Tackle highest-impact first
- Create a system to triage ad hoc fires

No massive reorgs.
No strategic pivots.

Quick wins that set the stage for long-term scale.

We broke all of this down in the
𝗚𝗧𝗠 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 𝗣𝘆𝗿𝗮𝗺𝗶𝗱 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 𝘃𝟯.𝟬

Access the Framework and all assets here
 👉 https://bit.ly/4ryrLA8

✌️

GTM Efficiency Pyramid - Quick Wins - Carousel

Founder | B2B GTM | Scale without headcount by mapping your playbooks into an AI revenue engine

Be honest - how many Linkedin posts have you seen this year saying that XYZ tech/playbook/widget is absolutely essential to your GTM this year?

Probably a lot

We now have thousands of sales and marketing technologies on the market

And all of them are pitching their solution as best in class

With playbooks, agencies, influencers to sell them

And yes, we have preferred tech vendors

Here's the difference

We don't throw you in canned playbook, we actually look at your Go to Market model before making recommendations

Let me tell you a funny story

I talked with an SDR team that was booking 80 meetings a month with parallel dialers and 10k emails per SDR per month

But 60% of their meetings got disqualified

Why?

They didn't qualify target accounts before doing outreach

Tech and playbooks don't save you deploy the wrong one at the wrong time

So what do we do different?

When you work with us, we start with an assessment

We look at your funnel metrics, your best customers, your messaging/copy, and get input from your team on detailed attributes that make up a great customer

That you CAN'T find in an off the shelf tool

After that we use our knowledge of best practices and tooling to identify the biggest opportunities to unlock more revenue per headcount in your team

This could look like

> Customer analysis
> Serviceable Addressable Market Mapping (because TAM is where you lose deals not win them)
> Target Account Lists
> Automated Contact Prospecting & Enrichment
> Pipeline Validation (we build out a script, test it to book meetings for you, help you take the meetings through completed discovery with next steps, then give you a completed call framework, email sequence, and discovery framework)
> Outbound Sales Team Coaching (Phone first)
> Sales Process Optimization
> Managed Cold Emails & Cold Calling
> Inbound Lead Flow Optimization
> AI Business Case Building (which we used to open a $300k+ opp at UPS)
> Implementation of Nooks, Clay, Evergrowth, and other sales tooling

Yes, we do that under one roof

Yes, it was very hard to find a team good enough to do all of this in one place

If you want to learn more, book a time here: https://calendly.com/b2bcatalyst/your-gtm-system-audit-linkedin
> Cold Email Infrastructure

Scott Martinis

GTM engineers & AI platforms are trying to figure out GTM context engineering by reinventing product marketing from first principles. Most will fail.

Context - I am seeing a ton of really smart people like Nico Druelle, Charlie Saunders, Alex Fine🌲, 🏍benyamin ‎ and others start to work on the problem of how to create centralized context libraries to iterate on messaging and targeting.

I am also seeing many platforms try to do the same thing.

The operators I included above will probably succeed. 

The platforms and GTM engineers that follow in their footsteps will largely fail.

Why?

Simply put - GTM context engineering is effectively reinventing a complete and fleshed out disciple (product marketing) from scratch.

Given INSANE amount of training volume, ML modeling (Karpathy released a new library to help automate this) CAN effectively invent the necessary cognitive architecture to help generalize those patterns.

Outreach could probably do this if they really wanted to. Gong as well.

But that's a waste of time, and anyone with less training data will probably fail horribly.

Think about what ACTUALLY happened to optimize messaging in high performing GTM orgs years back:

Product marketers would run meeting analysis, win/loss interviews, customer interviews, and talk with analysts.

They would then consolidate this into strategic narratives, positioning frameworks, competitive battlecards, ICP/segment/persona definitions, and value frameworks for major audiences.

If you want to do context engineering, you could try to reinvent this discipline from first principles.

But you're going to demonstrably slower than people who just... 

Interview good product marketers 

And figure out how to automate the product marketing analysis pipeline.

The marketers I've been most recently impressed with on this front are Emily Pick, Julia Hugg, Trinity Nguyen 💎

Octave, of course, is way, way ahead of the pack here.

Instead of trying to figure this out all by themselves, GTM engineers and revops leaders should take the shortcut and take the time to learn product marketing from elite practitioners instead

This was why all the AI SDRs failed by the way. 

It's not the lack of data foundations that broke them as many revops people supposed (though that doesn't help)

It was actually the lack of understanding the GTM strategy is quite complex, and guessing and checking without proper PMM foundations is not fast enough to get ROI on automated outbound.

What does this mean?

Well, the actual foundation of your GTM strategy is not revops OR GTM engineering, it's REALLY good product marketing

Both of those functions rely on good PMM to build good data models and automated workflows... though they both relying to some degree on well thought out enablement playbooks to know what to include in the data model and what to automate as well.

TLDR: model your context engineering on PMM. Will save 6-12 months.

I make AI work for complex B2B GTM through pipeline impact, not data projects | CEO, B2B Catalyst

So it turns out you can CSV dump from every GTM tool into your GitHub repo then Claude Code can write you data lake scripts in like... 20 minutes?

And if you dump in cold call transcripts from Gong or Chorus then you can basically rewrite any messaging playbook your org has in a few hours

Working next on ways to extract use cases from sales calls at scale, map in depth what messaging wins and loses

Then take the use cases and scrape online presence of won deals to extract custom signals

Tag won and lost deals with them

And build custom signal models predicting win rate and ACV

Future is pretty wild

Next up:

- Automated coaching briefs across the org
- Down funnel marketing campaign attribution
- Automated and targeting iterations for marketing campaigns and sequences
- Weekly or monthly auto playbook updates broke. down by segment
- Weekly or monthly value framework updates, battle cards, competitor battle cards (possibly automated)

Of course the more normal use cases like 

TAM scraping, signal sourcing, account prioritization, contact sourcing, qualification, classification 

TitanX phone intent

AI outbound personalization on emails calls LinkedIn

AI content generation and amplification 

AEO

AI inbound and outbound SDRs

Personalized ABM content

Personalized meeting prep

ETC

Candidly those feel a bit more pedestrian and table stakes to me though in 2026

Still... very exciting possibilities for GTM orgs

The key I think is knowing where to start

Which is usually your biggest bottleneck 

(DM me "context lake" if you want this in your org)

Every GTM intelligence tool is racing to answer the same question: who should we target?

Intent data. Buying signals. De-anonymization. Account scoring.

The targeting layer is getting genuinely good. 

And it's about to be commoditized. 

The same way signal aggregation became table stakes after Clay and 6sense turned it into infrastructure.

There's a deeper problem.

These tools are optimized for finding people who want to buy tools like them. They surface intent signals and firmographic matches.

They don't find the prospects where YOU have a differentiated advantage at closing.

That's a different ICP layer. Not "who looks like our customers" but "who has a problem we solve better than anyone else."

Most teams build messaging off the same shallow foundation. Company value props plus signals. "They just raised a Series B, mention growth." "They posted a sales role, mention scaling."

Relevant first line. Generic pitch.

The signal tells you WHEN to reach out. Your value prop tells the buyer what YOU think matters. 

Neither one tells you what the BUYER thinks matters.

The thing that converts is explaining why your solution beats the buyer's current state in a way they actually agree with.

That's differentiation. And it's missing from almost every discussion on signals & ABM I've seen. 

A VP of Ops at a 200-person logistics company. What's her job-to-be-done? What objection does she raise first?

That's not in your intent data. It's in your call recordings. It's in the patterns your best reps know but nobody's formalized.

Pull your last 30 closed-won deals. Listen to the first calls. What did the buyer say they cared about? Group them.

You'll find 3 to 4 patterns. Those are your real use cases.

Each one should shape both WHO you target and WHAT you say. Not a template with a different first line. A different reason to meet, built on why your solution changes their current state.

The targeting will keep getting smarter. The message won't get better until someone studies the buyer.

If you want help building this layer, DM me.

I rebuilt my company's website through an MCP inside Claude Code. Told my AI co-worker what to change. It read the Webflow data directly, made the edits, and published.

Mostly. I still had to open Webflow for some formatting changes the MCP couldn't handle. But 80% of the work happened without touching the UI.

That alone changed how I think about platforms.

MCP is Model Context Protocol. It lets AI talk directly to a platform's data and take actions.

Every legacy platform is walking the same path right now.

Step 1: Platform. You log in, click buttons, build reports, configure sequences. Standard SaaS.

Step 2: The AI can READ the platform's data. Pull reports, see pipeline, check analytics. You still log in to do anything.

Step 3: The AI can ACT. Create records, update fields, trigger workflows. You log in less.

Step 4: The AI owns the domain. It decides what to do, does it, reports back. You make decisions. You rarely touch the platform.

I'm somewhere between step 3 and 4 with Webflow. It's not perfect. But the direction is clear.

Now think about Salesforce, HubSpot, Outreach, Salesloft.

Once an AI can read your CRM, update records, pull analytics, manage sequences, and trigger workflows.. what's the UI for?

Salesforce has Einstein. HubSpot has Breeze. Outreach has "AI everywhere."

Bolting a chat window onto a legacy platform is step 2.5 at best. And the companies building step 4 aren't starting from step 1. They're starting fresh.

Pick the GTM platform you use most. Map it against the 4 steps. Where the AI feature actually sits vs. what the marketing claims will tell you everything you need to know about that vendor's roadmap.

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