Snowflake

Simplify data architectures and deploy AI to transform customer experiences, strengthen risk management and power business workflows with Snowflake AI data cloud for Financial Services and supercharge your use cases:

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360 Customer Analysis
Financial crime detection
Regulatory reporting
Marketing analytics
Insurance underwriting
Claims management
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Find our success stories here: https://www.snowflake.com/en/solutions/industries/financial-services/

Enterprise Account Executive - Financial Services Industry

Kertos

Automating DPO and Legal Compliance processes. Seed stage: 10x Founders, seed + speed, Redstone.

Advisor

Luminovo

Electronics supply chain platform for procurement & quoting processes. Series-A: Chalfen Ventures, Tencent, Verve Ventures, Khadjavi Capital Partners, La Famiglia, Cherry Ventures.

Valuecase

Built up the GTM motion, trained team, and closed complex large deals like Domo and Usercentrics.

Sales Team Lead

Fides

One-stop-shop for Corporate Governance. Seed stage: Sequoia, La Famiglia, Auxxo Female Catalyst.

Pavilion

Course: Revenue Architecture. As a revenue leader, learn how to architect your revenue in order to achieve sustainable growth by understanding the fundamental principles of recurring revenue and the specific frameworks to apply across your GTM team.

Sales Trainer

Winning by Design

G2.com #1 rated Sales and Go-To-Market Consulting and Training Company.
Inc.com #147 of top 5000 private companies.
Inc.com - third year in a row - top 1000 Fastest-Growing Private Companies in America.

Winning By Design helps Venture Capital and Private Equity backed Hyper-Growth companies to scale their Go-to-Market activities backed by a Science-based-Sales Approach that focusses on Customer-Centrity and Growth Model Forecasting.

Winning by Design's recurring revenue operating system runs literally dozens of unicorns, with several having now listed as public companies. Clients listed here: https://winningbydesign.com/clients/

Growth Consultant

CoffeeCup App

saasfunnels

We help B2B Founder Sales Teams to follow the right Go-To-Market Strategy and implement Best Practice Account Based Prospecting Campaigns.

🚀 100% hands on: Results in 2 weeks, Up to 20% meeting conversion
🚀 "One-Click-implementation": We built it with zero implementation effort for busy founders
🚀 Proven Blueprints: Data-base with over 500+ demand gen campaigns and metrics

Blueprints built upon concepts from the best of the best: 
salesprocess.io, pavillion, pre-sales collective, y-combinator startup school;

Our clients are backed by the best VCs worldwide: 
Y-Combinator, Vito Ventures, Coparion, High-Tech Gründerfonds, Hasso Plattner Ventures, and many more...

Founder, Growth Consultant

Cobrainer GmbH

Cobrainer’s SkillsAI truly understands the fine details of your unique industry, your company, and each individual employee. It brings the right skills to where they are needed most and it helps you build the critical missing skills with confidence. 
Responsibilities: Pipeline building, new logo acquisition and account based selling into DACH Enterprise companies.

Enterprise Business Development Manager

Hi, I am Johannes 👋  I love bringing tech to people and have spent the last 10 years in go-to-market and sales for high tech software products into DACH markets as consultant, team lead and account executive.

Happy to connect and start a conversation.

Meet me with Snowflake ❄️ and discover capabilities of Data and AI for Financial Services at AI in Banking Handelblatt Conference on 04/05th Sept, 
Info here https://live.handelsblatt.com/event/ai-in-banking/

Johannes Stich

⚙️ SaaS Enthusiast | 🤝 Student of sales since 2007 | 🤖 AI Explorer

If your best salesperson had unlimited time to research every account, who would they pick, what would they want to know and say? 

The systems I build bake this into code and accelerate processes that took weeks compressed into minutes. 

I support their wins by building bespoke and deeply customized revenue systems for companies that have clear PMF and repeatable sales processes. 

—-
16+ years of international, multi-domain, multi-functional experience at Apple and B2B scale-ups. Lead of Clay Club in NYC. 

Fun fact 🌋: I’ve been inside an active volcano.

Andreas Wernicke

My life is cooked, day/night cycles are finally obsolete

computa, activate anti-eye burn sequence. 

would you like a dark mode toggle in Clay? 🖲️

The State of GTM Engineering Report is out, and I’m in it. Real data on comp, tools, and where the role is heading. 

72% of GTMEs report direct revenue impact; the report finally gives us numbers about this still-emerging space.   

Amazing to be in great company with Kellen Casebeer , Jordan Crawford , Willy Hernandez and others, and big thanks to put this all together to Garrett Wolfe , Maja Voje and Alex Lindahl.  

My quote is about that the hard part is not executing GTM work, it's really doing it fast, well, consistently and absolutely MASTERING the learning-and-iteration loop. 

Using context as the 'what' to do and 'how' to do it, and the best tools (for me that's Claude Code combined with Clay) to execute on that, that's my take on the winning combo.  

No comments needed, just grab the report here: stateofgtme.com

"How do I use Claude Code?" Wrong Question: Start with the "What do I want to build." 

TL;DR:

The technical 'how' is a solved problem. Describe what you want, the tool handles execution.

What does good look like for this task? -> That's the question that compounds.

Once you're clear on the what, getting started is one conversation with claude.ai away.

To make this concrete, in the clip I show a super small but powerful use case (CRM property schema), and why the "What do I want to achieve", not the "how do I technically achieve it" is what matters.

The CRM example in the clip isn't about the Google Sheets integration. That's five minutes. 

It's shows that what matters is my taste, my methodology. It's not how tools connect. 

- naming schema
- metadata properties
- what does auditability (is this a word?) require

That document is the asset. 
The integration is a commodity.

For anyone sitting outside this space wondering where to start – skip the tutorials.

Go to claude.ai and say something like:

"I lead revenue operations. I keep hearing about Claude Code but don't know where to start. I'm somewhat technical, but have no development. Help me figure out what this could actually do for my team – ask me about what we're trying to achieve and help me think through where to start."

That conversation is worth more than any how-to video, IMHO. 

The technical how is mostly handleable once you're clear on the what.

Claude Code Context OS Hands-on example: Targeting the exact right people. 

You don't really want to target "VPs". You want to target VPs of a specific function*. Does your system do that well, specifically for your market? Enter: Context. 

(This is only one little element of targeting with precision, if that is worth it in your market, but a good example for this.) 

'Context' is thrown around a lot. It's all the rage with GTM builders. I see that it's quite nebulous when you're not already on this train. 

To make this more vivid to understand how incredibly powerful context systems in GTM are, let me show a concrete, hands-on example how Claude Code, Clay and Context make outcomes orders of magnitude better and more consistent.

Let's use this example: 

A title says "Vice President." Your GTM knows it means something different in Capital Markets than it does in Operations. Something different in the US than in Europe. That translation, from raw title to the target that actually matters, requires your judgment, not the model's.

This is what context does. It takes what your team already knows about good and makes it operable.

In the video I walk through a live build: title decomposition into 'seniority' and 'function', with the iteration loop that makes it compound:

- Initial Data build
- Clay runs the data agent against your contacts
- The output gets human-reviewed – what was right, what was wrong, and why
- Claude Code captures that feedback and rebuilds the context document
- The updated document feeds the next run in Clay
- Every edge case encoded. Every version traceable.

What started as a one-off title decomposition becomes a reusable artifact that gets sharper every iteration. (It's just small part of a bigger build.)

This is one use case, and the same principle applies to every 'decision' your GTM makes across classification, qualification, CRM integration, messaging...)

There is no real limit how far this can be pushed and scaled for near-perfect data in your CRM, in your systems or your messages. 

It's not happening with the click of a button, but it's really just a choice. 

You want this and invest in it today, or not and fall faster behind than you can say "I don't buy this hype!"

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The Battle

Johannes Stich

Andreas Wernicke

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Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Andreas Wernicke's LinkedIn Performance

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