New to Cannonball GTM? Start with our beginner's guide - it explains the core methodology and will make everything below much clearer.
Last Friday's livestream was... let's call it "loosely planned." Jordan had built something over the weekend (because that's what Jordan does), and we decided to throw Revv into the cannon without much prep beyond Doug spending two hours crafting the world's worst piston joke.
What emerged was probably the most demonstrative Cannonball we've done to date. Not because we're geniuses, but because we stumbled into something that actually works: a systematic approach to turning any brand website into qualified leads in about an hour.
Here's what happened, why it worked, and how you can replicate it without listening to Doug's dad jokes.
The Problem: GTM Research Takes Forever
We've all been there. You find an interesting brand, spend hours researching their market, their pain points, their competitors, trying to figure out who actually needs what they're selling. Then more hours trying to find actual prospects. Then even more hours crafting messages that don't suck.
By the time you're done, you've burned a day and you're not even sure you're pointed in the right direction.
The traditional approach looks like this:
Research the brand and their ICP
Understand their market dynamics
Identify pain points and buying triggers
Find companies experiencing those pain points
Research individual prospects
Craft personalized outreach
Each step requires multiple prompts, different tools, and a lot of manual synthesis. It's thorough, but it's slow.
What We Built: The Research-to-Leads Pipeline
Instead of six separate workflows, we created one mega prompt that handles the entire research-to-leads pipeline. Here's how it breaks down:
Phase 1: Deep Brand Analysis
The prompt starts by extracting everything about the target company: their ICP, value prop, competitive landscape, and most importantly, what changes in the world make their solution urgent right now.
For Revv, this meant understanding that ADAS (Advanced Driver Assistance Systems) are now on 92.7% of new vehicles, but many collision shops are still subletting calibration work or doing it manually. The regulatory pressure is intense; Maryland literally made improper calibration an "unfair deceptive practice."
Phase 2: Pain Point Investigation
Rather than guessing at pain points, the prompt searches for actual evidence of market pressure. It looks for regulatory changes, compliance requirements, insurance mandates, and other external forces creating urgency.
The Revv discovery: State Farm now requires specific documentation on every job (not just State Farm claims), and shops that can't provide it are getting kicked out of their preferred provider networks.
Phase 3: Targeting Signal Development
This is where most people stop thinking and start spraying. The prompt instead identifies specific, publicly available signals that indicate a company is experiencing the pain right now.
For Revv, these signals included: job postings asking for manual ADAS research, website language about "subletting calibration to third parties," and pricing that suggests they're not capturing the full calibration revenue.
Phase 4: Prospect Research & Validation
The prompt then goes hunting. It doesn't just find companies that fit a demographic profile - it finds companies showing multiple signals that they're drowning in their current state.
We ended up with five Maryland shops, each with 3-5 pieces of evidence suggesting they needed Rev's software immediately. Complete contact information, pain point documentation, and revenue impact estimates.
Phase 5: Message Generation
Finally, it writes the outreach. Not generic templates, but messages that demonstrate you understand their specific situation without being creepy about it.
The key insight Jordan shared: "There's a separation between what you know and what you say, and that gap is actually greater than you would think."
The Rev Results: From Zero to Qualified in 60 Minutes
Starting with just revvhq.com, here's what we generated:
Mayerless Collision Center (Baltimore, MD)
Evidence: Subletting ADAS calibration to third parties
Pain: Revenue leakage from lost calibration fees
Opportunity: ~$15K/month additional gross revenue
Message: "You're subletting ADAS to a third party partner while State Farm pushes proof-heavy documentation..."
Four additional shops with similar detailed profiles, contact information, and custom messaging.
Each prospect had multiple validation points - website language, Google reviews, job postings, compliance gaps. Not demographic guessing, but actual evidence of need.
Why This Approach Works (When It Works)
The mega prompt method works because it mirrors how your brain actually processes GTM research, just faster and more systematically. It forces you to:
Understand the customer's customer - Revv helps shops make more money from their customers' insurance claims
Find external pressure - Regulatory changes create urgency that transcends product features
Look for proof, not profiles - Public signals that someone needs help right now
Sequence the message - Lead with insight, not product pitch
But here's the thing, this isn't magic. It's methodology compressed into a prompt.
The Mega Prompt: What's Inside
We spent the last 15 minutes of the livestream creating what Jordan calls the "Ultra Mega Prompt" - a single prompt that captures this entire workflow for any vertical SaaS company.
The Mega Prompt Structure:
Phase 1: Brand Intelligence Extraction
- ICP identification and validation
- Value prop analysis
- Competitive landscape mapping
- Market timing assessment
Phase 2: Market Pressure Research
- Regulatory environment analysis
- Industry change documentation
- Compliance requirement mapping
- External urgency identification
Phase 3: Targeting Signal Development
- Public data signal identification
- Pain proxy development
- Competitive displacement indicators
- Implementation readiness markers
Phase 4: Prospect Discovery & Validation
- Multi-signal prospect identification
- Evidence documentation
- Contact information compilation
- Opportunity sizing
Phase 5: Message Crafting
- Pain-point-specific messaging
- Curiosity-driven subject lines
- Value-forward positioning
- Response optimization
Phase 6: Quality Validation
- Message-market fit assessment
- Signal strength verification
- Outreach sequence recommendations
- Scale-up guidanceImplementation: Start Here
If you want to try this approach:
Pick one vertical SaaS (horizontal SaaS works too, but requires more segmentation)
Spend 30 minutes understanding their business model and customer base
Run the research workflow - either manually or with the mega prompt
Generate 10-20 prospects with strong pain signals
Send messages immediately - don't overthink it
Measure response rates - if under 5%, revisit targeting or messaging
The goal isn't to build your entire pipeline from this. It's to validate whether you're pointed in the right direction before you scale anything.
What's Next
We're testing this approach across different verticals and refining the prompt based on what works (and what doesn't). The early results are promising, but we're not declaring victory yet.
As Jordan reminded us during the stream: "You are the guide, not the river. Tools are tooling is for tools. Process over prompts."
The mega prompt is just tooling. The methodology, understanding pain-based segmentation, identifying external pressure, finding public signals of need - that's what actually moves the needle.
