Phase 01
Mind Merge
Any successful engagement starts with shared understanding — not just of your product, but of where you are in your growth lifecycle and what winning looks like from where you sit. During this phase we'll get deep on your business, your product, and your market so we can agree on values, working style, and what we're actually trying to achieve together.
Working backward from where you want to be in three years, we'll identify the lead, user, and customer inputs necessary to get there within the product-solution fit, product-market fit, and scale stages of your growth lifecycle. Before any tactics, we run an initial AI-assisted scan of your competitive landscape and positioning so we walk into this conversation with context, not just questions.
What you'll get
- Clarity on the engagement scope and working model
- Minimum success criteria tied to your product lifecycle stage
- A preliminary read on your biggest positioning and pipeline gaps
- Recommended next steps
Phase 02
Problem Extraction / Market Audit
Review the problem you've identified, then dig deeper into it with real potential customers — not assumptions — to verify the opportunity before committing resources to a solution. This problem extraction can be a grind, but defining the weight and nuance of the problem now can save months of building the wrong thing.
AI-powered competitive analysis maps the problem space before we talk to prospects, so interviews are focused and the synthesis is faster. We're looking to confirm that the market feels the pain acutely enough to pay for a solution, and that your offering addresses it in a way competitors don't.
What you'll get
- Problem and solution definitions validated with real market input
- Key risks and dependencies identified before you build against them
- Opportunity sizing — realistic market depth and capture range
- Value assessment — what the problem costs buyers versus what they'd pay to solve it
Phase 03
Positioning / Targeting Audit
Most products lose deals not because of what they do, but because of how — or to whom — they describe it. This phase finds the angle that makes the right buyers move. We'll assess your relative position in the market, sharpen your unique selling proposition, and identify the specific segments and messaging that will generate the most traction.
This phase also includes a GEO/AEO audit — how your product appears (or doesn't) in AI-generated answers from ChatGPT, Perplexity, Gemini, and Claude. B2B buyers are increasingly starting their research in AI before they ever visit your website. Getting that positioning right is no longer optional.
The output of this phase directly informs the beachheads we'll test in Phase 4. Messaging that isn't grounded in buyer language and competitive positioning doesn't compound — it just spends.
What you'll get
- Value and pricing analysis — where you're leaving money on the table or pricing yourself out
- Persona definitions — the specific buyers, their triggers, and what they need to hear to move
- Messaging framework — tested language mapped to persona and buying stage
- Content/contact strategy — who to reach, how to reach them, and what to say
- GEO/AEO snapshot — how AI search sees your product category and where you're missing
Phase 04
Sales & Marketing Engine Development
Now that the foundation is solid — clear ICP, sharp positioning, validated messaging — we build the systems that generate leads, users, and customers. The work in this phase evolves based on where you are in the product growth lifecycle.
Product-Solution Fit Learning mode
Focus on qualitative leads that help you understand the problem better, pressure-test your solution, and craft offers that confirm you're building the right thing. Validation over volume.
Product-Market Fit Acquisition mode
Identify the engines that bring in more leads and paying users, reduce churn, and start building evangelists. AI-powered outreach and content automation accelerate this stage without inflating headcount.
Scale Compounding mode
Expand your market, improve throughput, increase retention and referrals, and systemize what's working. AI agents handle the repeatable work so the team focuses on strategy and judgment calls.
Across all stages, we'll review 25+ engines of growth and prioritize tests to bring in the right-fit leads for your product. The core principle: build, measure, and learn in parallel — so you're never waiting on one bet to pay off before you run the next one.
Content & Contact Strategy
The foundation of the engine.
- Persona Development
- Ideal Account Identification
- Contact Acquisition Plan
- Messaging Areas of Focus
- AI-Assisted Content Creation & Curation
- Pillar Content & SEO / GEO
- Website — Prospect to Customer Design, Conversion Optimization
Marketing & Sales Engines
Awareness, acquisition, and revenue.
- Email & Lifecycle Marketing
- AI-Powered Outreach
- Paid Media (SEM, Social, Retargeting)
- Partnerships & Biz Dev
- Engineering as Marketing
- Social Media & Community
- Events, Tradeshows & Speaking
- Public Relations & AI Citations (GEO/AEO)
- User Onboarding & Trial Activation
- Account Expansion & Retention
Optimizing Outcomes
What the experiments are measuring.
- Increase Qualified Pipeline
- Improve Win Rate
- Increase Trial-to-Paid Conversion
- Increase Revenue
- Shorten Sales Cycle
- Reduce Churn
- Lower Cost of Acquisition (CAC)
- Increase Lifetime Value (LTV)
- Build AI Search Presence
What you'll get
- A fractional CMO to oversee or run your marketing efforts
- Rank-ordered channels — the most optimal engines for your product, market, and stage
- Validated learning from parallel experiments using a hypothesis testing system to identify lowest CAC and highest LTV channels
- Leads, users, customers
- An AI-powered marketing stack that gives your team a compounding speed advantage
Phase 05
Business Model Benchmarking
We regularly review progress, benchmarking against your minimum success criteria. This isn't a status report — it's a working session. We'll look at your customer segments, positioning, messaging, pricing, and channel performance to assess what's working, what's leaking, and what to adjust to improve your path to predictable revenue over the next quarter.
The next experiment is always stated as a clear, testable hypothesis: "An outbound sequence targeting mid-market fintech buyers will produce 20 qualified conversations in 60 days." That discipline keeps the learning real and the investments defensible.
What you'll get
- Updated key learnings from the quarter's experiments and campaigns
- Constraint identification — what's blocking the next level of growth
- Revised goals for the following quarter
- The next experiment, stated as a specific hypothesis with a success threshold