Marketing Strategy Framework for Startups

Purpose

This recipe produces a stage-appropriate marketing strategy document with prioritized channel selections, budget allocations, a 90-day experiment plan, and measurable success criteria — calibrated to whether the startup is pre-PMF (learning mode) or post-PMF (scaling mode). The output prevents the two most common mistakes: spreading budget across too many channels before PMF, and under-investing in proven channels after PMF. [src1]

Prerequisites

• ICP definition — documented ideal customer profile — ICP Definition Framework
• Product positioning — value proposition and competitive differentiation — Startup Positioning Framework
• Current metrics baseline — MRR, churn rate, NPS, traffic sources, conversion rates
• Google Analytics 4 — installed on product/website at analytics.google.com (free)
• Budget clarity — monthly marketing budget approved or estimated based on runway

Constraints

• Pre-PMF: 80%+ of marketing effort must focus on learning, not scaling. [src4] [src5]
• Seed stage: budget $5K-25K/mo maximum before channel-market fit validation. [src2]
• Maximum 2 primary channels for first 90 days — spreading across 5+ channels guarantees none reach statistical significance. [src1]
• Series A: budget $40K-170K/mo. Only scale channels with proven CAC:LTV ratio > 3:1. [src2]
• Do not hire VP of Marketing before PMF — founders must own GTM learning. [src5]

Tool Selection Decision

Which path?
├── Pre-PMF (no retention metrics, still searching for fit)
│   ├── B2B SaaS → PATH A: Founder-led outbound + content
│   ├── B2C SaaS → PATH B: Community + product-led growth
│   ├── Marketplace → PATH C: Supply-side acquisition + demand tests
│   └── E-commerce → PATH D: Paid social + influencer tests
├── Early PMF (some retention, 40%+ would be disappointed)
│   ├── B2B → PATH E: Content + outbound scaling
│   └── B2C → PATH F: Paid + organic scaling
└── Strong PMF (retention proven, ready to scale)
    ├── B2B → PATH G: Multi-channel (content + paid + partnerships)
    └── B2C → PATH H: Performance marketing + brand

Execution Flow

Step 1: Audit Current State and Define PMF Stage

Duration: 1-2 hours · Tool: Analytics dashboard + metrics spreadsheet

Assess PMF stage using the Sean Ellis test (>40% "very disappointed"), retention curve analysis, NPS, organic referrals, and revenue growth without paid acquisition. Score 0-1 = Pre-PMF, 2-3 = Early PMF, 4-5 = Strong PMF.

Verify: PMF stage classified with documented metrics baseline. · If failed: Classify as Pre-PMF and focus on instrumenting analytics first.

Step 2: Select Primary Channels (Maximum 2)

Duration: 1 hour · Tool: Channel scoring matrix

Score each potential channel against four criteria (Reachability, Trust Transfer, Cost, Speed) on a 1-5 scale. Select top 2. Apply business-model rules: B2B SaaS high-ACV = outbound + events; B2B SaaS low-ACV = content/SEO + PLG; B2C = paid social + organic/community. [src1]

Verify: Exactly 2 channels selected with rationale tied to ICP behavior. · If failed: Run 2-week micro-tests ($500/channel) to generate decision data.

Step 3: Allocate Budget by Stage

Duration: 30 minutes · Tool: Spreadsheet

Pre-PMF: 40% channel experiments, 25% content, 15% tools, 20% research. Post-PMF: 50% proven channels, 15% new experiments, 20% content/brand, 10% tools, 5% team. [src2] [src6]

Verify: Budget matches approved spend. No single channel > 50% pre-PMF. · If failed: Reduce to 1 channel + content.

Step 4: Design 90-Day Experiment Plan

Duration: 1 hour · Tool: Notion, Google Sheets, or Airtable

Create 4-6 structured experiments per 90-day cycle. Each experiment needs: hypothesis, budget, success metric, minimum viable signal, timeline (min 2 weeks), and owner. Stagger starts by 2 weeks. [src7]

Verify: Each experiment has measurable success criteria and kill thresholds. · If failed: Narrow channel tactics until outcomes are measurable.

Step 5: Build Measurement and Attribution

Duration: 30-60 minutes · Tool: GA4 + CRM + UTM conventions

Establish UTM conventions (source, medium, campaign, content). Configure GA4 goals for key actions. Track per-channel funnel: impressions → visits → signups → activated users → paying customers. [src3]

Verify: UTM conventions documented. GA4 conversions configured. · If failed: Start with UTM tracking on all links — imperfect attribution is better than none.

Step 6: Execute, Review, and Iterate (90-Day Cycles)

Duration: Ongoing (weekly 30-min + monthly 2-hr reviews)

Weekly: check experiment metrics vs targets, flag underperformers, identify winners. Monthly: calculate CAC per channel, compute LTV:CAC ratio, kill failing experiments, promote winners. 90-day: identify top 2 channels, reallocate 70% of budget, design next cycle.

Verify: 4+ experiments completed per cycle with clear winners identified. · If failed: Experiments were too short or too small — increase duration and budget per experiment.

Output Schema

{
  "output_type": "marketing_strategy_document",
  "format": "structured markdown + experiment backlog",
  "columns": [
    {"name": "pmf_stage", "type": "string", "description": "Pre-PMF, Early PMF, or Strong PMF", "required": true},
    {"name": "primary_channel", "type": "string", "description": "First priority channel", "required": true},
    {"name": "secondary_channel", "type": "string", "description": "Second priority channel", "required": true},
    {"name": "monthly_budget", "type": "number", "description": "Total monthly marketing budget", "required": true},
    {"name": "budget_allocation", "type": "object", "description": "Budget breakdown by category", "required": true},
    {"name": "experiment_count", "type": "number", "description": "Experiments in 90-day plan", "required": true},
    {"name": "target_cac", "type": "number", "description": "Target customer acquisition cost", "required": false},
    {"name": "review_cadence", "type": "string", "description": "Review schedule", "required": true}
  ],
  "expected_row_count": "1",
  "sort_order": "N/A",
  "deduplication_key": "pmf_stage"
}

Quality Benchmarks

If below minimum: Start with channel selection (Step 2) and experiment plan (Step 4). Running structured experiments with hypotheses produces learning even without formal measurement.

Error Handling

Cost Breakdown

Anti-Patterns

Wrong: Scaling paid ads before PMF

Spending $10K+/mo on ads before validating retention and conversion at sustainable rates. Result: high CAC, low LTV, rapid cash burn. [src4] [src5]

Correct: Use paid ads as learning tools pre-PMF

Pre-PMF paid ads serve one purpose: fast feedback. Spend $500-2K to test messaging and validate demand. Do not optimize for conversions until retention is proven.

Wrong: Copying a competitor's channel mix

Adopting well-funded competitor channels without their budget, brand, or domain authority. [src1]

Correct: Choose channels with asymmetric advantage

Select channels where the startup has a unique edge: founder network, domain expertise, niche community access, or willingness to do things that don't scale.

Wrong: Measuring by vanity metrics only

Reporting impressions and followers without connecting to pipeline or revenue. [src3]

Correct: Measure acquisition funnel from day one

Track visitors → signups → activated users → paying customers by channel. Even small numbers reveal funnel drop-offs and channel quality.

When This Matters

Use this recipe when the agent needs to build a complete marketing strategy for a startup, not execute a specific channel. This produces the strategic plan that downstream execution recipes (content marketing, SEO, paid acquisition) implement. Requires ICP definition and positioning as inputs.