# Decisions: Marketing

Critical decision points that determine marketing effectiveness and efficiency.

---

## Decision 1: Channel Mix Selection

**Context:** Choosing where to invest marketing resources across channels.

**Options:**

| Channel Type | Pros | Cons | Choose When |
|--------------|------|------|-------------|
| **Paid (ads)** | Instant traffic, scalable | CAC compounds, ad fatigue | Unit economics proven, need speed |
| **Organic (SEO/content)** | Compounds, low CAC | Slow, competitive | Long-term, content capacity |
| **Social** | Brand building, engagement | Algorithm dependent, time-intensive | Visual product, engaged community |
| **Email** | Owned audience, high ROI | Requires list, competitive inbox | Existing audience, nurture-heavy |
| **Partnerships** | Leverage others' audience | Less control, revenue share | Complementary products exist |

**Framework:**
```
Channel selection criteria:

Where is your audience?
├── B2B decision makers → LinkedIn, email
├── B2C consumers → Meta, TikTok, Instagram
├── Developers → GitHub, Twitter, communities
├── Enterprise → Events, ABM, partnerships
└── SMB → Google, Facebook, content

Resource availability?
├── Budget heavy → Paid ads, events
├── Time heavy → Content, community
├── Expertise heavy → Technical content, partnerships
└── Limited → Focus on 1-2 channels only

Stage of company?
├── Pre-PMF → Free channels, learning
├── Early traction → Amplify what works
├── Growth → Scale winners, test new
└── Scale → Full funnel, brand + performance

CHANNEL ALLOCATION:
70%: Proven performers
20%: Promising experiments
10%: Moonshots

CHANNEL COMMITMENT:
Minimum 6 months per channel
Consistent investment
Clear success criteria
Kill or scale decision point
```

**Default Recommendation:** Start with one paid channel (Google or Meta) + one organic channel (SEO or social) + email. Master before adding more.

---

## Decision 2: Brand vs. Performance Marketing

**Context:** Balancing long-term brand building with short-term performance.

**Options:**

| Approach | Pros | Cons | Choose When |
|----------|------|------|-------------|
| **Performance-focused** | Measurable, short feedback loop | No brand equity, CAC creep | Need immediate ROI, testing |
| **Brand-focused** | Long-term equity, premium pricing | Hard to measure, slow | Established, premium positioning |
| **Balanced** | Best of both | Requires more budget | Growth stage, sufficient resources |

**Framework:**
```
Brand vs. Performance balance:

Company stage?
├── Seed/Pre-product → 100% learning, minimal spend
├── Early stage → 80% performance / 20% brand
├── Growth → 60% performance / 40% brand
├── Scale → 50% performance / 50% brand
└── Mature → 40% performance / 60% brand

Category?
├── Commoditized → More brand (differentiation)
├── New category → More brand (education)
├── Technical → More performance (features matter)
└── Emotional → More brand (connection matters)

BRAND MARKETING:
- Awareness campaigns
- Content marketing
- Sponsorships
- PR and thought leadership
- Community building

PERFORMANCE MARKETING:
- Paid acquisition
- Conversion optimization
- Retargeting
- Email sequences
- Landing pages

MEASUREMENT:
Brand: Awareness surveys, share of voice, brand search
Performance: CAC, ROAS, conversion rates

INTEGRATION:
Brand campaigns → Performance retargeting
Performance data → Brand creative decisions
```

**Default Recommendation:** Early stage = 80% performance. Increase brand investment as unit economics stabilize and CAC rises on performance channels.

---

## Decision 3: In-House vs. Agency

**Context:** Deciding whether to build internal team or hire agencies.

**Options:**

| Approach | Pros | Cons | Choose When |
|----------|------|------|-------------|
| **In-house** | Control, institutional knowledge | Fixed costs, hiring risk | Core competency, long-term |
| **Agency** | Expertise, flexibility | Less control, learning leaks | Specialty skills, variable needs |
| **Hybrid** | Balance control and expertise | Coordination overhead | Mature marketing function |

**Framework:**
```
In-house vs. agency decision:

Frequency of need?
├── Daily operations → In-house
├── Campaign-based → Agency
├── Specialized projects → Agency
└── Core competency → In-house

Expertise required?
├── General marketing → In-house possible
├── Specialized (SEO, PPC) → Agency or specialist hire
├── Creative (video, design) → Hybrid common
└── Strategic → In-house leadership

Budget structure?
├── Fixed budget → In-house (predictable)
├── Variable budget → Agency (flexible)
├── Project-based → Agency or contractor
└── Growth mode → Hybrid

GOOD AGENCY USE CASES:
- Paid media management
- PR and communications
- Video production
- Seasonal campaigns
- Specialized SEO

GOOD IN-HOUSE USE CASES:
- Marketing strategy
- Content creation
- Email marketing
- Brand voice
- Customer communication

HYBRID MODEL:
In-house: Strategy, core content, management
Agency: Execution, specialized skills

AGENCY MANAGEMENT:
- Clear briefs
- Regular check-ins
- Performance metrics
- Knowledge transfer
- Annual review
```

**Default Recommendation:** Start with generalist in-house marketer + specialist agencies. Build in-house expertise in areas that matter most.

---

## Decision 4: Marketing Technology Stack

**Context:** Choosing tools for marketing execution and measurement.

**Options:**

| Approach | Pros | Cons | Choose When |
|----------|------|------|-------------|
| **All-in-one (HubSpot)** | Integrated, easier | Less flexibility, cost | Simplicity priority, growing team |
| **Best-of-breed** | Best tools for each job | Integration work, complexity | Specific needs, technical team |
| **Minimal** | Low cost, simplicity | Limited capability | Early stage, budget constraints |

**Framework:**
```
Martech stack decision:

Stage?
├── Pre-revenue → Minimal (free tools)
├── Early revenue → Basic stack
├── Growth → Full stack
└── Scale → Integrated enterprise

Budget?
├── <$500/mo → Free/cheap tools
├── $500-2000/mo → Basic SaaS stack
├── $2000-10000/mo → Full marketing stack
└── >$10000/mo → Enterprise platforms

MINIMAL STACK:
- Analytics: Google Analytics (free)
- Email: Mailchimp (free tier)
- Social: Buffer (free tier)
- Landing pages: Carrd ($9/yr)

BASIC STACK:
- Analytics: GA + Mixpanel/Amplitude
- Email: Mailchimp/ConvertKit
- CRM: HubSpot free
- SEO: Ahrefs/SEMrush
- Social: Buffer/Hootsuite

FULL STACK:
- All-in-one: HubSpot/Marketo
- Or: Specialized tools integrated
- CDP: Segment
- Attribution: Branch/Adjust
- Data: Looker/Metabase

DECISION CRITERIA:
1. What are must-have features?
2. What integrations are needed?
3. Who will manage it?
4. What's total cost of ownership?
5. Can we migrate away if needed?
```

**Default Recommendation:** Start minimal, add tools when pain is clear. HubSpot free CRM + Mailchimp + GA covers most early needs. Avoid overbuilding.

---

## Decision 5: Content Strategy Approach

**Context:** Deciding the type and focus of content marketing.

**Options:**

| Approach | Pros | Cons | Choose When |
|----------|------|------|-------------|
| **SEO-driven** | Compounds, measurable | Slow, competitive | Long-term, search-heavy category |
| **Thought leadership** | Brand building, differentiation | Hard to measure | New category, executive brand |
| **Product-led** | Direct conversion, updates | Limited reach | Strong product, existing audience |
| **Community-driven** | Engagement, advocacy | Time-intensive | Strong community, niche audience |

**Framework:**
```
Content strategy selection:

How does your audience find solutions?
├── Search (Google) → SEO-driven
├── Social/network → Thought leadership
├── Recommendations → Community + product
├── Events/conferences → Thought leadership
└── Direct sales → Product-led + ABM content

What resources do you have?
├── Writers → SEO/blog content
├── Executives → Thought leadership
├── Product team → Product content
├── Community → User-generated

Timeframe for results?
├── 3-6 months → Product-led, email
├── 6-12 months → Thought leadership
├── 12+ months → SEO
└── Ongoing → Community

CONTENT TYPES BY APPROACH:

SEO-driven:
- Long-form blog posts
- Comprehensive guides
- Comparison articles
- Answer articles

Thought leadership:
- Opinion pieces
- Research and data
- Industry trends
- Executive social posts

Product-led:
- Feature announcements
- Use case tutorials
- Customer stories
- Changelog

Community-driven:
- User spotlights
- Q&A content
- Community roundups
- Co-created content
```

**Default Recommendation:** SEO-driven for most B2B SaaS (long-term traffic). Add thought leadership for differentiation. Product-led for existing audience activation.

---

## Decision 6: Pricing Communication

**Context:** How prominently to display pricing and positioning.

**Options:**

| Approach | Pros | Cons | Choose When |
|----------|------|------|-------------|
| **Transparent pricing** | Qualifies leads, builds trust | Competitors see, less flexibility | Self-serve, SMB, commoditized |
| **Hidden pricing** | More control, sales conversations | Friction, can feel shady | Enterprise, custom solutions |
| **Hybrid** | Flexibility, qualifying | Complexity, mixed signals | Multiple segments |

**Framework:**
```
Pricing transparency decision:

Buyer type?
├── Self-serve → Transparent (required)
├── SMB/Mid → Transparent (expected)
├── Enterprise → Hidden or "Contact us"
└── Mixed → Hybrid (show some, hide enterprise)

Purchase process?
├── Credit card → Transparent pricing
├── Procurement → Hidden acceptable
├── Complex negotiation → Hidden
└── Hybrid → Show base, "contact for volume"

Competitive landscape?
├── Commoditized → Transparent (compete on value)
├── Differentiated → Either works
├── Premium → Can hide (sell value first)

TRANSPARENT PRICING BENEFITS:
- 24/7 selling
- Qualifies leads (budget fit)
- Builds trust
- Reduces sales burden
- SEO for "[product] pricing"

HIDDEN PRICING BENEFITS:
- Flexibility in negotiation
- Competitor can't undercut
- Force conversation
- Value selling opportunity

HYBRID APPROACH:
Self-serve tiers: Show pricing
Enterprise tier: "Contact us"

OR:

Starting at $X/mo: Gives anchor
Custom pricing: "Let's talk"
```

**Default Recommendation:** Transparent for self-serve and SMB. Hybrid for mixed audiences. Only hide if sales-led with complex pricing.

---

## Decision 7: Campaign vs. Always-On

**Context:** Balancing big campaign moments with consistent presence.

**Options:**

| Approach | Pros | Cons | Choose When |
|----------|------|------|-------------|
| **Campaign-heavy** | Big moments, attention spikes | Inconsistent, tiring | Launches, seasonal products |
| **Always-on** | Compounds, consistent | No peaks, less exciting | Subscription, ongoing demand |
| **Balanced** | Both benefits | More planning required | Most businesses |

**Framework:**
```
Campaign vs. always-on balance:

Business model?
├── Subscription → Always-on primary
├── Transactional → Campaign moments matter
├── Enterprise deals → Campaign (events, launches)
└── Consumer → Seasonal campaigns + always-on

Category behavior?
├── Always buying → Always-on
├── Seasonal (holidays) → Campaign around seasons
├── Event-driven → Campaign around events
└── Mixed → Balanced

ALWAYS-ON ACTIVITIES:
- SEO and content
- Email nurture
- Social presence
- Paid retargeting
- Community engagement

CAMPAIGN ACTIVITIES:
- Product launches
- Seasonal promotions
- Events and conferences
- Partner announcements
- Company milestones

BALANCED ALLOCATION:
Always-on: 60-70% of effort
Campaigns: 30-40% of effort

CAMPAIGN CADENCE:
Major campaigns: 2-4 per year
Minor campaigns: Monthly features
Micro-moments: Weekly content

INTEGRATION:
Campaigns create attention
Always-on captures and nurtures
```

**Default Recommendation:** 70% always-on foundation + 30% campaign moments. Build consistent engine, amplify with campaigns.

---

## Decision 8: Localization Strategy

**Context:** Deciding how to approach international markets.

**Options:**

| Approach | Pros | Cons | Choose When |
|----------|------|------|-------------|
| **English only** | Focused, efficient | Limited market | Global English speakers, early stage |
| **Translation** | Wider reach | Moderate investment | Growing, clear international demand |
| **Localization** | True market fit | Expensive, complex | Serious international expansion |
| **Multi-domestic** | Local relevance | Very expensive | Dominant, different markets |

**Framework:**
```
Localization decision:

International demand signals?
├── Strong organic traffic → Consider translation
├── International customers → Listen to needs
├── Competitor presence → Evaluate opportunity
└── No signals → Stay English first

Market priority?
├── English-speaking (UK, AU) → Easy expansion
├── European (DE, FR) → Translation + local
├── Asia (JP, KR) → Full localization
└── LATAM (ES, PT-BR) → Translation + adaptation

LEVELS OF LOCALIZATION:

Level 1: English only
- US and global English speakers
- Common for early stage

Level 2: Translation
- Website in multiple languages
- Same content, translated
- Basic keyword localization

Level 3: Localization
- Adapted content for market
- Local examples, currency
- Local SEO strategy

Level 4: Multi-domestic
- Local teams
- Local content creation
- Local partnerships
- Full local presence

LOCALIZATION CHECKLIST:
□ Currency display
□ Date formats
□ Language of support
□ Local payment methods
□ Local case studies
□ Local SEO
□ Legal compliance (GDPR, etc.)
```

**Default Recommendation:** Stay English-only until international demand is clear. Translate when you have 10%+ traffic from a language. Full localization for major expansion.

---

## Decision 9: Lead Qualification Approach

**Context:** Defining when leads are ready for sales.

**Options:**

| Approach | Pros | Cons | Choose When |
|----------|------|------|-------------|
| **Light qualification** | More leads to sales | Lower quality, sales burden | Small sales team, abundant capacity |
| **Heavy qualification** | Higher quality, focused sales | May miss opportunities | Large sales team, quality priority |
| **Product-qualified** | Behavior-based, accurate | Requires usage data | Product-led growth |
| **Intent-based** | High timing relevance | Requires intent data | Complex B2B, long cycles |

**Framework:**
```
Lead qualification strategy:

Sales capacity?
├── Limited → Heavy qualification (protect time)
├── Abundant → Lighter qualification (more at bats)
└── Growing → Iterate and tighten

Product-led signals available?
├── Yes (usage data) → PQL model
├── Limited → MQL + behavior
└── No → Traditional demographic + action

LEAD TYPES:

MQL (Marketing Qualified):
- Meets fit criteria
- Engaged with content
- Downloaded assets
- Visited pricing

SQL (Sales Qualified):
- MQL + sales conversation
- Confirmed need/budget/timing
- Ready for proposal

PQL (Product Qualified):
- Active user
- Hitting usage limits
- Using key features
- Upgrade signals

QUALIFICATION CRITERIA:

Fit scoring:
- Company size: +10
- Industry match: +15
- Role match: +20

Engagement scoring:
- Page views: +1 each
- Content download: +10
- Pricing page: +20
- Demo request: +50

PQL signals:
- Free tier limit hit
- Multiple users invited
- Integration connected
- X actions in Y days
```

**Default Recommendation:** MQL for sales-led, PQL for product-led. Define clear handoff criteria between marketing and sales. Iterate based on conversion rates.

---

## Decision 10: Attribution Model

**Context:** Choosing how to credit marketing touchpoints for conversions.

**Options:**

| Model | Pros | Cons | Choose When |
|-------|------|------|-------------|
| **Last-click** | Simple, clear | Ignores assist | Quick decision, simple funnels |
| **First-click** | Values awareness | Ignores nurture | Awareness priority |
| **Linear** | Fair credit | Oversimplifies | Equal weight valid |
| **Position-based** | Balanced | Still simplified | Long journeys, both ends matter |
| **Data-driven** | Most accurate | Complex, needs data | Mature, ML capability |

**Framework:**
```
Attribution model selection:

Funnel complexity?
├── Simple (few touches) → Last-click sufficient
├── Medium (5-10 touches) → Position-based
├── Complex (many touches) → Data-driven
└── Very long cycle → Custom modeling

ATTRIBUTION MODELS:

Last-click:
100% credit to last touch
Easy but misleading

First-click:
100% credit to first touch
Values awareness

Linear:
Equal credit to all touches
Fair but flat

Position-based (U-shaped):
40% first, 40% last, 20% middle
Values intro and close

Time-decay:
More credit to recent touches
Values recency

Data-driven:
ML determines credit
Most accurate, needs data

PRACTICAL REALITY:
1. Perfect attribution is impossible
2. All models are wrong, some are useful
3. Directional insight is the goal
4. Supplement with qualitative

IMPLEMENTATION:
1. Start with last-click (baseline)
2. Add first-click (compare)
3. Move to position-based
4. Graduate to data-driven if volume allows

ALSO ASK:
Post-purchase survey: "How did you hear about us?"
Often more accurate than tracking
```

**Default Recommendation:** Start with last-click for simplicity. Add first-click to understand awareness. Move to position-based or data-driven as you scale. Always include "how did you hear about us" survey.
