Channel Selection & GTM Planning — Decision Frameworks & Quarterly Planning¶

A comprehensive, operator-grade reference for B2B SaaS channel strategy and go-to-market planning. Covers the RACE framework adapted for SaaS, a conditional logic channel decision tree, GTM archetype selection, a full quarterly planning cycle template, stage-based budget allocation, 30/60/90-day channel playbooks, and a systematic testing cadence with kill/depth criteria.

1. RACE Framework for SaaS¶

RACE — Reach → Act → Convert → Engage — was developed by Pratap Tony (RACE 2012, updated through 2024) as a data-driven marketing planning framework. It extends the linear AIDA model into a closed-loop system where the final stage (Engage) feeds back into the first (Reach), making the funnel circular and measurable at every point.

The SaaS adaptation of RACE is distinct from traditional marketing funnels in three important ways:

1. The flywheel closes itself. In e-commerce or lead-gen funnels, Engage is the end state. In SaaS, Engage is the beginning of the next acquisition cycle — happy customers become promoters, referral sources, and expansion revenue.
2. Time-to-value (TTV) is the primary conversion metric. Traditional conversion is a binary event (lead → opportunity → close). SaaS conversion is a process: trial → activation → habit formation → expansion. The "Convert" stage in SaaS is not one moment but a continuum.
3. The Engage stage carries the highest leverage. In SaaS, NRR (Net Revenue Retention) determines whether growth is compounding or leaking. A 110% NRR company grows 10% per year without adding a single new customer. This makes Engage the most strategically important stage, unlike traditional funnels where Reach dominates spend.

Stage-by-Stage SaaS Tactics¶

REACH — Building Top-of-Funnel Awareness¶

Goal: Put your brand and category in front of the right people before they're actively searching.

RACE Reach metric: Addressable Market Reach % = (Monthly unique ICP visitors) / (Total addressable market universe) × 100
Target: >15% of addressable market reached monthly before entering active consideration.

ACT — Driving Consideration and Intent Signal¶

Goal: Convert anonymous reach into identifiable intent. Turn passive readers into active researchers.

RACE Act metric: Engagement rate = (# of ICP visitors who complete 2+ engagement actions per month) / (# of total ICP visitors) × 100
Target: >8% engagement rate for SMB; >12% for mid-market (buyers engage more deeply before committing).

CONVERT — Turning Interest into Paying Customers¶

Goal: Reduce friction between evaluation and purchase. Close the gap between marketing-attributed intent and signed contract.

RACE Convert metric: Trial-to-paid conversion rate = (Converted trials per quarter) / (Total active trials per quarter) × 100
Benchmarks: SMB 5–15%; Mid-market 15–25%; Enterprise 25–40%.

ENGAGE — Maximizing Customer Value and Advocacy¶

Goal: Get customers to value faster, retain them longer, and turn them into the engine of the next Reach cycle.

RACE Engage metric: NRR = (Starting ARR + Expansion − Churn − Contraction) / Starting ARR × 100
Benchmarks: World-class >130%; Good 110–120%; Healthy floor 100%.

Stage-Appropriate Channel Mix by Growth Stage¶

Sources: RACE Framework, Pratap Tony (Smart Insights, 2024); HubSpot Flywheel Momentum Framework (2018); OpenView Partners, 2023 SaaS Benchmark.

2. Channel Selection Decision Tree¶

Channel selection is not a one-time decision — it follows a conditional logic tree that maps business inputs to channel priorities. Run through the tree in order; each branch point is a hard constraint, not a preference.

Decision Inputs¶

Before running the tree, establish five input values:

Decision Tree¶

START: What is your ACV?

ACV < $5,000
├── Sales cycle < 30 days?
│   ├── YES → PRIMARY: PLG / Self-serve
│   │           SECONDARY: Content SEO (long-term compounding)
│   │           KILL: Outbound sales, ABM
│   │           Rationale: Sales headcount cannot scale economically below this ACV
│   └── NO (cycle 30–90 days) → PRIMARY: PLG + Content + Paid retargeting
│                                SECONDARY: Outbound (SDR for demos only)
│
ACV $5,000–$25,000
├── Product complexity < 30 days to value?
│   ├── YES → PRIMARY: PLG-primary + Sales-assisted for upsell
│   │           SECONDARY: SEO, LinkedIn content, retargeting
│   │           Add second motion WHEN: >20% of inbound trials come from ACV >$15K accounts
│   └── NO (complex, 30–90 days) → PRIMARY: Content + Inbound MQL + Sales-assisted
│                                SECONDARY: ABM-lite (Tier 3 programmatic) for mid-market
│                                Add second motion WHEN: SQL-to-close rate <25%
│
ACV $25,000–$100,000
├── ICP density in target market > 15%?
│   ├── YES (high-density: SMB/mid-market horizontal, dense vertical) → PRIMARY: SLG + Inbound + ABM-lite
│   │           SECONDARY: Partner/referral channel; events
│   │           Add second motion WHEN: CAC payback >18 months (add outbound capacity)
│   └── NO (low-density: sparse enterprise, niche vertical) → PRIMARY: ABM (Tier 1/2) + SLG
│            SECONDARY: Events + direct content + PR
│            Add second motion WHEN: Average deal size justifies 6+ month sales cycle investment
│
ACV > $100,000
├── Sales cycle < 6 months? → PRIMARY: SLG + ABM Tier 1
│                            SECONDARY: Events; executive direct mail; category-defining content
│                            Add second motion WHEN: NRR <110% (add CS-led expansion focus)
└── Sales cycle 6–18 months → PRIMARY: ABM Tier 1 (1:1) + Enterprise sales
                             SECONDARY: Ecosystem/partners (GSI); executive advisory relationships
                             Rationale: Deal economics justify 6–18 months of personalized ABM investment

Post-Tree Adjustments¶

Run these overrides after the base tree:

Override 1 — Team Size Constraint
If you have <2 marketing FTEs:
- Kill everything except: content/SEO (if category is SEO-friendly), PLG (if product supports it), or direct founder sales
- Defer: paid ads, ABM, outbound, community events

Override 2 — Budget Constraint
If quarterly budget <$25K:
- Prioritize: SEO + content (compounding), PLG mechanics (if applicable), founder personal network
- Kill: paid media (insufficient data to optimize), ABM tools, events with expensive sponsorships

Override 3 — Product Complexity Override
If product requires >90 days to value AND ACV >$25K:
- Shift to "land-and-expand" model: start with a lower-touch entry point (team tier, pilot) to get in, then expand
- Channel priority becomes: events (to build trust), executive relationships (to support land), partner introductions (to reduce risk)

Channel Priority Matrix¶

After running the tree, rank channels using this effort/impact matrix:

3. GTM Archetype Selection¶

The GTM archetype defines your primary growth engine. Choose before allocating budget or headcount — it's the load-bearing decision.

The Five Archetypes¶

Sales-Led Growth (SLG)¶

The AE is the primary growth driver. Marketing generates MQLs; sales converts them.

Decision criteria — choose SLG when:
- ACV > $25K (sales headcount economics work)
- Sales cycle > 60 days (complex, multi-stakeholder evaluation)
- Product requires human explanation or custom configuration
- ICP is concentrated (sparse high-value accounts that need hunting)
- Regulated industry (compliance needs sales explanation)

When to add a second motion: When CAC payback exceeds 18 months, or when sales cycle limits growth rate below target despite strong win rates.

Product-Led Growth (PLG)¶

The product drives acquisition and conversion. Users self-serve through the funnel.

Decision criteria — choose PLG when:
- ACV < $25K (sales cannot scale economically)
- Product delivers value within first session (no training required)
- Viral/collaborative mechanics exist (team invites, shared workspaces, network effects)
- Large ICP market (many potential users to self-serve through)
- Purchase decision is bottom-up (individual contributor → team → org)

When to add a second motion: When enterprise accounts are signing up via PLG but want a sales conversation to close; when ACV is rising above $15K.

Community-Led Growth (CLG)¶

Customers become advocates who recruit other customers. Growth compounds through community identity and peer recommendation.

Decision criteria — choose CLG when:
- Developer ecosystem or platform (marketplace, API, plugins)
- Strong network effects (product value increases with more users)
- Customers share a strong identity or mission
- NPS > 50 and customers talk to peers in the category
- Category is young enough that community = category definition

When to add a second motion: When community alone cannot fill the pipeline; typically add SLG for enterprise tier or PLG for developer/self-serve tier.

Outbound-Led Growth¶

Targeted, personalized outreach to a defined account list. Used for enterprise and high-touch motions.

Decision criteria — choose Outbound when:
- ICP is so concentrated that cold outbound is the only scalable reach strategy
- Product has a compelling differentiator that cold contact can credibly communicate
- ACV justifies the cost of SDR/AE time ($50K+)
- No organic channel presence yet (no SEO, no brand)

When to add a second motion: When outbound CAC is rising (market saturation); when brand presence improves enough that outbound now hits warmer prospects.

Hybrid Motion¶

Most growth-stage companies operate with two simultaneous motions. The canonical combinations:

Decision rule for adding a second motion — the 20% threshold:
Add a second motion when >20% of revenue is being lost to a cohort that a different motion could capture. Example: if 20%+ of your trials come from enterprise accounts (ACV >$50K) that never convert via self-serve, add an SLG motion.

GTM Archetype Transition Triggers¶

Sources: Reforge, GTM Archetypes (2022); Bessemer Venture Partners, PLG Market Map (2023); OpenView Partners, 2023 SaaS Benchmark; Winning by Design, The SPICED Framework (2021).

4. Quarterly GTM Planning Template¶

A real quarterly GTM planning cycle runs 12 weeks. It follows a sequential decision process: data → hypothesis → prioritization → allocation → execution → retrospective. Skipping steps produces bad allocation decisions.

Timeline Overview¶

Phase 1: Data Review (Weeks 1–2)¶

Objective: Understand what happened last quarter and why. Separate noise from signal.

Activities:

1. Pull the full marketing dashboard — pipeline created, revenue closed, CAC, CAC payback, LTV:CAC, NRR, MQL volume, SQL volume, demo requests, trial starts, trial-to-paid conversion, inbound vs. outbound mix.

2. Close the attribution gaps — Cross-check CRM revenue against finance's recognized revenue. If they differ by >5%, investigate before planning.

3. Identify the top 3 wins and top 3 losses
   - Wins: What channels/activities drove them? Were they attributed correctly?
   - Losses: Lost to competitors? Budget? Timing? Product fit? No decision?

4. Calculate channel efficiency scores (see Section 7 for formula)

5. Flag anomalies — Any channel that performed 2x or 0.5x vs. the prior two quarters? Need explanation before planning.

Output: Q1 Performance Summary — one-page internal memo with key metrics, notable outliers, and 3–5 data-driven observations.

Phase 2: Channel Audit (Weeks 2–3)¶

Objective: Score every active channel against efficiency thresholds. Identify which channels deserve more budget, which need optimization, and which to kill.

Channel Audit Scorecard:

Efficiency scoring rubric:
- 5 = ROI >150% or strategic brand-building with clear pipeline influence
- 4 = ROI 80–150% or strong influence metric
- 3 = ROI 30–80%; borderline
- 2 = ROI 0–30%; needs optimization or kill
- 1 = Negative ROI and no strategic justification

Decision thresholds:
- Score 5 → Double budget (if team capacity allows)
- Score 4 → Increase budget 25–50%
- Score 3 → Hold; run one test to improve
- Score 2 → Cut budget 50%; run focused test to improve or kill
- Score 1 → Kill; reallocate budget to Score 5 channels

Phase 3: Hypothesis (Week 3)¶

Objective: Make the quarter's bets explicit. Every initiative should be a testable hypothesis.

Hypothesis template:

"We believe [doing X with channel Y] will [produce outcome Z] because [evidence from Q1 data or industry benchmark]. We will know it worked if [measurable signal]."

Examples:

"We believe investing $X more in LinkedIn retargeting will produce $3X pipeline because our retargeting engagement score (e.g., 45+) correlates with 3x higher demo conversion vs. cold LinkedIn outreach (GTMnow, Outreach case study)."

"We believe adding a PQL-triggered sales alert will reduce our trial-to-paid cycle by 20% because our CS data shows trials that get an AE call within 3 days of hitting the activation event convert at 2x the rate of non-contacted trials."

"We believe SEO will deliver 2x pipeline in Q3 vs. Q2 because we are publishing 8 bottom-of-funnel comparison pages targeting [keyword cluster] with estimated monthly search volume of [X]."

Rules:
- Maximum 3–5 hypotheses for the quarter (focus is survival)
- Each hypothesis must have a measurable success criterion defined before execution starts
- If you can't define the success criterion, it's not a hypothesis — it's a hope

Phase 4: Prioritization (Week 4)¶

Objective: Rank hypotheses and ongoing activities by expected impact vs. resource cost. Kill things that don't make the cut.

Prioritization matrix:

Decision rules:
- Priority Score >1.0 → Do in Q2
- Priority Score 0.5–1.0 → Hold; revisit if capacity allows
- Priority Score <0.5 → Kill; reallocate resources

Alignment check: Are the top 3 initiatives aligned with the GTM archetype decision (Section 3)? If a high-scoring initiative contradicts the archetype (e.g., investing heavily in outbound when PLG is the right archetype), resolve the conflict before proceeding.

Phase 5: Budget Allocation (Week 5)¶

Objective: Translate prioritization into actual budget commitments.

Budget allocation process:

1. Start with stage-appropriate baseline (see Section 5 for benchmarks)
2. Adjust based on Q1 channel audit — shift budget from low-efficiency to high-efficiency channels
3. Reserve 15–20% for testing — do not allocate all budget to known channels; reserve for hypothesis testing
4. Cap new channel experiments at $XK — define the maximum you will spend on any single untested channel before requiring a proof-of-concept

Budget allocation template:

Phase 6: QGTM Plan Lock (Week 6)¶

Deliverable: QGTM Plan document (internal, 3–5 pages)

Must include:
- Q1 retrospective summary (1 page max)
- Q2 hypotheses (3–5, with success criteria)
- Budget allocation table
- Channel priorities ranked
- OKRs for the quarter (objectives + key results)
- Team briefs (who owns what)
- Weekly/bi-weekly check-in cadence

Lock criteria — do not proceed to execution without:
- [ ] CEO/Founder alignment on OKRs
- [ ] Sales leadership sign-off on SLG assumptions
- [ ] Finance alignment on CAC payback targets
- [ ] Board/ investor alignment if significant budget change vs. prior quarter

Phase 7: Execution (Weeks 7–11)¶

Operational cadence:

Hypothesis pulse check at Week 9:
At the halfway point of execution (end of Week 9), run a hypothesis review:
- For each hypothesis, assess: Are we seeing early signals of the expected outcome?
- If a hypothesis is clearly failing (no positive signal by Week 9), kill it and reallocate to the next priority
- If a hypothesis is clearly winning, consider accelerating investment

Phase 8: Retrospective (Week 12)¶

Objective: Score performance against hypotheses; document learnings; prepare Q3 planning inputs.

Retrospective format:

Q2 GTM Retrospective

HYPOTHESIS SCORECARD
H1: [Statement] → RESULT: [Confirmed / Partially Confirmed / Invalidated] → Evidence: [What we saw]
H2: [Statement] → RESULT: [Confirmed / Partially Confirmed / Invalidated] → Evidence: [What we saw]
H3: [Statement] → RESULT: [Confirmed / Partially Confirmed / Invalidated] → Evidence: [What we saw]

CHANNEL PERFORMANCE
- Revenue closed: $X vs. target $X (X% of target)
- CAC payback: X months vs. target X months
- NRR: X% vs. target X%
- Best performing channel: [Channel] — ROI X%, evidence: [what drove it]
- Worst performing channel: [Channel] — ROI X%, evidence: [why it underperformed]

KEY LEARNINGS (top 3)
1. [What we learned that changes Q3 planning]
2. [What we learned that changes Q3 planning]
3. [What we learned that changes Q3 planning]

Q3 PRIORITY INPUTS
[What goes into the Q3 planning process — budget constraints, team changes, market changes, product changes]

Source: Outreach GTM Evolution Framework (GTMnow, Mark Kosoglow); Lenny Rachitsky, Quarterly Planning Playbook (2024).

5. Budget Allocation by Stage¶

Budget allocation is a proxy for strategic intent. The allocation tells you what you actually believe, not what you say you believe.

Early-Stage (0–$1M ARR)¶

Context: Product-market fit not yet proven or recently proven. Every dollar must validate the growth hypothesis.

Inbound vs. outbound mix: ~70% inbound / 30% outbound (if SLG motion)
Headcount assumptions (1–2 marketing FTEs + 1 SDR):
- Founder or GM doing sales-heavy role
- 1 marketing generalist (content + paid + social)
- 1 SDR (if outbound motion exists)

What to avoid: Large event sponsorships; expensive ABM tooling; large paid media campaigns without data; hiring a full content team before validating content ROI.

Warning sign of misallocation: If >40% of budget is going to paid media in the first $500K ARR, you are buying growth you haven't earned and will not be able to sustain.

Growth-Stage ($1M–$10M ARR)¶

Context: PMF validated; now scaling the engine that works. Primary goal is efficient growth, not experiment.

Inbound vs. outbound mix: ~50% inbound / 50% outbound (at $5M+ ARR, leans toward 60/40 inbound if SEO is mature)
Headcount assumptions (4–8 marketing FTEs):
- 1 VP Marketing / Marketing Director
- 1–2 Content / SEO specialists
- 1 Paid media manager
- 1 SDR manager + 2–4 SDRs
- 1–2 AEs (if SLG)
- 1 Demand gen / analytics person

Scale-Stage ($10M–$50M ARR)¶

Context: Efficient growth at scale; multiple segments; NRR is a primary lever.

Inbound vs. outbound mix: ~55% inbound / 45% outbound (scale stage benefits from brand recognition driving inbound)
Headcount assumptions (10–20+ marketing FTEs):
- CMO + VP-level team
- Demand gen, content, ABM, events, customer marketing, community — each with dedicated leads
- Full SDR org (6–10+ SDRs)
- Multiple AE teams segmented by company size

Sources: OpenView Partners, 2023 SaaS Benchmark; Bessemer Venture Partners, SaaS Budget Allocation Guide (2023); SaaHero, B2B SaaS Marketing Spend Benchmarks (2024).

6. Channel-Specific Playbooks¶

Each major channel has a distinct 30/60/90-day activation sequence. These are the sequences that work for most B2B SaaS companies; adjust for your ACV and ICP.

SEO Playbook¶

Goal (30/60/90): Establish content infrastructure, publish foundational assets, begin ranking for bottom-of-funnel terms.

Day 1–30: Foundation
- [ ] Technical SEO audit (Screaming Frog or Semrush site audit); fix critical crawl errors
- [ ] Keyword research: map 3–5 topic clusters (each cluster = 1 pillar page + 3–5 supporting posts) targeting bottom-of-funnel and mid-funnel keywords
- [ ] Define content calendar: 2 posts/week minimum (1 long-form pillar/cluster post + 1 short-form tactical post)
- [ ] Set up GSC + GA4 + Semrush/ Ahrefs tracking; baseline organic sessions and keyword rankings
- [ ] Publish 4–8 foundational posts (your top 3 comparison pages, your best how-to guides)

Day 31–60: Publishing Cadence
- [ ] Maintain 2 posts/week publishing schedule
- [ ] First link-building outreach: 20–30 personalized outreach emails for backlinks to top 3 existing posts
- [ ] Publish first comparison/versus page targeting your primary competitor
- [ ] Set up organic traffic-to-MQL conversion tracking (UTM + CRM tracking)
- [ ] Analyze first 30-day data: which topics are driving qualified traffic? Double down.

Day 61–90: Optimization + Expansion
- [ ] Update and expand top 3 performing posts (add new data, improve depth, refresh stats)
- [ ] Publish 4–6 additional cluster posts around proven topic clusters
- [ ] Guest post or podcast: secure 1–2 external placements for backlinks
- [ ] Begin internal linking architecture audit — ensure all new posts link to pillar pages
- [ ] End-of-quarter review: organic sessions +X%? Keyword ranking improvements? Traffic-to-MQL conversion rate?

SEO KPIs: Organic sessions growth (target: 15–25% QoQ for early-stage); keyword ranking improvements for target terms; organic MQL volume.

Paid Acquisition Playbook¶

Goal (30/60/90): Prove paid channels can deliver ROI-positive pipeline within 90 days. Start narrow, expand based on data.

Day 1–30: Setup + Test
- [ ] Define campaign structure: branded (always-on), non-branded (use-case keywords), retargeting (website visitors), ABM (if applicable)
- [ ] Set up conversion tracking: thank-you page tags, CRM pipeline stage updates
- [ ] Launch branded search campaigns (cheapest CPC, highest conversion rate — always worth running)
- [ ] Launch retargeting campaigns (Google Display + LinkedIn) to website visitors last 30/60/90 days
- [ ] Launch 1–2 non-branded Google Search campaigns on bottom-of-funnel use-case keywords (tight match types)
- [ ] Set UTM structure for all campaigns (source/medium/campaign/content)
- [ ] Establish baseline CPCs and conversion rates

Day 31–60: Optimize + Expand
- [ ] Pause low-performing keywords (CPA >3x target CAC or ROAS <1.5x)
- [ ] Double down on top 3 performing keywords/ad sets
- [ ] Launch LinkedIn ABM campaigns if ACV >$25K (target account list + job title targeting)
- [ ] Begin A/B testing ad copy (headlines, CTAs, landing page variants)
- [ ] Optimize landing pages: test at least 2 variants per campaign
- [ ] Review attribution: are paid-influenced deals tracking correctly in CRM?

Day 61–90: Scale What Works
- [ ] Increase budget on campaigns with positive ROI (ROAS >2x for Google; ROAS >1.5x for LinkedIn)
- [ ] Expand keyword lists to mid-funnel terms if bottom-of-funnel is working
- [ ] Launch Meta retargeting (if applicable — works best for ACV <$10K with strong visual product)
- [ ] Set up automated bidding rules (target CPA / maximize conversions) once you have 30+ conversions per campaign
- [ ] Quarter-end review: Paid-influenced pipeline $X at CAC $Y vs. target $Z

Paid KPIs: ROAS by channel; CAC payback; paid-influenced pipeline; conversion rate by keyword/ad.

Outbound Playbook¶

Goal (30/60/90): Build outbound infrastructure, generate qualified meetings, prove outbound can produce ROI-positive pipeline.

Day 1–30: Infrastructure
- [ ] Define ICP and build target account list (100–300 accounts based on ICP criteria)
- [ ] Purchase data: LinkedIn Sales Navigator, Apollo.io, or Clearbit for contact data (email + phone)
- [ ] Write 3 email sequences: (1) intro cold email, (2) LinkedIn connection request, (3) break-up email
- [ ] Set up outreach tooling: Outreach.io, Salesloft, or Apollo sequences
- [ ] Train SDRs/AEs on discovery call framework; set up call coaching (Gong or chorus.ai)
- [ ] Set quota: SDR target = 50–80 contacts/day; 8–15 meetings booked/week per SDR
- [ ] Define qualification criteria: SQL definition agreed between Sales and Marketing

Day 31–60: Execution + Qualification Calibration
- [ ] Launch outbound sequences to Tier 1 target accounts
- [ ] Run first 2 weeks of outreach; analyze reply rates by subject line, send time, and copy variant
- [ ] Weekly calibration: Sales + Marketing review SQL quality; refine qualification criteria
- [ ] Measure: reply rate (>8% is good for cold email), meeting booking rate (>3% of contacts booked = healthy)
- [ ] Introduce ABM overlays for top 20–50 accounts (personalized content, direct mail, executive outreach)

Day 61–90: Optimization + Scaling
- [ ] Kill sequences with reply rates <5%; double down on highest-reply variants
- [ ] Analyze meeting-to-close rate for first outbound-attributed opportunities (establish baseline)
- [ ] If ACV >$25K and outbound is working: add AE capacity to handle inbound + outbound meetings
- [ ] Build first outbound-to-close ROI calculation: revenue closed from outbound pipeline / total outbound cost
- [ ] End-of-quarter: Is outbound ROI positive? If not within sight of positive by Month 4, re-evaluate the motion.

Outbound KPIs: Contact volume; reply rate; meeting booking rate; SQL rate; meeting-to-close rate; CAC payback.

Content Marketing Playbook¶

Goal (30/60/90): Establish thought leadership voice, build topical authority, begin generating organic pipeline-attributed content.

Day 1–30: Strategy + Production Setup
- [ ] Conduct content audit of existing assets; retire or update low-performing posts
- [ ] Define 3–5 content pillars aligned with your ICP's buying journey:
- Pillar 1: [Category education] — for TOFU awareness
- Pillar 2: [Problem framing + solutions] — for MOFU consideration
- Pillar 3: [How-to / implementation] — for BOFU intent
- [ ] Set up content production workflow: topic brief → outline → draft → review → publish
- [ ] Hire or assign: 1–2 freelance writers (niche expertise preferred); 1 editor; 1 SEO specialist
- [ ] Define content distribution workflow: publish → social share → email to list → outreach for backlinks
- [ ] Publish Week 1: 1 long-form pillar post (2,000–3,000 words) + 1 short-form tactical post

Day 31–60: Cadence + Distribution
- [ ] Maintain 2 posts/week; week 1–2: 1 pillar + 1 short-form; week 3–4: repeat
- [ ] Set up email newsletter: weekly digest of new content to full subscriber list
- [ ] Repurpose content: each long-form post → LinkedIn carousel + Twitter thread + newsletter section
- [ ] Begin organic social distribution: founder and team resharing; LinkedIn native articles
- [ ] Analyze first-month data: which topics drove most organic traffic and most email signups? Prioritize those pillars.
- [ ] Guest post outreach: pitch 2–3 relevant publications for backlinks

Day 61–90: Optimization + Pipeline Attribution
- [ ] Review content performance: organic sessions, email subscribers, MQLs attributed to content
- [ ] Identify top 3 performing posts; update and expand them (add new data, more depth, better CTA)
- [ ] Begin SEO keyword expansion: target 5–10 new keywords in the 100–500 monthly search volume range
- [ ] Create first content-to-pipeline attribution report: which posts are generating demo requests?
- [ ] Launch first "ultimate guide" pillar page targeting your primary category term (3,000–5,000 words; thorough treatment)
- [ ] End-of-quarter: Is content producing measurable pipeline? If not by Month 4, revisit content-to-CTA conversion optimization.

Content KPIs: Organic sessions; email subscriber growth; content-attributed MQLs; organic traffic-to-MQL conversion rate.

Community Playbook¶

Goal (30/60/90): Build the community flywheel — start with internal advocates, then expand to external community.

Day 1–30: Seed the Community
- [ ] Identify your top 20 customers by NPS and engagement — these are your founding community members
- [ ] Set up community infrastructure: Slack workspace (preferred for B2B), or Circle/Discourse forum
- [ ] Define community rules and value proposition: what will members get that they can't get elsewhere?
- [ ] Invite founding members personally (CEO/founder outreach); make it feel exclusive and curated
- [ ] Schedule recurring community events: weekly office hours, monthly user spotlight, quarterly AMA with product team
- [ ] Seed content: share exclusive data, early product previews, beta access in the community first

Day 31–60: Grow Beyond Founders
- [ ] Launch public-facing community invitation (via in-product prompt, email to full customer list, blog/social call-out)
- [ ] Create first community-generated content: highlight customer wins, feature community members
- [ ] Introduce member recognition: "Champion of the week," community badges, referral acknowledgment
- [ ] Begin community-to-content flywheel: community discussions → blog post topics → shared externally
- [ ] Launch community channel for peer support (reduces support ticket load; builds advocacy)
- [ ] Measure: MAU (active members), weekly message volume, new member growth rate

Day 61–90: Community as Pipeline
- [ ] Introduce community-first lead gen: gated webinars for community members + prospects
- [ ] Identify top advocates: the 10% of members who are most active — these become your referral source
- [ ] Launch formal referral program: community advocates referring their peers (tech contacts, industry peers)
- [ ] Begin community-to-events flywheel: community meetups at industry conferences; invite community members to speak
- [ ] Track: Community-attributed pipeline (demo requests from community channel or community mentions in CRM); referral revenue from community members
- [ ] End-of-quarter: Is community producing measurable pipeline? Is community reducing churn? Both are the right metrics.

Community KPIs: MAU; community-driven leads per quarter; referral rate from community members; community NPS vs. product NPS; support ticket deflection rate.

ABM Playbook (Tier 2 — 1:Few)¶

Goal (30/60/90): Stand up a targeted ABM motion for a defined account cohort; prove account engagement correlates with pipeline quality.

Day 1–30: List Building + Tooling
- [ ] Define ABM cohort: 25–100 accounts grouped by shared characteristics (same vertical, similar size, same tech stack)
- [ ] Build target account list in ABM tool (6sense, Demandbase, or Terminus — or LinkedIn Campaign Manager for lighter approach)
- [ ] Set up intent data (Bombora for topic intent; 6sense for behavioral intent) if budget allows
- [ ] Define account engagement score (weighted across: website visits, content downloads, email engagement, LinkedIn impressions, direct mail receipt)
- [ ] Create cohort-level personalization: industry-specific messaging, case study from same vertical, problem-specific content
- [ ] Align with sales: joint account planning for top 20 accounts in cohort; assign AE/SDR ownership

Day 31–60: Multi-Channel Orchestration
- [ ] Launch LinkedIn awareness campaign to full account list (job title targeting within accounts)
- [ ] Launch retargeting campaign (display/programmatic) across the web targeting account list IPs + account-level cookies
- [ ] Begin personalized email nurture sequence (3–5 emails) for accounts showing intent signals
- [ ] Send personalized direct mail to executive contacts at top 20 accounts (book relevant to their industry challenge; personalize by name and title)
- [ ] Trigger-based outreach: if an account visits your pricing page or downloads a case study, escalate to sales (same-day follow-up)
- [ ] Weekly: Review account engagement scores; flag accounts scoring >50 points for immediate sales follow-up

Day 61–90: Pipeline Integration + Measurement
- [ ] Review ABM-influenced pipeline: how many opportunities were touched by ABM campaign in last 90 days?
- [ ] Calculate: ABM-influenced win rate vs. non-ABM win rate; ABM-influenced deal size vs. non-ABM deal size
- [ ] For top 10 accounts with highest engagement scores: escalate to Tier 1 (1:1 ABM) with fully personalized campaign
- [ ] Refine account list for next quarter: remove accounts with low engagement, add new accounts showing intent signals
- [ ] Present ABM ROI to leadership: influenced pipeline, influenced revenue, cost per influenced opportunity
- [ ] End-of-quarter: If ABM-influenced pipeline is >30% of total pipeline and ABM-influenced win rates are 20%+ higher, scale the program.

ABM KPIs: ABM-influenced pipeline ($ and % of total); ABM-influenced win rate; account engagement score vs. deal velocity; cost per influenced opportunity.

7. GTM Testing Cadence¶

Testing new channels systematically prevents two failure modes: (1) doubling down on channels that look good but have no ROI, and (2) killing channels too early because they haven't had time to optimize.

The 90-Day Test Protocol¶

Every new channel follows this protocol before a scale/kill decision:

Week 1–4: Setup and Baseline
- Launch with minimum viable budget ($2K–$10K depending on channel and company stage)
- Set up tracking: UTMs, conversion events, CRM pipeline attribution
- Establish baseline metrics: CPC, CPM, impression volume, click-through rate
- Do not judge performance on revenue in Month 1 — judge on leading indicators (engagement, click-through, form fills)

Week 5–8: First Optimization Pass
- Pause worst-performing ad sets/campaigns (bottom 25% by cost per engagement)
- Double down on top-performing variants
- Apply first optimization learnings to targeting, creative, or copy
- Measure: Is the channel producing engagement at a reasonable cost?

Week 9–12: Conversion Assessment
- Now measure conversion metrics: MQL rate, demo request rate, trial start rate
- Calculate early ROI signal: (pipeline created × historical close rate × ACV) / spend
- If early ROI signal is positive (>0.5x) AND engagement metrics are healthy → continue to Month 4
- If early ROI signal is negative (<0x) AND engagement is also poor → escalate to kill review
- If early ROI signal is unclear → extend test to Month 4 with reduced budget

End of Month 3: Scale/Kill Decision

When to Double Down vs. Kill a Channel¶

Double down when:
- Channel has positive ROI (even if early and small)
- Channel shows consistent improvement across 2+ optimization cycles
- Channel fits the GTM archetype (don't kill PLG channels if PLG is the archetype)
- Channel is producing strategic signals (brand mentions, ABM influence) even without direct ROI
- The team has capacity to optimize without deprioritizing other high-ROI channels

Kill when:
- 90-day test fails the kill decision criteria above
- Channel has been running for 6+ months without positive ROI signal
- Channel requires a fundamental creative/targeting shift to work (not just optimization)
- Budget is needed for a channel with proven ROI
- Channel actively produces negative brand signals (spam complaints, low-quality leads damaging sales team morale)

Warning: Do not kill channels based on a single bad week. Do not double down on channels based on a single good week. Both decisions require trend data across at least 4 weeks.

Channel Efficiency Metrics¶

Core metrics every channel must track:

Blended CAC vs. Channel-Specific CAC:
- Always report blended CAC to the board — it's the true cost of growth
- Report channel-specific CAC internally to allocate budget — but don't let it create silos (channels work together)
- Attribution note: Last-touch over-credits "closing" channels; first-touch over-credits awareness channels. Use multi-touch (linear, time-decay, or data-driven) for internal allocation decisions.

Source: OpenView Partners, SaaS Metrics that Matter (2023); Bessemer Venture Partners, SaaS Benchmark Report (2023); SaaHero, CAC Payback Benchmarks by ACV Tier (2024).

Quick Reference¶

GTM Archetype Decision Summary¶

Budget Allocation Summary¶

Quarterly Planning Timeline¶

Sources cited:

• RACE Framework, Pratap Tony / Smart Insights (2024)
• HubSpot, Flywheel Momentum Framework (2018)
• Winning by Design, The SPICED Customer Success Framework (2021)
• Demandbase, ABM Platform Buyer Survey (2023)
• ITSMA, ABM Leadership Survey (2022)
• Bombora, The State of Intent Data (2023)
• 6sense, ABM Measurement Framework (2023)
• Reforge, GTM Archetypes (2022)
• Bessemer Venture Partners, PLG Market Map (2023)
• OpenView Partners, 2023 SaaS Benchmark
• OpenView Partners, The PLG + SLG Playbook (2023)
• GTMnow, The 5-Phase Framework That Grew Outreach from $0 to $230M ARR (Mark Kosoglow, 2024)
• SaaHero, B2B SaaS Marketing Budget Allocation & CAC Payback Benchmarks (2024)
• Gartner, B2B Buying Journey Report (2022)
• Lenny Rachitsky, Quarterly Planning Playbook (2024)

Concepts¶

Extracted from this source: race-framework · gtm-archetype

Related concepts: channel-selection · ideal-customer-profile · product-led-growth · community-led-growth · account-based-marketing