# SaaS Conversion & Profitability Playbook — Feb 2026

**Purpose:** All SaaS, all pay models. No open source. This playbook is grounded in 100-search-scale research (Feb 2026) on conversion, data, marketing, and best practices so we convert to the most paying and most profitable customers for our full remit.

**SSOT:** GitHub (issues, project board). Actions from this playbook are broken into micro-verbosity tasks in GitHub and orchestrated to macro goals.

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## 1. Positioning: All SaaS, All Pay

- **No open source.** We deliver a **SaaS product** with **pay models** only. Conversion and profitability are the bar.
- **Full remit:** GPU remit, local-only path, read-only access, per-GPU opt-in, value from real data — all serve **paying customers** and **profitability**.

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## 2. Conversion Benchmarks (Feb 2026)

| Metric | Median / Typical | Good | Great / Top |
|--------|-------------------|------|-------------|
| Free-to-paid (overall) | 8% | — | 10–15%+ |
| Freemium | 3–5% | 8–12% | — |
| Free trial (no CC) | 4–6% | 10–15% | — |
| Free trial (CC required) | — | 25–35% | 50–60% |
| Landing page conversion | 3.8% | — | 10–15% |
| Activation (first value) | 20–35% | 40%+ | &lt;5 min to first value |
| Trial-to-paid (14-day) | — | 15–25% | CC upfront 5x vs no CC |
| LTV:CAC | 3–5x | &gt;5x | — |
| CAC payback | 15–20 mo | &lt;12 mo | 8 mo (ACV &lt;$5K) |
| Monthly churn (B2B) | 3.5% | &lt;2% | Top 10% &lt;1% |
| NRR ($10–50M ARR) | 105–110% | &gt;115% | — |

**Takeaways:** Credit card upfront on trial 5x conversion; three tiers + decoy/anchor; activation in &lt;5 min; reduce checkout friction (30–40% abandon); transparent pricing 10–15% higher conversion.

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## 3. Conversion Levers (Actionable)

### 3.1 Pricing & packaging
- **Three tiers**; middle tier “Most Popular” (60–70% of signups). Decoy effect: +30–40% conversion on target tier.
- **Anchor high:** Show highest price first; strikethrough/original price can add ~40% lift.
- **Transparent pricing:** 10–15% higher conversion, 30% shorter cycles, 50% more trust. Avoid hidden fees.
- **Consumption/usage-based** where it fits (GPU, API, tokens); 58% of AI SaaS use subscription, 35% shifting to consumption.
- **Value metrics** over arbitrary feature gates (API calls, compute, seats).

### 3.2 Trial & signup
- **Trial with CC upfront** where acceptable: 30%+ conversion vs ~5% without.
- **14-day trial** most common (62%); 7-day for urgency, 30-day for delayed conversion.
- **First value in &lt;5 minutes**; activation &gt; onboarding completion. Reduce setup steps.
- **Developer tools:** First API call in ~90 sec; code-first onboarding &gt; form-first.

### 3.3 Landing & pricing pages
- **Outcome-focused CTAs** (“See 2x ROI in 30 days”) &gt; generic “Sign up” (e.g. +202% in studies).
- **Social proof:** 5+ reviews ~270% lift; video testimonials ~80%; trust badges 17–21% revenue lift.
- **Interactive demos** 2x static; AI personalization ~40% lift. Page speed: ~7% drop per second.
- **Mobile-first:** 79–83% visits mobile; desktop still converts ~8% better — optimize both.

### 3.4 Checkout & payment
- **Fewer steps and fields;** single-page checkout ~20% less abandonment. 30–40% abandon at checkout otherwise.
- **No surprise costs;** show all costs upfront. Guest checkout where possible (24% abandon on forced account).
- **Trust signals** at payment (badges, SSL); inline trust ~18% higher completion.
- **Embedded checkout** in-product &gt; redirect. Express (Apple Pay, etc.) +12–15%.

### 3.5 Onboarding & activation
- **Activation &gt; completion.** Define First Activation Event (FAE); get users there in &lt;5 min.
- **Segment by use case;** avoid generic tours. Pre-populate empty states.
- **Trial email sequence:** Day 0 welcome, Day 3/5/7 activation + social proof, last 3 days urgency; post-expiry recovery.

### 3.6 Retention & churn
- **Onboarding to aha in 14 days** → ~3x retention; early churn -10–20% with good onboarding.
- **Involuntary churn:** ~48% from failed payments; 40–60% recoverable via dunning.
- **Usage-based early warning** for at-risk accounts. Feedback in &lt;48h → ~2.3% churn reduction.
- **NRR &gt;105%** target; expansion offsets logo churn.

### 3.7 Trust & proof
- **Verifiable social proof** (G2, real tweets) &gt; generic; +15–20% conversion.
- **Founder-led video** &gt; polished explainer. Real numbers &gt; rounded.
- **Pricing page:** Outcomes over features; clarity over cleverness.

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## 4. AI / LLM Infrastructure SaaS (Feb 2026)

- **Hybrid GTM:** ~50/50 PLG vs SLG in AI B2B; FDEs (forward-deployed engineers) in 32% of customers (up from 20%).
- **Pricing shift:** 58% subscription, 35% moving to consumption, 18% outcome-based.
- **Gross margin:** AI SaaS 50–70% (vs 75–90% classic); inference ~23% of revenue at scale.
- **Multi-provider:** 3.1 model providers per company; OpenAI 77%, Gemini 55%, Claude 51%.
- **Unit economics:** LTV/CAC and payback timelines 18–24 mo longer than classic SaaS; consumption + value-based pricing needed.

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## 5. What We Deliver (Conversion-Focused)

- **Product:** SaaS (llmhosts.com) + pay tiers (Free / Pro / Team / Enterprise); API keys, devices, topology, marketplace, billing (Stripe).
- **Value prop:** Your GPU as production AI infra; orchestration, routing, cache, cost visibility; local + external; full remit (user control, read-only, per-GPU opt-in).
- **Conversion work:** Pricing page (three tiers, anchor, transparency); trial/signup (activation &lt;5 min, clear CTA); checkout (Stripe, minimal friction); onboarding (first value fast); trust (social proof, real data); retention (usage, dunning, NRR).

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## 6. Research Basis (Feb 2026)

Synthesized from 100-search-scale research across:
- SaaS conversion rate optimization, B2B pricing strategy, free-to-paid conversion, trial benchmarks
- Landing page, pricing page, CTA, trust signals, social proof
- Onboarding, activation, first value, PLG, checkout friction
- Churn, retention, NRR, LTV, CAC, unit economics
- AI/LLM SaaS monetization, GPU inference pricing, AI infrastructure GTM
- Consumption-based pricing, developer tools conversion, Stripe/checkout

Sources include ChartMogul, Growth Unhinged, Rework, GetMonetizely, SaaS Hero, InfluenceFlow, Eagle Rock CFO, SaaStr/ICONIQ, and 2026 CRO/benchmark reports. Exact query count and themes logged for reproducibility.

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## 7. GitHub Orchestration

Every tactic and task from this playbook is broken into **micro-verbosity issues** in GitHub (title + body with acceptance criteria, links to this doc and to remit/strategy). **Project board** and **milestones** map issues to **macro goals**: conversion, profitability, E2E, launch. **Execution order** is defined in a master playbook issue and milestone sequence. No work lives only in docs — all activities in GitHub Pro with full use of labels, custom fields, and automation.

**Current issues (Feb 2026):**
- **Master playbook:** #325 (execution order + full micro index in comment).
- **Conversion epics:** #326→#332. **Conversion micro:** #333–#344 (all done): Three tiers, Anchor, Transparent pricing, Value metrics, FAE, First API 90s, Outcome CTAs, Social proof, Single-page checkout, Dunning, NRR, Verifiable social proof.
- **E2E:** #319; #354–#358 (App Auth, routes, API Keys, CLI, Proxy); #359 Round 1 Alienware, #360–#362 Round 2, #363 Gap analysis.
- **OpenClaw/Research/Remit:** #345–#347, #348, #350–#352 (done). #349, #353 (done). Research log: docs/marketing/research-100-search-log.md. Remit: config.remit.local_only + remit_allowlist; tunnel no-op when local_only; onboarding copy on devices page.
- All in Project #5; milestones: Conversion wave 1, E2E Round 1 Alienware, E2E Round 2 diversity, POC Testing Phase. See `docs/planning/github-project-5-views.md`.
