Skip to content This library is free, offered as dana. If it helps your work, donate here →

This is one of 3,622 free prompts in the penguin tree ai library. Sign up once and the whole library opens, with new prompts by email.

open the library →

Organic-to-pipeline OKR builder

Builds a full quarterly OKR set that connects organic channel inputs (traffic, rankings, share of voice) to revenue outcomes (SQLs, pipeline, ARR, activation, blended CAC) using a defensible conversion model…

download .md

Purpose

Translate top-of-funnel organic signals into revenue-accountable OKRs — building the conversion model that connects sessions, rankings, and share of voice to SQLs, pipeline, ARR, activation, and blended CAC, so an organic team can be measured on outcomes it can actually defend in a quarterly business review.

When to Use

Invoke this skill when the user asks to:

  • Build quarterly OKRs for an SEO, content, or organic growth team
  • Connect organic traffic and rankings to revenue or pipeline targets
  • Set defensible SQL, ARR, or activation goals tied to organic channels
  • Justify organic investment against paid channels using a shared revenue model
  • Reverse-engineer how much organic traffic is needed to hit a pipeline number
  • Replace vanity-metric goals (traffic, keyword count) with revenue-linked key results

Inputs Required

Before starting, collect:

  • Current organic metrics: Monthly organic sessions, tracked keyword count, top-3/top-10 ranking share, and share of voice if available
  • Funnel conversion rates: Known rates for session→lead, lead→MQL, MQL→SQL, SQL→closed-won (any that exist; the model fills gaps with benchmarks)
  • Deal economics: Average contract value (ACV) or ARR per deal, and average sales cycle length
  • Pipeline or revenue target: The quarterly SQL, pipeline coverage, or new ARR number the team is accountable to
  • Activation definition: What "activated" means for this product and current activation rate, if the goal set includes product engagement
  • Current CAC or blended CAC target: Existing customer acquisition cost and the efficiency bar for the quarter
  • Team capacity & timeframe: Content/link/technical output the team can realistically ship, and the quarter being planned

If funnel conversion rates are missing, apply B2B SaaS organic benchmarks (session→lead 1.5–3%, lead→SQL 10–15%, SQL→won 20–25%) and flag each assumed value explicitly.

Instructions

Step 1: Build the Organic-to-Revenue Conversion Model

Construct the bridge from traffic to ARR before setting any target. Work backward from the revenue goal AND forward from current traffic, then reconcile the two.

Forward calculation (what current organic produces):

Monthly organic sessions
  × session→lead rate        = organic leads
  × lead→SQL rate            = organic SQLs
  × SQL→closed-won rate      = organic new customers
  × ACV                      = organic ARR

Backward calculation (what the target requires):

Target new ARR ÷ ACV                = customers needed
  ÷ SQL→won rate                    = SQLs needed
  ÷ lead→SQL rate                   = leads needed
  ÷ session→lead rate               = sessions needed

State the traffic gap: sessions needed minus sessions the current trajectory delivers. This gap is the actual planning problem — everything downstream sizes against it. Flag every conversion rate as either "provided" or "benchmark assumed."

Step 2: Diagnose Where the Gap Gets Closed

The gap closes through one or more of four levers. Assign a rough contribution split (must sum to 100%):

  • Volume — new rankings and content driving incremental sessions (slow, compounds; 4–6 month lag to revenue)
  • Position — moving existing page-1 rankings up (fast, high leverage; a jump from position 5→2 can 3–4x CTR)
  • Conversion — improving session→lead rate via intent-matched content, CRO, and offer placement (fastest to revenue)
  • Retention/Activation — improving activation of organic-sourced signups (compounds LTV, affects CAC payback)

Recommend the split based on the timeframe: for a single quarter, weight Position and Conversion higher than Volume, since new content rarely converts to ARR inside 90 days.

Step 3: Draft 3–5 Objectives

Each objective is a qualitative, directional statement tied to a business outcome — not a metric. Structure the set so it spans the funnel:

  • One acquisition objective (grow qualified organic demand)
  • One conversion/pipeline objective (turn demand into SQLs and pipeline)
  • One efficiency objective (improve organic CAC or payback)
  • Optionally one activation/retention objective and one defensibility/moat objective (share of voice, topical authority)

Write each objective in one sentence that a CRO would recognize as a business goal.

Step 4: Attach Key Results to Each Objective

For every objective, write 2–4 key results. Each KR must be:

  • Measurable with a baseline and a target (e.g., "Grow organic SQLs from 42 to 68/quarter")
  • Paired as leading + lagging — include at least one leading indicator (rankings, sessions, lead volume) and one lagging indicator (SQLs, pipeline, ARR) per objective so the team gets an early signal
  • Owned — attributable to organic influence, not shared credit with paid unless explicitly modeled

Format each KR as: Metric: baseline → target (indicator type).

Step 5: Set the CAC and Efficiency Guardrail

Calculate implied organic CAC for the plan:

Organic team + content + tooling cost for quarter ÷ organic new customers = organic CAC

Set the CAC key result relative to blended CAC and paid CAC — organic's argument is almost always CAC efficiency and compounding, so make that explicit. Include a CAC payback figure (CAC ÷ monthly ACV) where activation data allows.

Step 6: Stress-Test and Add a Confidence Rating

Rate each objective Committed (≥70% confidence, resourced) or Aspirational (stretch, 40–60%). Identify the single highest-risk assumption in the model (usually the session→lead or SQL→won rate) and state what would break the plan if it's off by 20%.

Output Format

  • Structure: Conversion model first (with forward/backward math and the traffic gap), then the gap-closing lever split, then the OKR set organized by objective with nested key results, then the CAC guardrail and confidence ratings
  • Length: 900–1,300 words
  • Format: Structured document — model math in code-style blocks or a small table, OKRs as a labeled hierarchy (Objective → Key Results)
  • Sections: Conversion Model & Traffic Gap → Gap-Closing Lever Split → Objectives & Key Results (3–5 objectives) → CAC/Efficiency Guardrail → Confidence Ratings & Key Risk
  • Tone: Growth director in a QBR — quantitative, defensible, no vanity metrics, willing to state assumptions plainly

Quality Checklist

Before delivering output, verify:

  • [ ] The forward and backward calculations both appear and the traffic gap is stated as a specific number
  • [ ] Every conversion rate is labeled "provided" or "benchmark assumed" — no silent assumptions
  • [ ] The lever contribution split (Volume/Position/Conversion/Retention) sums to 100%
  • [ ] Each of the 3–5 objectives has at least one leading and one lagging key result
  • [ ] Every key result has a baseline → target, not just a target
  • [ ] Organic CAC is calculated and compared against blended or paid CAC
  • [ ] Each objective is rated Committed or Aspirational and the single highest-risk assumption is named

Notes

  • The most common failure in organic OKRs is committing to ARR that new content can't produce inside the quarter — Volume-driven revenue lags 4–6 months, so a Q1 content push shows up as Q3 pipeline. Weight in-quarter targets toward Position and Conversion levers.
  • If the team has no session→lead data, the entire model rests on a benchmark — say so loudly and recommend instrumenting attribution as its own key result.
  • Share of voice and topical authority are legitimate lagging-moat KRs, but they should never be the only KR under an objective; always pair with a pipeline or ARR number so the goal stays revenue-accountable.
  • When defending organic against paid, the winning argument is compounding CAC efficiency and payback — make the CAC guardrail the headline, not traffic growth.

How to use this skill

This file is a Claude Code skill in Anthropic's standard format — markdown with YAML frontmatter at the top.

Installing in Claude Code:

  • ~/.claude/skills/<folder-name>/SKILL.md — auto-loads in every session anywhere on your machine (recommended for skills you'll use across multiple projects)
  • <your-project>/.claude/skills/<folder-name>/SKILL.md — auto-loads only when working in that project (recommended for project-specific skills)

Restart Claude Code or open a new session to register.

Using in Claude.ai, ChatGPT, Gemini, or other AI tools:

  1. Drag this file into a new chat, or copy and paste its contents
  2. Send your task or request as your next message — the AI will apply the skill where it fits

For Claude Code skill details: https://docs.anthropic.com/en/docs/claude-code/skills