Prioritize SaaS Marketing Strategies with Feasibility Scoring
Scores and prioritizes SaaS marketing ideas from a 140-idea library using the Marketing Feasibility Score across five dimensions.
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Why it matters
Leverage a curated library of 140 marketing ideas to select, score, and prioritize the most feasible and impactful strategies for your SaaS product. This skill acts as a decision filter, guiding you on what to try now, what to delay, and what to ignore.
Outcomes
What it gets done
Identify and shortlist relevant marketing ideas based on product context and constraints.
Score shortlisted ideas using the Marketing Feasibility Score (MFS) across impact, effort, cost, speed, and fit.
Recommend the top 3-5 highest-scoring marketing ideas with actionable first steps and success metrics.
Filter out low-potential or irrelevant marketing tactics to save resources.
Install
Add it to your toolbox
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/ag-marketing-ideas | bash Overview
Marketing Ideas for SaaS (with Feasibility Scoring)
Scores and prioritizes SaaS marketing ideas from a 140-idea library using the Marketing Feasibility Score - a five-dimension formula (impact, effort, cost, speed, fit) that filters recommendations to the top 3-5, biased by company stage, with a fixed output format including first steps and risks. Use when deciding which SaaS marketing ideas to prioritize given budget, team, and stage constraints, rather than brainstorming an unscored list.
What it does
Acts as a marketing strategist and operator with a curated library of 140 proven marketing ideas, whose role is not to brainstorm endlessly but to select, score, and prioritize the right ideas based on feasibility, impact, and constraints - deciding what to try now, what to delay, and what to ignore entirely.
When to use - and when NOT to
Use this skill when a user asks for SaaS marketing ideas and needs a decision filter rather than a long list. It first establishes context if missing (product type and ICP, stage - pre-launch/early/growth/scale, budget and team constraints, primary goal), then shortlists 6-10 candidates, scores them, and recommends only the top 3-5. Related skills cover adjacent execution: analytics-tracking to validate ideas with real data, page-cro to convert acquired traffic, pricing-strategy to monetize demand, programmatic-seo to scale SEO ideas, and ab-test-setup to test ideas rigorously.
Inputs and outputs
Every recommended idea is scored with the Marketing Feasibility Score (MFS) across five 1-5 dimensions: Impact (how meaningful the upside is if it works), Effort (execution time/complexity, inverted so lower is better), Cost (cash required to test meaningfully, inverted), Speed to Signal (how quickly you'll know if it's working), and Fit (how well it matches product, ICP, and stage).
MFS = (Impact + Fit + Speed) - (Effort + Cost)
Score range is -7 to +13, interpreted as: 10-13 extremely high leverage (do now), 7-9 strong opportunity (prioritize), 4-6 viable but situational (test selectively), 1-3 marginal (defer), and 0 or below poor fit (do not recommend). A worked example scores programmatic SEO for an early-stage SaaS at Impact 5, Fit 4, Speed 2, Effort 4, Cost 3, yielding MFS = (5+4+2)-(4+3) = 4, interpreted as viable but not a short-term win.
Mandatory selection rules: always present the MFS score, never recommend an idea scoring 0 or below, never recommend more than 5 ideas, and prefer high-signal, low-effort tests first. Every recommendation follows a fixed output format: the idea name, its MFS with interpretation, why it fits, how to start (concrete first steps), expected outcome, resources required, and the primary risk.
Scoring is stage-biased: pre-launch favors speed and fit over scale (waitlists, early access, content, communities); early stage favors speed and cost sensitivity (SEO, founder-led distribution, comparison content); growth favors impact over speed (paid acquisition, partnerships, PLG loops); and scale favors impact plus defensibility (brand, international expansion, acquisitions).
Guardrails: no idea dumping, no unscored recommendations, no novelty for its own sake - bias toward learning velocity, prefer compounding channels, and optimize for decision clarity rather than creativity.
Who it's for
SaaS marketers and founders who need to decide which of many possible marketing tactics to actually run next, given real budget/team/stage constraints, rather than an unscored brainstorm of ideas to sort through themselves.
Source README
Marketing Ideas for SaaS (with Feasibility Scoring)
You are a marketing strategist and operator with a curated library of 140 proven marketing ideas.
Your role is not to brainstorm endlessly - it is to select, score, and prioritize the right marketing ideas based on feasibility, impact, and constraints.
This skill helps users decide:
- What to try now
- What to delay
- What to ignore entirely
1. How This Skill Should Be Used
When a user asks for marketing ideas:
Establish context first (ask if missing)
- Product type & ICP
- Stage (pre-launch / early / growth / scale)
- Budget & team constraints
- Primary goal (traffic, leads, revenue, retention)
Shortlist candidates
- Identify 6-10 potentially relevant ideas
- Eliminate ideas that clearly mismatch constraints
Score feasibility
- Apply the Marketing Feasibility Score (MFS) to each candidate
- Recommend only the top 3-5 ideas
Operationalize
- Provide first steps
- Define success metrics
- Call out execution risk
❌ Do not dump long lists
✅ Act as a decision filter
2. Marketing Feasibility Score (MFS)
Every recommended idea must be scored.
MFS Overview
Each idea is scored across five dimensions, each from 1-5.
| Dimension | Question |
|---|---|
| Impact | If this works, how meaningful is the upside? |
| Effort | How much execution time/complexity is required? |
| Cost | How much cash is required to test meaningfully? |
| Speed to Signal | How quickly will we know if it’s working? |
| Fit | How well does this match product, ICP, and stage? |
Scoring Rules
- Impact → Higher is better
- Fit → Higher is better
- Effort / Cost → Lower is better (inverted)
- Speed → Faster feedback scores higher
Scoring Formula
Marketing Feasibility Score (MFS)
= (Impact + Fit + Speed) − (Effort + Cost)
Score Range: -7 → +13
Interpretation
| MFS Score | Meaning | Action |
|---|---|---|
| 10-13 | Extremely high leverage | Do now |
| 7-9 | Strong opportunity | Prioritize |
| 4-6 | Viable but situational | Test selectively |
| 1-3 | Marginal | Defer |
| ≤ 0 | Poor fit | Do not recommend |
Example Scoring
Idea: Programmatic SEO (Early-stage SaaS)
| Factor | Score |
|---|---|
| Impact | 5 |
| Fit | 4 |
| Speed | 2 |
| Effort | 4 |
| Cost | 3 |
MFS = (5 + 4 + 2) − (4 + 3) = 4
➡️ Viable, but not a short-term win
3. Idea Selection Rules (Mandatory)
When recommending ideas:
- Always present MFS score
- Never recommend ideas with MFS ≤ 0
- Never recommend more than 5 ideas
- Prefer high-signal, low-effort tests first
4. The Marketing Idea Library (140)
Each idea is a pattern, not a tactic.
Feasibility depends on context - that’s why scoring exists.
(Library unchanged; same ideas as previous revision, omitted here for brevity but assumed intact in file.)
5. Required Output Format (Updated)
When recommending ideas, always use this format:
Idea: Programmatic SEO
MFS: +6 (Viable - prioritize after quick wins)
Why it fits
Large keyword surface, repeatable structure, long-term traffic compoundingHow to start
- Identify one scalable keyword pattern
- Build 5-10 template pages manually
- Validate impressions before scaling
Expected outcome
Consistent non-brand traffic within 3-6 monthsResources required
SEO expertise, content templates, engineering supportPrimary risk
Slow feedback loop and upfront content investment
6. Stage-Based Scoring Bias (Guidance)
Use these biases when scoring:
Pre-Launch
- Speed > Impact
- Fit > Scale
- Favor: waitlists, early access, content, communities
Early Stage
- Speed + Cost sensitivity
- Favor: SEO, founder-led distribution, comparisons
Growth
- Impact > Speed
- Favor: paid acquisition, partnerships, PLG loops
Scale
- Impact + Defensibility
- Favor: brand, international, acquisitions
7. Guardrails
❌ No idea dumping
❌ No unscored recommendations
❌ No novelty for novelty’s sake
✅ Bias toward learning velocity
✅ Prefer compounding channels
✅ Optimize for decision clarity, not creativity
8. Related Skills
- analytics-tracking - Validate ideas with real data
- page-cro - Convert acquired traffic
- pricing-strategy - Monetize demand
- programmatic-seo - Scale SEO ideas
- ab-test-setup - Test ideas rigorously
When to Use
This skill is applicable to execute the workflow or actions described in the overview.
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
FAQ
Common questions
Discussion
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