pricing-strategy

Overview of pricing-strategy skill

pricing-strategy is a decision-support skill for SaaS pricing, packaging, and monetization questions. It is best for founders, product marketers, growth teams, and operators who need more than “pick a number” advice: they need a defensible pricing model, tier structure, or price-change plan tied to customer value and go-to-market reality.

What the pricing-strategy skill actually helps with

This pricing-strategy skill is designed for jobs like:

• choosing a pricing metric such as per seat, per usage, or flat rate
• structuring good-better-best tiers
• deciding between freemium and free trial
• evaluating a price increase
• aligning packaging with SMB, mid-market, or enterprise buyers
• using research methods like Van Westendorp or willingness-to-pay surveys

The practical differentiator is that it pushes the model to gather missing business context first, then reason across three pricing axes: packaging, metric, and price point. That is more useful than a generic prompt that jumps straight to arbitrary numbers.

Who should install pricing-strategy

Install pricing-strategy if you regularly ask questions such as:

• “How much should we charge?”
• “Should we bill per user or per outcome?”
• “How should we structure our plans?”
• “Can we raise prices without hurting retention?”
• “Should we offer a free plan?”

It is strongest for B2B and SaaS-style offers where value capture, segmentation, and expansion matter.

When this skill is a poor fit

pricing-strategy is less useful if you need:

• paywall copy or upgrade-screen UX optimization
• purely financial modeling without customer-value reasoning
• one-shot consumer retail pricing with heavy elasticity data already in hand
• hard econometric forecasting from large historical datasets

In those cases, you may need a different skill or a custom analysis workflow.

How to Use pricing-strategy skill

Install context for pricing-strategy

Use the skill from the coreyhaines31/marketingskills repository:

npx skills add https://github.com/coreyhaines31/marketingskills --skill pricing-strategy

The repository does not ship scripts or automations for this skill. It is prompt-and-framework driven, so output quality depends heavily on the context you provide.

Read these files first

For a fast pricing-strategy install and review path, start here:

1. skills/pricing-strategy/SKILL.md
2. skills/pricing-strategy/references/tier-structure.md
3. skills/pricing-strategy/references/research-methods.md
4. skills/pricing-strategy/evals/evals.json

This order matters. SKILL.md shows the working workflow, the references deepen the pricing choices, and evals/evals.json reveals what “good usage” looks like in practice.

Check for product marketing context before prompting

The skill explicitly tells the agent to look for .agents/product-marketing-context.md or .claude/product-marketing-context.md before asking questions. If you already maintain one of those files, this is one of the main reasons to use pricing-strategy instead of a generic pricing prompt.

If that file exists, make sure it includes:

• target customer segments
• product category and positioning
• primary value proposition
• competitive alternatives
• go-to-market motion

That prevents repetitive back-and-forth and improves recommendation specificity.

Minimum inputs the skill needs

The pricing-strategy skill works best when you supply inputs in four buckets:

• Business context: product type, target market, GTM motion, current pricing
• Value and competition: key outcomes delivered, buyer alternatives, competitor pricing
• Current performance: conversion, churn, expansion, sales friction, discounting
• Decision scope: new pricing, tier redesign, price increase, free plan decision, metric choice

Without these, the model can still respond, but it will default to generic SaaS patterns.

Turn a rough pricing goal into a strong prompt

Weak prompt:

“Help me with pricing for our SaaS.”

Stronger pricing-strategy usage prompt:

“We run a B2B SaaS for e-commerce support teams. Target customers are SMB and lower mid-market brands. Current price is $49, $99, $199 per month, but adoption is strongest on the lowest tier and expansion is weak. We are deciding between per agent, per ticket, and platform + usage pricing. Sales is hybrid: self-serve for SMB, demos for larger accounts. Main alternatives are Zendesk and Gorgias. Please use a packaging + pricing metric + price point framework, recommend a tier structure, and explain tradeoffs.”

That stronger version gives the skill enough structure to do real work.

Best workflow for pricing-strategy usage

A reliable workflow:

1. provide current business context
2. define the pricing decision you need made
3. ask the model to evaluate multiple pricing metrics or tier structures
4. request a recommendation with rationale and risks
5. ask for a rollout or validation plan

This matters because pricing decisions are rarely only about “what number feels right.” The skill is better at framing tradeoffs than producing a single unsupported price.

What the skill tends to do well

Based on the skill instructions and evals, pricing-strategy is strongest at:

• comparing pricing metrics against value delivery
• proposing good-better-best packaging
• advising on free plan vs free trial
• outlining price increase strategy
• connecting research methods to pricing uncertainty

If you want a recommendation plus reasoning, this is a strong fit.

What to ask for explicitly

To get better output, ask pricing-strategy to produce concrete artifacts such as:

• recommended tiers with names, limits, and target customers
• pricing metric decision table
• price increase rollout plan
• competitor-relative positioning summary
• research plan using Van Westendorp, MaxDiff, or willingness-to-pay surveys

The repository references are especially helpful when you need validation methods, not just a packaging guess.

Use the reference files for deeper decisions

references/research-methods.md is useful when your team lacks confidence in willingness-to-pay assumptions. It covers:

• Van Westendorp
• MaxDiff
• willingness-to-pay surveys
• usage-value correlation analysis

references/tier-structure.md is useful when your main problem is plan design rather than exact price level. It covers:

• number of tiers
• good-better-best logic
• feature vs usage differentiation
• persona-based packaging
• freemium vs free trial
• enterprise pricing triggers

Common adoption blockers

The biggest blocker to pricing-strategy install is not technical. It is incomplete context. Teams often ask the skill for pricing advice without sharing:

• who buys
• what value they pay for
• current conversion/churn signals
• whether growth is self-serve or sales-led

If you cannot provide those basics, expect broad heuristics rather than tailored pricing guidance.

pricing-strategy skill FAQ

Is pricing-strategy better than a normal pricing prompt?

Usually, yes, if your problem is strategic rather than superficial. The pricing-strategy skill gives the model a structured path: gather context, evaluate packaging, pricing metric, and price point, then recommend a direction. A normal prompt often skips directly to tier ideas with weak justification.

Is the pricing-strategy skill beginner friendly?

Yes, but beginners should come with basic business facts. You do not need advanced pricing research to start, but you do need to know your product, buyer, alternatives, and current monetization model. Otherwise the output will sound polished but remain generic.

Does pricing-strategy only work for SaaS?

SaaS is the clearest fit. The language, examples, and references strongly favor subscription software, especially products choosing between per-seat, usage-based, freemium, trial, and enterprise packaging models. It can still help adjacent digital products, but the farther you move from SaaS monetization, the more adaptation you will need.

Can pricing-strategy tell me the exact price to charge?

Not reliably from thin inputs. The skill is better at narrowing a sensible range, choosing a value metric, and designing packaging logic. Exact price points are strongest when paired with customer research, competitor review, or current performance data.

When should I not use pricing-strategy?

Skip it when your main task is:

• paywall UX or upgrade copy
• invoice, billing, or tax implementation
• deep statistical price optimization from large datasets
• one-off consulting fee estimation without tiered product logic

Does pricing-strategy support pricing research workflows?

Yes. That is one of its more useful advantages. The included references show how to run methods like Van Westendorp and MaxDiff, which makes the skill more credible for teams that want to validate a recommendation instead of accepting AI intuition.

How to Improve pricing-strategy skill

Give pricing-strategy the decision, not just the topic

Bad input: “We need pricing help.”

Better input: “We need to choose between per seat and usage-based pricing for a self-serve analytics SaaS because trial conversion is fine but expansion is weak.”

Specific decisions produce sharper tradeoff analysis and more actionable outputs.

Provide current numbers even if they are messy

Include any available metrics such as:

• trial-to-paid conversion
• demo close rate
• churn by segment
• expansion revenue
• average contract value
• share of customers hitting limits
• discount frequency

pricing-strategy becomes materially better when it can connect packaging problems to actual business signals.

Separate packaging, metric, and price point

A common failure mode is bundling all three into one vague question. Ask the skill to treat them separately:

• Packaging: what features or limits belong in each plan?
• Metric: what unit should customers pay on?
• Price point: what should each plan cost?

This mirrors the repository’s logic and prevents shallow answers.

Show competitor context without asking for cloning

Useful input looks like:

“Competitor A charges per seat, Competitor B charges by usage, and both reserve SSO and advanced reporting for enterprise. We do not want to copy them blindly; we want to know where our value capture should differ.”

That lets pricing-strategy compare norms without defaulting to imitation.

Ask for rollout risk, not just recommendation

For changes like a 30% increase, ask pricing-strategy for:

• which customers should be grandfathered
• whether new pricing should apply only to new customers first
• how to communicate the increase
• what leading indicators to watch after launch

This is especially important because a sound pricing model can still fail operationally.

Use research methods when confidence is low

If the first recommendation feels speculative, ask the skill to convert uncertainty into a validation plan using the repository references. For example:

• Van Westendorp for acceptable price range
• MaxDiff for packaging priorities
• usage-value correlation to test pricing metric fit

This is one of the best ways to improve pricing-strategy output quality after the first pass.

Iterate with counterfactuals

A strong second-round prompt is:

“Now rerun the recommendation assuming our best-fit customer is mid-market instead of SMB, and assume procurement resistance increases if we add usage pricing.”

Counterfactuals expose whether the original recommendation was robust or just anchored to one assumption set.

Request an answer format you can operationalize

If you need to act on the output, ask pricing-strategy for a structure like:

• recommendation
• rationale
• risks
• rollout plan
• validation plan
• metrics to monitor

This keeps the skill from producing an essay when you need a decision memo.

Know the main failure modes

The pricing-strategy skill is most likely to underperform when:

• the buyer segment is unclear
• product value is described in features, not outcomes
• the team wants certainty without research
• competitive context is missing
• enterprise and self-serve motions are mixed together without segmentation

Fix those inputs first before judging the skill.

Improve the repository-reading path for your team

If your team will use pricing-strategy repeatedly, create or update .agents/product-marketing-context.md with the recurring facts the skill asks for. That single step reduces prompt overhead and makes future pricing-strategy usage much more consistent.