Results for “pricing”

Guides SaaS pricing strategy: selecting models, value metrics, packaging tiers, and applying psychology tactics to optimize revenue.

Design value-based pricing, packaging, and monetization strategies for SaaS products, including tier structures, value metrics, and price optimization.

Configures and troubleshoots Salesforce CPQ pricing: Price Rules, Discount Schedules, Block Pricing, Percent of Total, and Contracted Prices.

Selects pricing models (subscription, usage-based, value-based, freemium, hybrid), analyzes willingness-to-pay survey data with Van Westendorp PSM, and designs Good/Better/Best packaging tiers with anti-pattern detection.

Design products and pricing around validated willingness to pay, using the framework from Ramanujam & Tacke's "Monetizing Innovation" to avoid common monetization failures.

Evaluate the financial impact of pricing changes using ARPU, conversion, churn risk, NRR, and payback analysis to make data-driven go/no-go decisions.

Provides evidence-first revenue, pricing, refunds, team-billing, and billing-model truth workflows for sales snapshots, pricing comparisons, duplicate-charge diagnosis, or code-backed billing reality.

Provides revenue leadership frameworks for B2B SaaS companies, including forecasting, pricing strategy, sales model design, and team scaling.

Researches competitors, compares features, pricing, and tech stacks, then produces a prioritized gap analysis with actionable roadmap.

Defines the product vision, architecture, pricing, and roadmap for Auri, an intelligent voice assistant built on Amazon Alexa and Claude.

Analyzes competitor products by synthesizing data from pricing pages, app store reviews, job postings, SEO signals, and social media into structured competitive intelligence. Produces feature comparison matrices, SWOT analyses, positioning maps, UX audits, pricing breakdowns, action plans, and presentations.

Create a strategy for selling to your first 100 customers using the minimalist entrepreneur playbook, with actionable steps for outreach, pricing, and tracking.

Transforms scattered competitor data into a decision-ready product strategy report with positioning maps, feature matrices, pricing analysis, and opportunity windows.

Guides strategic product decisions, pricing, backlog prioritization, and trend intelligence, routing tasks to specialized sub-skills.

Run structured competitive analysis with feature matrices, SWOT, pricing comparison, review mining, and positioning maps using the inference.sh CLI.

Routes commercial inquiries to specialized sub-skills for pricing, deal desk, partnerships, channel economics, policy, RFP response, and forecasting. Provides deterministic decision support with canon-cited analysis and human-approver routing.

Sell to AI agents with machine-readable products, agent-optimized APIs, structured pricing, and discovery strategies for the agentic economy.

Proposal research workflow that matches local case studies and gathers web evidence into an HTML research dossier. Use when the user needs proposal research, client intel, tech stack discovery, pricing benchmarks, competitive context, or case-study matching for a brief. Triggers: 'research this proposal', 'build a research dossier', 'match case studies', 'find pricing benchmarks', 'client intel for', 'what tech does X use'.

Designs revenue models, sets value-based price points, and creates referral loops to turn users into paying customers.

Brainstorm 3-5 monetization strategies with audience fit, risks, and validation experiments for a product or feature.

Turn a product idea into a manual-first process you can start delivering today, before writing any code.

Diagnoses business models using dontbesilent's ontological framework, offering consultation mode to dissolve problems and checkup mode to analyze business structures.

Define o produto Auri, um assistente de voz inteligente baseado em Alexa e Claude, incluindo arquitetura AWS, planos de preços, roadmap e estratégia de mercado.

Design or revise a company's commercial policy governing discounts, approver thresholds, exception flows, and deal frameworks using data-backed matrices and linting tools.

Optimizes in-app paywalls and upgrade flows to convert free users to paid or upgrade users to higher tiers at moments of peak value.

Breaks down a company's business model, revenue signals, positioning, pricing, moat, and weak points into a fixed, comparable template with fact-versus-inference labeling.

World-class autonomous sales and revenue skill system. Use ANY time the user asks to sell, pitch, prospect, close, negotiate, launch, monetize, build funnels, write outreach, craft proposals, develop pricing, design offers, write sales copy, create email sequences, plan campaigns, position products, handle objections, create playbooks, build pipeline, forecast revenue, develop GTM strategy, optimize conversions, write ad copy, create sales decks, score leads, nurture prospects, upsell, cross-sell, retain customers, write case studies, price products, structure enterprise deals, create battle cards, script discovery calls, build affiliate programs, plan product launches, create webinar funnels, design pricing pages, A/B test offers, analyze unit economics, calculate LTV/CAC, or ANY other sales, revenue, monetization, go-to-market, or commercial growth task. If it involves selling, revenue, deals, pipeline, or commercial strategy — USE THIS SKILL. Trigger aggressively.

Prepare and execute negotiations using tactical empathy, calibrated questions, and the Ackerman method. Use when the user mentions "salary negotiation", "contract terms", "handling objections", "mirroring and labeling", "difficult conversation", "deal terms", "BATNA", or "anchoring". Also trigger when preparing for vendor negotiations, resolving pricing disputes, or navigating high-stakes conversations where both parties need to feel heard. Covers accusation audits, Black Swan discovery, and the "Thats Right" technique. For persuasion in product/marketing, see influence-psychology.

Orchestrator for the experimentation skill suite — turn assumptions and product questions into rigorous, well-instrumented experiments and decision-grade readouts. Routes through backlog → spec → runbook → readout based on user need and existing artefacts. Platform-agnostic with PostHog as the primary binding. Load when the user asks to design an experiment, A/B test something, set up an experiment, run a holdout, test a hypothesis, decide what to test next, read out experiment results, analyse a test, or says "should we A/B test this", "experiment on the landing page", "is this lift real", "ship or kill this test", "what should we test next", "build an experiment backlog", "test the pricing page", "validate this with an experiment".

When the user needs a comprehensive marketing plan for a client, a company they advise, or their own product. Also use when the user mentions "marketing plan," "growth plan," "GTM plan," "go-to-market plan," "AARRR plan," "90-day marketing plan," "12-month marketing roadmap," "fractional CMO plan," or "fCMO plan." Generates an exhaustive 13-section plan structured by AARRR (Acquisition, Activation, Retention, Referral, Revenue), customized to the client's current budget, team, and stage, mapped to future funding milestones, cross-referenced with the 139-idea marketing-ideas library and an embedded 17-section current-state audit rubric, with a full marketing operations stack showing which skills and MCP/API integrations execute each part. Outputs a Notion-paste-ready markdown document. For positioning and ICP context before planning, see product-marketing. For stage-specific deep work, see onboarding, signup, emails, referrals, pricing.