# How to Tailor pm-product-discovery for Different Product Types (SaaS, Mobile Apps) > Tailor product discovery for SaaS and mobile apps by infusing product-type context into your workflow. Steer assumptions, metrics, and experiments for platform-specific success. - Repository: [Pawel Huryn/pm-skills](https://github.com/phuryn/pm-skills) - Tags: how-to-guide - Published: 2026-06-14 --- **You can tailor pm-product-discovery for SaaS, mobile apps, or other product platforms by injecting specific product-type context into the agnostic discovery workflow, steering assumptions, metrics, and experiments toward platform-specific constraints.** The `pm-product-discovery` module in the `phuryn/pm-skills` repository provides a domain-agnostic framework for product discovery. Because the underlying skills request context rather than enforcing rigid domain rules, you can tailor pm-product-discovery for different product types by strategically supplying platform-specific signals at each stage of the process. ## Understanding the Product-Agnostic Architecture The discovery workflow is built from **reusable skills** and **commands** that guide you from idea generation to experiment design. The core command **`/discover`** (defined in [`pm-product-discovery/commands/discover.md`](https://github.com/phuryn/pm-skills/blob/main/pm-product-discovery/commands/discover.md)) initiates the workflow by asking whether you are exploring an **existing product** (continuous discovery) or a **new product** (initial market validation). Rather than hardcoding logic for specific platforms, the skills in `pm-product-discovery/skills/` accept contextual prompts. This architecture allows you to use the same **`brainstorm-ideas-new`**, **`identify-assumptions-new`**, and **`prioritize-assumptions`** components across different product types by simply adjusting the input context. ## Tailoring Discovery for SaaS Products When working with SaaS web applications, you typically have access to usage analytics, subscription data, and defined onboarding funnels. You can inject these signals to steer the discovery process toward multi-tenant architecture, API integrations, and pricing validation. ### Setting the Discovery Context for Existing SaaS For existing SaaS products, begin the **`/discover`** command by specifying continuous discovery signals. The skill will route you through the **existing-product** branch, utilizing [`pm-product-discovery/skills/brainstorm-ideas-existing/SKILL.md`](https://github.com/phuryn/pm-skills/blob/main/pm-product-discovery/skills/brainstorm-ideas-existing/SKILL.md) and [`pm-product-discovery/skills/identify-assumptions-existing/SKILL.md`](https://github.com/phuryn/pm-skills/blob/main/pm-product-discovery/skills/identify-assumptions-existing/SKILL.md). Input contextual details that emphasize: - **Multi-tenant architecture** constraints - **Integration APIs** and third-party dependencies - **Pricing tier** limitations and upgrade paths - **Data-export** compliance requirements ### Identifying SaaS-Specific Assumptions The **`identify-assumptions-existing`** skill categorizes risks into **Value, Usability, Feasibility, and Viability**. For SaaS, frame assumptions around enterprise adoption patterns, such as: *"Will mid-market customers adopt a usage-based API pricing model?"* This falls under **Viability** and **Value** categories. When using **`prioritize-assumptions`** (defined in [`pm-product-discovery/skills/prioritize-assumptions/SKILL.md`](https://github.com/phuryn/pm-skills/blob/main/pm-product-discovery/skills/prioritize-assumptions/SKILL.md)), map assumptions to **ARR growth**, **churn reduction**, or **average revenue per user (ARPU)**. These metrics align with the **Impact × Risk** matrix used to highlight "leap-of-faith" assumptions specific to subscription business models. ### Designing SaaS Experiments Invoke **`brainstorm-experiments-existing`** (from [`pm-product-discovery/skills/brainstorm-experiments-existing/SKILL.md`](https://github.com/phuryn/pm-skills/blob/main/pm-product-discovery/skills/brainstorm-experiments-existing/SKILL.md)) with prompts that reference billing validation or integration testing. For example: > *"Design an experiment to test whether adding a self-service data export feature reduces churn for enterprise SaaS customers."* The skill will suggest appropriate validation methods—such as A/B testing or concierge MVPs—that respect SaaS deployment constraints. ## Tailoring Discovery for Mobile Apps Mobile applications introduce distinct constraints including platform-specific distribution (App Store, Play Store), offline functionality requirements, and battery consumption concerns. You can tailor the same discovery skills by injecting mobile-specific context signals. ### Mobile Context Signals and Discovery Stage When initiating **`/discover`** for mobile, specify **new product** or **existing product** boundaries while emphasizing: - **App-store review** cycles and approval risks - **Push-notification** limits and permissions - **Install-to-signup** conversion metrics - **Platform-specific** iOS/Android constraints These signals direct the workflow in [`pm-product-discovery/skills/identify-assumptions-new/SKILL.md`](https://github.com/phuryn/pm-skills/blob/main/pm-product-discovery/skills/identify-assumptions-new/SKILL.md) or [`pm-product-discovery/skills/identify-assumptions-existing/SKILL.md`](https://github.com/phuryn/pm-skills/blob/main/pm-product-discovery/skills/identify-assumptions-existing/SKILL.md) to surface mobile-centric risks. ### Mobile-First Ideation Techniques Use **`brainstorm-ideas-new`** or **`brainstorm-ideas-existing`** (from [`pm-product-discovery/skills/brainstorm-ideas-new/SKILL.md`](https://github.com/phuryn/pm-skills/blob/main/pm-product-discovery/skills/brainstorm-ideas-new/SKILL.md) and [`pm-product-discovery/skills/brainstorm-ideas-existing/SKILL.md`](https://github.com/phuryn/pm-skills/blob/main/pm-product-discovery/skills/brainstorm-ideas-existing/SKILL.md)) with explicit mobile framing: > *"Generate ideas for a mobile-first habit tracking app that must support offline mode and native iOS gestures."* The skill generates ideas from PM, Designer, and Engineer perspectives while respecting the mobile constraints, surfacing concepts around **offline support**, **native UI gestures**, and **battery optimization**. ### Platform-Specific Risk Categories Mobile assumptions often involve **Go-to-Market** risks (for new products) or **Usability** challenges (for existing products). Frame assumptions such as: *"Will users enable push notifications during the first 7 days on iOS?"* This maps to **Usability** and **Value** (retention) categories. When calling **`prioritize-assumptions`**, use mobile-specific impact metrics like **DAU/MAU**, **30-day retention**, or **lifetime value (LTV)** instead of SaaS revenue metrics. ### Mobile Experiment Design For **`brainstorm-experiments-new`** or **`brainstorm-experiments-existing`**, include mobile-specific constraints in your prompts: > *"Design an experiment to test personalized push-notification timing for increasing 30-day retention on iOS."* The skill will suggest experiments such as landing-page pre-launch tests or in-app prototypes that account for App Store approval timelines and platform-specific user behaviors. ## Practical Command Examples for Product-Specific Workflows Below are concrete command sequences demonstrating how to steer the discovery flow for each product type within the **pm-skills** workspace. ### SaaS Existing Feature Expansion ```text /discover # Response: Existing product # Context: "Advanced reporting dashboard for B2B SaaS analytics platform" /brainstorm-ideas-existing # Select ideas relevant to API integrations and data visualization /identify-assumptions-existing # Focus on assumptions around enterprise adoption and data security /prioritize-assumptions # Map to ARR impact and implementation risk /brainstorm-experiments-existing # Design A/B test for dashboard UI changes ``` ### Mobile New Product Discovery ```text /discover # Response: New product # Context: "On-the-go habit tracking mobile app for iOS and Android" /brainstorm-ideas-new # Emphasize offline-first architecture and native gestures /identify-assumptions-new # Include Go-to-Market assumptions about App Store optimization /prioritize-assumptions # Map to DAU/MAU impact and technical feasibility /brainstorm-experiments-new # Design fake-door test and in-app prototype sequence ``` Both flows generate a markdown **Discovery Plan** that aggregates ideas, assumptions, experiments, and timelines into a single document defined in [`pm-product-discovery/commands/discover.md`](https://github.com/phuryn/pm-skills/blob/main/pm-product-discovery/commands/discover.md). ## Extending the Discovery Plan for Platform Deliverables The final discovery plan is a plain markdown file that you can customize post-generation to reflect product-type specific deliverables. For **SaaS products**, append sections for: - **Integration testing** checklists - **Billing validation** workflows - **Multi-tenant security** audits For **mobile apps**, insert: - **Store-listing optimization** checklists - **Crash-report monitoring** notes - **Platform-specific approval** timelines Because the plan is a standard markdown file, you can version-control it or pipe it into downstream tools in the `pm-skills` repository, such as the **PRD-generator** in the *pm-product-strategy* package, without modifying the underlying skill code. ## Summary - **pm-product-discovery** uses agnostic skills that accept contextual prompts, allowing you to tailor the workflow for SaaS, mobile, or other product types. - Provide **product-type context** at the start of each step (`/discover`, `brainstorm-ideas`, `identify-assumptions`) to steer the outputs toward platform-specific constraints. - Use **SaaS-specific metrics** (ARR, churn, ARPU) when prioritizing assumptions, and **mobile-specific metrics** (DAU/MAU, retention, LTV) for app products. - Reference the skill files in `pm-product-discovery/skills/`—including [`brainstorm-ideas-new/SKILL.md`](https://github.com/phuryn/pm-skills/blob/main/brainstorm-ideas-new/SKILL.md), [`identify-assumptions-existing/SKILL.md`](https://github.com/phuryn/pm-skills/blob/main/identify-assumptions-existing/SKILL.md), and [`prioritize-assumptions/SKILL.md`](https://github.com/phuryn/pm-skills/blob/main/prioritize-assumptions/SKILL.md)—to understand how context injection modifies the discovery outputs. - Customize the final markdown **Discovery Plan** with platform-specific deliverables such as integration testing (SaaS) or store-listing optimization (mobile). ## Frequently Asked Questions ### Can I use pm-product-discovery for hardware or IoT products? Yes. The framework is deliberately agnostic. You can tailor pm-product-discovery for hardware or IoT products by supplying appropriate context during the **`/discover`** command and subsequent skills. Focus on hardware-specific assumptions around manufacturing feasibility, supply chain risks, and firmware update mechanisms when using **`identify-assumptions-new`** or **`identify-assumptions-existing`**. ### How do I switch between existing and new product discovery modes? The **`/discover`** command (defined in [`pm-product-discovery/commands/discover.md`](https://github.com/phuryn/pm-skills/blob/main/pm-product-discovery/commands/discover.md)) prompts you to specify whether you are exploring an **existing product** or **new product** at the outset. This selection determines whether the workflow utilizes `brainstorm-ideas-existing` and `identify-assumptions-existing` (for continuous discovery) or their `*-new` counterparts (for initial validation). ### What metrics should I use when prioritizing assumptions for marketplace products? For marketplace products (a hybrid of SaaS and mobile considerations), use **`prioritize-assumptions`** with metrics that capture **both sides of the market**, such as **liquidity** (successful matches), **take rate**, and **network effects velocity**. Include these specific metrics in your context when calling the skill to ensure the **Impact × Risk** matrix reflects marketplace dynamics rather than single-sided user metrics. ### Can I combine multiple product types in one discovery workflow? While the skills are designed to handle single product-type contexts, you can run parallel discovery tracks by initiating separate **`/discover`** sessions for each platform (e.g., one for your SaaS dashboard and one for your companion mobile app). Alternatively, provide hybrid context during **`brainstorm-ideas-new`** to generate cross-platform ideas, then use **`prioritize-assumptions`** to resolve conflicts between web and mobile constraints.