In an ever-changing world of software development, the role of a product owner is constantly evolving, blending a mix of technical knowledge and strategic insight. As the tech landscape shifts, so do the skills required to be effective in this role. This article offers a skill map, thoughtfully designed for both established and aspiring software product owners. It outlines key areas of expertise necessary in today’s market, including development, emerging technologies, marketing, sales, product management, and project management.

This skill map serves as a practical guide, offering insight into the diverse and dynamic set of skills needed to succeed as a software product owner. Whether you’re looking to enhance your current skill set or starting your journey in software product ownership, this article aims to be a valuable resource in navigating the complexities of the field.

Development Link to heading

Low-code Builder (FlutterFlow) Link to heading

  • FF1. FlutterFlow Basics: Register, Setup, UI.
  • FF2. FlutterFlow Learning app mirroring.
  • FF3. FlutterFlow Advanced: Design, Integrations, Firebase.
  • FF4. FlutterFlow Own App Creation: Storyboard, GitHub, Marketplaces, Web.

Programming Language (Dart) Link to heading

  • PL1. Basics (in Dart): Data types, variables, conditional operators, loops, functions, optional types.
  • PL2. Advanced (in Dart): Object-oriented programming, error handling, asynchronous programming.

Code Quality Link to heading

  • CQ1. SOLID Principles and CLEAN Architecture.
  • CQ2. Architectural Patterns: MVC, MVP, MVVM, VIP architectures, Flux (Redux).
  • CQ3. Design Patterns (in Dart).

Development Orientations Link to heading

  • DO1. Web Development: HTML, CSS, JavaScript/TypeScript. Templating engines (Pug). Angular, VueJS, React Frameworks.
  • DO2. Native App Development: iOS - Objective-C/Swift, UIKit → SwiftUI. Android - Java/Kotlin.
  • DO3. Hybrid App Development: WebView and a native part.
  • DO4. Cross-Platform App Development: React Native, Flutter, Cordova, Ionic, Electron.
  • DO5. Backend: Lightweight - NodeJS, Flask. Heavyweight - Spring (Java), Django. Main frameworks - Yii, Flask, NodeJS, Django.
  • DO6. Backend: RESTful APIs and integrations.
  • DO7. Cloud Technologies and Microservices: Understanding cloud technologies, DevOps, and microservices environment.

Git and GitFlow Link to heading

  • GF1. Git Basics and Workflow: Branch management, pull requests.
  • GF2. GitHub, GitLab.
  • GF3. AWS, GCP, Azure DevOps.

Databases Link to heading

  • DB1. Database Fundamentals: SQL vs NoSQL.
  • DB2. Database Key Technologies - MongoDB, Redis, Elasticsearch, SQL databases (e.g., PostgreSQL).
  • DB3. Database Types of relationships between entities (1:1, 1:m, m:m).
  • DB4. Database Relationships: What is normalization, indexes.
  • DB5. Advanced SQL and Data Modeling: Advanced SQL querying, data modeling, and reporting.

Dependency Injection Link to heading

  • DI1. Service Locator - If it exists, return it; if not, create and return.
  • DI2. Dependency Injection.

CI/CD Link to heading

  • CI. Continuous Integration and Continuous Deployment.

Testing Link to heading

  • TE1. Testing Basics. Main types of testing.
  • TE2. Impact on the production process - TDD (Test-Driven Development).
  • TE3. Tests as an essential element of CI/CD and Testing Integration.

Algorithms Link to heading

  • AL. Algorithmic Complexity (Big O Notation).

Additional Technologies Link to heading

  • AT1. Reactive Programming and Functional Reactive Programming (see ReactiveX implementations).
  • AT2. DeepLink and URL Schemes.

New Technologies Link to heading

AI & Machine Learning Link to heading

  • AI1. Fundamentals of AI/ML: Understanding types of learning - supervised, unsupervised, reinforcement, and semi-supervised learning.
  • AI2. Common ML Algorithms: Common algorithms such as decision trees, k-nearest neighbors, neural networks, and support vector machines.
  • AI3. ML Model Evaluation and MLOps: Techniques to evaluate models, such as cross-validation and A/B testing specifically for ML models. Best practices for deploying, monitoring, and maintaining ML models in production.
  • AI4. Ethical Implications in AI/ML: Understanding the ethical considerations and potential biases in AI/ML.

Large Language Models Link to heading

  • LM1. Fundamentals of Large Language Models: The architecture of models like GPT-3, BERT, etc.
  • LM2. Applications of LLMs: Use cases in natural language processing, content generation, and more.
  • LM3. Customization of LLMs: How to fine-tune these models for specific tasks or industries.
  • LM4. Challenges and Limitations of LLMs: The limitations, including biases in the models and issues with interpretability.

Web3 Link to heading

  • WT1. Blockchain Basics: The concept of blockchain, distributed ledgers, and how they work.
  • WT2. Smart Contracts: Write, deploy, and interact with smart contracts.
  • WT3. Decentralized Applications (DApps): Architecture and development of DApps.
  • WT4. Cryptocurrencies and Tokens: The role of digital assets within Web3.
  • WT5. Decentralized Finance (DeFi): Financial applications built on blockchain.

Continuous Learning and Adaptation Link to heading

  • CL1. Staying Updated with Tech Trends: Strategies for keeping up-to-date with emerging technologies.
  • CL2. Networking and Professional Development: Building a professional network and continuous skill enhancement.

Marketing Link to heading

  • MA1. Research: Market research, target audience identification, market size estimation, market development forecasts, user segmentation, feedback collection, and user problem descriptions.
  • MA2. Attracting users: Offline and online channels, channel effectiveness evaluation, referral programs, audience warming-up strategies.
  • MA3. Unique Selling Proposition (USP) - development and testing for different segments.
  • MA4. User onboarding: Design, first session planning, identifying key ‘aha’ moments, tutorials, and first-session lifetime value prediction.
  • MA5. Content: Content marketing strategies, community building, email marketing, notifications, article writing, webinars.
  • MA6. Retention and return strategies: Retention Rate, Churn Rate, NPS, Customer Lifetime Value, retention plateaus, and customer return methods.
  • MA7. Landing page: Strategies, including information layout, text writing, design, development, and testing.
  • MA8. Competitive analysis: Direct and indirect competitors, benchmarking, non-market advantages, unique selling points, and price analysis. Users’ feedback from competitors.

Sales Link to heading

  • SA1. Negotiation: Preparation, need identification, understanding decision backgrounds, managing complex negotiations.
  • SA2. Presentation: Competitive presentations tailored to customer needs, various presentation styles, audience attention maintenance, storytelling, and pitching.
  • SA3. Sales funnel: Construction and optimization.
  • SA4. Pricing: Freemium, Subscription Model, Licensing (One-time payment), Commission Model, Monetization through Advertising, Investments, Product Pricing Determination, Testing Business Models, Unit Economics.

Product Management Link to heading

Fundamentals Link to heading

  • FU1. Roles: Product Management: Growth Manager, Marketing Expert, Product Owner, Product Manager, Project Manager, Business Analyst, System Analyst, Developer, QA, Support. Team motivation.
  • FU2. Methodologies: Agile/Lean methodologies like Scrum, Kanban, Less, Lean startup canvas, and principles.

Design and User Experience Link to heading

  • DE1. User Experience (UX) and User Interface (UI): Design principles, including user-centered design, usability, accessibility, information architecture, and visual design elements like color theory, typography, and layout.
  • DE2. Prototyping and wireframing: Figma, FlatterFlow.
  • DE3. Conceptualization: Developing Minimum Viable Products.
  • DE4. User Research: Interviews, surveys, personas, journey mapping. Usability testing to gather user insights and validate designs.

Analytics Link to heading

  • AN1. Customer and User: Customer Journey Mapping and User Stories. User Stories, Use Cases, User Flows, system diagrams, wireframes.
  • AN2. Metrics: Add metric pyramid, identifying important product metrics, tracking, and interpreting results. LTV, CRR, NPS, CLV. Tableau, Power BI. Google Analytics, Facebook Pixel. Appsflyer, Appmetrica, Amplitude, Mixpanel, Firebase.
  • AN3. Tests: Tools for data collection and analysis, cohort analysis, A/B testing, split-testing, experiment preparation, and result interpretation.
  • AN4. Statistics: Statistical significance and mathematical statistics.
  • AN5. Economics: Product strategy planning, P&L (Profit and Loss) management, ROI calculation, customer economics, vision formulation, business model testing, and unit economics

Backlog Link to heading

  • BL1. Backlog: Prioritizing, versions, requirements.
  • BL2. Growth Hacking Theory.
  • BL3. Product Portfolio Decomposition.
  • BL4. Refactoring (and technical debt) - how much time to allocate, importance. Difference between refactoring and technical debt. Connection between the technical team and product team.

Project Management Link to heading

  • PJ1. Team Building: Finding, hiring, and managing a team. Assembling and managing effective development and product success team.
  • PJ2. Communication strategies: Effective negotiation and managing conflicts.
  • PJ3. Task setting: User story/Job story formats, task-linking to strategy through OKRs, cascading goals, and task formulation from goals.
  • PJ4. Reporting: Budgeting, forecasting and reporting by team members.
  • PJ5. Communication: Teams, clients, stakeholder expectation management, inter-departmental communication. Stakeholder management, partner negotiations and communication.
  • PJ6. Time management: Planning, including roadmaps, GIST, sprint planning.
  • PJ7. Risk management: Task prioritization models, value vs. cost analysis, and client value delivery.
  • PJ8. Documentation: Internal and external user purposes.
  • PJ9. Facilitation: Skills for different group sizes and distributed teams.