Reflections on Product Prioritization Strategies

From an AI Product Management Course A journey of understanding, evaluating, and gaining deeper awareness of what truly makes a difference in the world of products.

When working on products in a constantly changing and complex environment, the decision of “What should we build first?” becomes a strategic one that shouldn’t be taken lightly. Prioritization isn’t just about sorting ideas — it’s an art and a mindset. It’s a balance between value and effort, between what the customer needs and what the team can deliver.

In this post, I share the strategies I learned in the course, as reflections aimed at gaining a deeper understanding and reinforcing what I have studied.

1. Impact vs. Effort Matrix

This matrix categorizes ideas into four quadrants based on:

• Impact: How much of a difference will this idea make?
• Effort: How much time and resources will it require?

Result: A clear visualization that distinguishes quick wins from large or draining projects.

Reflections

• Big wins aren’t always the best options.
• Great, low-effort ideas can be overlooked while focusing on more complex tasks.
• “Impact” should be evaluated from multiple perspectives: customer, revenue, team.
• “Effort” isn’t just time — it includes resources, budget, skills, and even mental pressure.

2. Kano Model

Features are classified into:

• Basic: Their absence causes dissatisfaction.
• Performance: The better they are, the higher the satisfaction.
• Delighters: Unexpected but pleasantly surprise the customer.

There are also neutral or even negative features in some contexts.

Reflections

• What we consider “innovative” might mean nothing to the user.
• The timing and context of a feature can be more important than the feature itself.
• Communicating with customers and analyzing their experience reveals what truly satisfies them.

3. RICE Framework (Reach, Impact, Confidence, Effort)

A framework that scores each idea across four criteria:

• Reach: How many users will it affect?
• Impact: How strong will the effect be?
• Confidence: How certain am I about my assumptions?
• Effort: What will it cost to execute?

Reflections

• “Reach” isn’t just about numbers — it’s about real influence.
• Confidence needs data, not just gut feeling.
• RICE is a great way to stay neutral and reduce bias.

4. Weighted Scoring

A tool based on setting multiple criteria (e.g., revenue, customer satisfaction), assigning weights to each, and scoring each idea accordingly.

Reflections

• Weight distribution reveals what we truly value.
• Team involvement in setting weights is essential to avoid bias.
• Surprises are a natural part of this exercise — and can lead to better decisions.

5. SWOT and PEST Analysis

• SWOT: Internal (Strengths & Weaknesses) and external (Opportunities & Threats) analysis.
• PEST: Political, Economic, Social, and Technological factor analysis.

Reflections

• Focusing only inward weakens strategic vision.
• External environments can completely reshape strategy.
• These analyses aren’t one-time tasks — they’re tools to revisit regularly.

6. Product Thinking in Phases

Breaking product development into phases:

• MVP (Minimum Viable Product): The essentials.
• Enhancements: What improves the experience.
• Differentiation and Scaling: What sets the product apart and drives growth.

Reflections

• Striving for perfection early on does more harm than good.
• Time and resources define what’s realistic to launch.
• Growth isn’t an emotional decision — it’s a strategic one.

📍 Also Read: The previous part of This Series