How to determine total feature costs

As a product owner, estimating the total cost of a feature goes far beyond counting developer hours. Understanding the full picture — both during development and post-launch — helps you make better decisions about what to build, when to build it, and how to maintain it.

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The four types of feature costs

In a recent Triggre webinar, we introduced a simple way to evaluate feature costs using a cost quadrant based on two axes:

• Internal vs. external costs

• Development time vs. production time

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This creates four key types of costs to consider:

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1. Internal development costs

These include everything your team does to create the feature: designing, building, and testing. It's typically the most visible cost and easiest to estimate because it directly relates to the time your team will spend. ‍

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2. External development costs

These are the third-party services or tools you need during the development phase. Examples include cloud hosting, software licenses, or external APIs. These costs often grow with the number of developers or the size of your testing environment. ‍

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3. External production costs

Once your feature is live, these costs start to accumulate with usage. Think of API call fees, hosting charges, or any licenses that scale with your user base. The more your feature is used, the higher these costs can go.

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4. Internal production costs

Often underestimated, this category covers ongoing maintenance by your team. Technical debt is a major factor here — code that ages over time, requires updates, or breaks when surrounding systems change. You also need to think about support, security updates, and integrating updates from third-party services.

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Constant vs. dynamic costs

When evaluating a feature’s cost, it’s also useful to identify which costs are static and which will grow over time.

• Dynamic costs (top of the quadrant) scale with developers or users. For example, the more users interact with a paid API, the more it costs.  
• Constant costs (bottom of the quadrant) are typically tied to team size and effort. Maintenance and updates often fall here and stay relatively stable regardless of how many users you have.

This distinction helps you forecast costs more accurately, especially as your user base grows.

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Comparing two real-life examples

Let’s break down two different features using this framework: a visual dashboard and a generative AI summary tool.

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Feature A: an extensive visual dashboard

• Development costs (both external and internal) make up roughly 25%. Your team implements and tests a front-end dashboard using a visual library.

• External production costs remain relatively low. You might need a license for the visual library, which could account for 10% to the total.

• The main cost driver here is internal production. Visual libraries often need to be updated to stay compatible with modern browsers. Your team will likely need to revisit this code regularly.

This feature is a good example of one that scales well. Once it’s built, adding new users doesn’t increase costs significantly. But it does require more ongoing attention from your team.

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Feature B: a generative AI summary feature

• Like Feature A, development time represents about 20% of the total cost.

• However, external development and production costs are much higher. You’ll be calling a paid AI API, which charges based on usage. Testing and validating outputs during development can get expensive.

• In production, these costs scale directly with user activity. The more summaries your users generate, the more you’ll pay.

• Internal production costs are lower than for Feature A. Unless the API changes or requires an update, ongoing maintenance is minimal.

This feature is cost-effective when used by a small group of users. But if usage grows rapidly, so do the costs — particularly the dynamic, external ones.

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Choosing the right feature for your product

Neither of the examples above is “better.” They simply have different cost profiles. What matters is choosing the right feature for your goals and constraints.

Here are a few key takeaways when planning new features:

• Map each feature into the quadrant. Where do most of the costs fall?

• Identify dynamic costs. Will your expenses rise with user growth?

• Don’t forget maintenance. Internal production costs like technical debt can quietly accumulate over time.

• Use cost profiles to guide your roadmap. Some features are a better fit for early-stage products; others work best when you’ve scaled.

You don’t need perfect calculations. A rough breakdown of cost types is enough to avoid surprises and make well-informed decisions.

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Takeaway

To determine a feature’s total cost, don’t just look at build time. Consider:

• Internal vs. external costs

• Development vs. production phase

• Whether your costs are constant or will scale with users

Using a quadrant approach helps clarify where the real costs lie, especially hidden ones like maintenance and technical debt. Thinking this through before development helps ensure your product stays sustainable as it grows.