Cost per Feature Calculator

Product backlogs fill with requests; feature ROI asks whether build cost is justified by measurable revenue lift, conversion improvement, or retention — modelled here as monthly uplift per affected user over a period.

Positive ROI on direct uplift does not guarantee strategic fit — but negative direct ROI should trigger hard questions.

Backlogs fill with requests; feature ROI asks whether build cost is justified by measurable revenue lift, conversion, or retention modelled as monthly uplift per user.

Positive direct ROI does not guarantee strategic fit — but weak direct ROI should trigger hard questions before engineering starts. If the question is roadmap order rather than payback, use the RICE prioritisation calculator.

Use with roi calculator, build vs buy software calculator, and RICE prioritisation calculator for larger bets.

Build cost £18,000. Expected revenue lift £2.50 per user per month for 1,200 users over 12 months = £36,000 gross uplift.

Net value £18,000 before ongoing maintenance. ROI = 100% on the initial build cost in this simplified model.

Add support burden and opportunity cost of engineering time — ROI falls if lift is optimistic or delayed.

Build cost £18,000. Lift £2.50/user/month for 1,200 users over 12 months = £36,000 gross uplift.

Net value £18,000 before maintenance. ROI = 100% on build cost in this simplified model.

If only 600 users adopt, revenue lift halves and ROI falls to 0% — adoption assumptions dominate.

Platform work, compliance, and retention features may have indirect value. Label assumptions when uplift is speculative.

Compare ROI across features with similar user reach — small lifts at huge user counts can beat large lifts on niches.

Large engineering bets competing with core roadmap should show ROI or explicit strategic rationale before sprint allocation.

Sales-promised features with unclear adoption need ROI gates — otherwise engineering becomes a sales support function at negative return.

Platform work that could be bought off-the-shelf should run through build vs buy software calculator before custom build commits.

Counting all users as affected when only a segment will adopt. Ignoring maintenance and infra cost after launch.

Measuring lift before stable usage — run the period long enough to see retention effects.

Counting entire team salary in build cost for a 2-week sprint — allocate actual sprint cost, not annual payroll.

Attributing retention lift without holdout — run ROI on measurable upsell first, retention second.

Shipping because “strategic” without documenting non-financial success criteria — document or defer.

Expected revenue lift = users affected × monthly lift × months. ROI % = (lift − build cost) ÷ build cost × 100.

Maintenance and support burden after launch are not automatic — add to build cost for conservative ROI.

Indirect benefits (retention, brand) can justify build with weak direct ROI — label assumptions explicitly.

Validate willingness to pay with design partners who match target segment — not friendly beta users only.

Ship MVP to a subset before full build cost — measure adoption before phase two funding.

Price as add-on so revenue lift appears explicitly in ARPU rather than blended averages.

Bundle with tier upgrade so expansion revenue captures value from the feature.

Kill fast when adoption metrics miss agreed gates at 90 days — sunk cost is not a reason to continue.

Set adoption floor (e.g. 40% of target users in 90 days) and ROI floor before build — kill or pivot if gates miss, even after sunk cost.

Add 6–12 months maintenance to build cost for conservative ROI on platforms with compliance or API churn.

Compare build ROI to build vs buy software calculator if the feature is a commodity capability.

Set adoption gates at 90 days post-launch — kill or pivot if gates miss.

Compare build ROI to build vs buy software calculator for commodity capabilities.

Add maintenance to build cost for honest second-year ROI.

Rank features by contribution per engineering month — a £200,000 expected uplift over 4 months beats £250,000 over 12 months for the same team size even if absolute ROI is higher on the slower bet.

Include opportunity cost: building a nice-to-have delays the feature that improves retention 1% — run churn impact calculator on retention-led bets before cosmetic roadmap items.

Define minimum viable scope and kill criteria before sprint start — scope expansion is the main driver of negative feature ROI in internal tools and customer-facing alike.

Features with low adoption still incur support and security cost — retirement can improve margin faster than another launch; log sunsetting savings in the same ROI tracker as new builds.

Before building v2 of a weak feature, compare fix cost to expected uplift — sometimes removal plus a simpler workflow wins.

This page should target cost per feature calculator, feature ROI calculator, software feature payback, product feature ROI, and product prioritisation calculator searches.

It compares one feature's build cost with expected revenue lift from affected users over a measurement period. It does not estimate engineering salary from team size, allocate sprint capacity, model maintenance automatically, score qualitative strategy, calculate retention lift from cohorts, or replace a full roadmap prioritisation system.