feature-investment-advisor

Feature prioritization by ROI evaluates proposed features using revenue impact, cost structure, payback period, and strategic value to output build, do-not-build, or validate recommendations. It classifies impact as direct monetization, retention, conversion, or expansion to adapt calculations accordingly for roadmap decisions.

Prioritize features by classifying their revenue impact as direct monetization, retention, conversion, or expansion, then adapt ROI calculations accordingly. This approach combines financial thresholds like ROI cutoffs and payback period with strategic considerations such as moat building or compliance to recommend build decisions.

Modeling revenue and payback period requires feature description, target segment, current MRR/ARR, ARPU, monthly churn, gross margin, estimated development cost, and ongoing COGS/OpEx. These inputs compute monthly and annual revenue, contribution margin, payback period, and ROI while flagging margin dilution or timing constraints.

You should not build a feature when cost analysis reveals margin dilution, ROI falls below financial thresholds, or payback period exceeds acceptable timing constraints. The analysis flags these financial risks while weighing strategic factors like platform enablement and compliance to ensure defensible build decisions.

Feature investment analysis works for SaaS products with high churn by factoring monthly churn into retention and conversion revenue calculations. It adapts ROI computations to assess whether retention-focused features generate sufficient contribution margin to justify development costs despite elevated churn rates.