Plan home renovation budgets with ROI estimates. Part of the DevTools Surf developer suite. Browse more tools in the Real Estate & Home collection.
Use Cases
Plan a bathroom or kitchen renovation budget by room and trade category (demo, framing, plumbing, electrical, finishes).
Calculate break-even ROI for a renovation before deciding whether to upgrade to sell or move.
Track actual vs. budgeted costs as a renovation progresses to manage scope creep.
Compare DIY-eligible tasks vs. contractor-required tasks to reduce total spend.
Tips
Add a 15-20% contingency buffer on top of contractor quotes — renovation projects exceed initial quotes 80% of the time according to contractor industry surveys.
Get three quotes minimum for structural or electrical work — bids for the same scope can vary 40-60% between contractors.
Budget permit costs separately — permits add 1-3% to project cost but are required for structural, electrical, plumbing, and HVAC work in most municipalities.
Fun Facts
Kitchen renovations have the highest average ROI of any renovation type at 62-81% (cost recouped at resale), according to Remodeling Magazine's 2023 Cost vs. Value Report.
The average US kitchen renovation costs $26,000-80,000 depending on scope. The main cost driver is cabinet replacement, which alone can cost $8,000-30,000 installed.
Homeowners spend an estimated $472 billion annually on renovations and repairs in the US (Harvard JCHS, 2023) — more than the GDP of many countries.
FAQ
Does it include labor costs?
Yes — each category includes typical labor cost ranges as a percentage of materials. You can override with your own quotes to get a project-specific total.
How does it estimate permit costs?
Permit cost is estimated at 1-2% of total project cost, which matches US national averages. Enter your municipality's actual permit fee if known for exact figures.
Does it calculate ROI?
Yes — it shows the national average cost recovery percentage for common renovation types (kitchen, bathroom, deck, roof) based on Remodeling Magazine's annual Cost vs. Value data.
