What is a Comp Analysis?
A comp analysis (short for comparable market analysis, or CMA) is the process of evaluating recently sold or rented properties to determine the market value of a subject property. In real estate investing, comp analysis is how you calculate ARV for flips and ARR for rentals. It's the foundation of every investment decision: what to offer, what to spend on repairs, and what to price the deal at when marketing to buyers.
The term "running comps" means finding comparable properties and using their sale prices or rental rates to estimate what your subject property is worth. It's what appraisers do when a bank orders an appraisal, what real estate agents do when pricing a listing, and what investors do when evaluating a deal. The difference is that investors need to do it faster, with a focus on post-renovation value rather than current value.
Comp selection criteria
The quality of your comp analysis depends entirely on the quality of the comps you select. A great comp is one that is so similar to your subject property (in its post-renovation state) that minimal adjustments are needed. Here are the criteria, ranked by importance:
1. Location (most important)
Location is the single biggest factor in property value. Ideally, your comps are in the same subdivision or neighborhood, within 0.25-0.5 miles. You can extend to 1 mile in suburban areas. Never cross major boundaries (highways, railroad tracks, school district lines, city limits) unless absolutely necessary. Two houses that are 0.3 miles apart but in different school districts can have a $50,000 value difference.
2. Recency
Use sales from the last 6 months when possible. Extend to 12 months maximum if you need more comps. In rapidly changing markets, even 6-month-old data may need adjustment. Never use comps older than 12 months -- market conditions change too much. For rental comps, 3-6 months is ideal because rental rates shift faster than sale prices.
3. Physical characteristics
Match these features in order of impact on value:
- Property type: Single family to single family, condo to condo. Never compare different types.
- Square footage: Within 15-20% of the subject. A 2,400 sqft house is not comparable to a 1,400 sqft house even if everything else matches.
- Bedrooms and bathrooms: Within one bedroom and one bathroom. Bed/bath count affects value more than raw square footage in many markets.
- Year built: Within 10-15 years. A 1960s ranch and a 2010 contemporary have fundamentally different construction, layouts, and buyer appeal.
- Stories: One-story to one-story, two-story to two-story. These attract different buyer pools.
- Garage: Match garage count. A no-garage property compared to a two-car garage comp needs a significant adjustment.
4. Condition
Your comps should match the condition your property will be in after renovation. If you're planning a standard investor-grade rehab, use comps that sold in similar renovated condition. Don't use luxury flip comps if you're doing a basic rehab, and don't use as-is sales if you're planning a full renovation.
Making adjustments
No comp is a perfect match. Adjustments account for the differences between each comp and your subject property. Common adjustments include:
| Feature | Typical Adjustment | Notes |
|---|---|---|
| Square footage | $50-$120/sqft | Varies significantly by market and price point |
| Bedroom | $5,000-$15,000 | More impactful in family-oriented neighborhoods |
| Bathroom | $5,000-$10,000 | Full bath worth more than half bath |
| Garage | $10,000-$25,000 | Per garage bay, varies by market |
| Pool | $10,000-$30,000 | Can be negative in markets where pools are a liability |
| Lot size | $1,000-$5,000 per 1,000 sqft | Matters more in suburban/rural areas |
| Age | $500-$2,000 per year | Newer commands premium; diminishes past 20+ years |
| Condition | $10,000-$50,000+ | Biggest and hardest adjustment to quantify |
Adjustments are always made to the comp, not to the subject. If the comp has one more bedroom than your subject, adjust the comp's price downward. If the comp has less square footage, adjust upward. The goal is to answer: "What would this comp have sold for if it were identical to my subject property?"
MLS vs. public records data
There are two primary data sources for comps: MLS (Multiple Listing Service) and public records (county deed recordings, tax assessor data).
MLS data is the gold standard. It includes listing photos, days on market, sold price, listing price, agent remarks, and detailed property features. MLS data is the most current and most detailed. The limitation is access -- MLS data is controlled by local realtor associations and typically requires a real estate license or a subscription to a platform that licenses MLS data.
Public records data includes deed recordings (sale price, date, buyer, seller), tax assessments, property characteristics, and ownership history. It's available to everyone but lacks the rich detail of MLS data. Sale prices in public records can lag MLS by weeks or months, and some non-disclosure states don't record sale prices at all.
The best comp analysis uses both. MLS data gives you the most recent and detailed sold comps. Public records fill in gaps, provide ownership history, and work in areas where MLS coverage is thin.
Flip comps vs. rental comps
Flip comps (ARV comps) and rental comps (ARR comps) serve different purposes and come from different data sets:
- Flip comps are recently sold properties. You're looking at sold prices to determine what your property will sell for after renovation. Focus on renovated condition sales.
- Rental comps are actively listed or recently leased properties. You're looking at rental rates to determine what your property will rent for. Focus on similar condition and bedroom/bathroom configuration.
When marketing a wholesale deal, presenting both sets of comps lets buyers evaluate the deal through their preferred strategy. A flipper uses the sale comps. A landlord uses the rental comps. A BRRRR investor uses both. By providing both analyses, you maximize the number of buyers who can quickly see the value in your deal.
How Deal Run automates comp analysis
Deal Run's comp analysis pulls sale and rental comps automatically from MLS and public records data. Each comp is scored for similarity using AI that evaluates distance, size match, age match, condition level, and recency. Comps are displayed on an interactive map and in a sortable grid, with filters for distance, date range, property type, and price range. You can select or deselect individual comps to fine-tune your ARV and ARR estimates. Use our free ARV calculator for quick estimates without an account.