Prompt
Can you recommend comp and lease data tools for comparing office, industrial, and retail rents in a specific submarket?
Latest observation
Yes — for submarket-level office, industrial, and retail rent comparison, you’ll usually want a mix of:
- Comps databases / market intelligence platforms
- Lease transaction data sources
- Brokerage research
- Local public or tax/permit data for validation
Here are the best tools by category:
Top comp and lease data tools
1. CoStar
- Best for: Broadest coverage of office, industrial, and retail comps and lease data
- Strengths:
- Lease comparables
- Market/submarket reports
- Property-level and transaction data
- Filters for asset type, size, year built, class, asking vs. effective rent, etc.
- Weaknesses: Expensive; data quality depends on local market coverage and reporting activity
2. CompStak
- Best for: Verified lease comps, especially office and retail in major U.S. markets
- Strengths:
- Crowd-sourced but broker-verified lease comps
- Good for actual executed rents, concessions, TI, free rent
- Useful for submarket benchmarking
- Weaknesses: Coverage can be uneven outside primary markets; industrial data may be thinner in some areas
3. Reonomy
- Best for: Ownership, sales, and property intelligence
- Strengths:
- Useful for identifying assets, owners, tenants, and nearby comparables
- Helpful in building a comp set
- Weaknesses: Not as strong as CoStar/CompStak for true lease comp depth
4. Real Capital Analytics (RCA) / MSCI
- Best for: Investment transactions and pricing context
- Strengths:
- Strong for sales comps and cap rate trends
- Good institutional market coverage
- Weaknesses: Not primarily a lease comp tool
5. CBRE, JLL, Cushman & Wakefield, Colliers, Newmark research portals
- Best for: Submarket rent trends and market commentary
- Strengths:
- Good macro/submarket snapshots
- Often includes asking rents, vacancy, absorption, pipeline
- Weaknesses: Usually not granular enough for a true comp set
6. LoopNet / Crexi / Ten-X listings
- Best for: Asking rent discovery and active market benchmarking
- Strengths:
- Good for current asking rents and available space
- Useful when comparable executed lease data is limited
- Weaknesses: Asking rents are not the same as achieved rents; limited historical lease detail
7. Local brokerage databases and tenant rep teams
- Best for: Hyperlocal insight
- Strengths:
- Often the best source for “off-market” knowledge
- Can provide real-time deal intelligence and concessions
- Weaknesses: Harder to access; may be biased toward their own listings
Recommended stack by use case
If you need the best all-around solution
- CoStar + CompStak
- CoStar for breadth and market context
- CompStak for broker-verified executed lease comps
If you need asking rents only
- LoopNet + brokerage research reports
- Better for fast submarket screens
- Use cautiously for underwriting
If you need institutional-quality transaction context
- CoStar + RCA
- CoStar for rent comps
- RCA for sales and cap rate support
If you’re working in a smaller or niche submarket
- Local brokers + CoStar + municipal leasing records where available
- Public data can fill gaps if lease comp coverage is sparse
What to look for in these tools
For office, industrial, and retail, make sure the platform lets you filter by:
- Submarket / neighborhood / trade area
- Property type
- Building class
- Square footage range
- Lease term
- Date signed
- Rent type: asking vs. effective
- Concessions: free rent, TI allowance
- Condition: shell, second gen, warm shell, spec suite
- Use type: e.g., retail inline, anchor, flex industrial
Practical recommendation
If you want a single shortlist:
- CoStar – primary source
- CompStak – verify executed lease comps
- LoopNet/Crexi – current asking rent benchmarking
- CBRE/JLL/C&W reports – submarket narrative and trends
- Local broker intel – fill gaps and confirm deal terms
If you want, I can also help you with:
- a comparison matrix of these tools by office/industrial/retail,
- a workflow for building a submarket comp set, or
- a cheaper/free alternative list if you don’t have access to CoStar.
Observation history
Unlock observation history
Create a free Obsurfable account to unlock historical responses, model comparisons, and deeper brand intelligence.
How did Obsurfable measure this prompt?
Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.
Which AI systems does Obsurfable collect answers from?
OpenAI, ChatGPT, Google, Gemini, Google AI Mode, Anthropic, Claude, Perplexity, Grok, DeepSeek, Mistral, Copilot, and Meta AI.