REAL ESTATE & PRIVATE EQUITY

Real Estate Financing & Private Equity Study

Capture how institutional investors, fund managers, and asset allocators evaluate deal structures, compare financing instruments, and weigh risk-return thresholds across property classes, so you can sharpen acquisition criteria, benchmark capital deployment, and refine positioning across investor segments.

Multi-Market Sample
Institutional Investors (Fund Managers, Asset Allocators)
15-20 min
Talk to a Survey Consultant
Deal Conversion & Pipeline FrictionIdentify where investor commitment stalls across financing stages and structures.
Capital Allocation & Risk ThresholdsBenchmark return expectations, leverage tolerance, and asset class prioritisation signals.
TRUSTED BY LEADING BRANDS
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CONTEXT & RELEVANCE

Why run this survey now

Most real estate capital allocators don't lose deals purely on return projections. They lose them due to misread risk appetite, opaque LP expectations, misaligned debt structures, sponsor track record gaps, and shifting asset class conviction, none of which fully show up in deal memos or fund performance reports.

If you are...

  • PE fund competing for LP capital
  • Debt fund vs equity fund positioning
  • Real estate investment head
  • Capital markets or IR lead
  • Asset management strategy team

You're likely facing...

  • LP conviction gaps: debt vs equity
  • Deal drop-offs at credit structuring
  • PE funds = return-focused/illiquid perception
  • Sponsor credibility vs yield tension
  • Refinancing triggers and exit misalignment

This will help answer...

  • LP preference drivers beyond IRR
  • Financing drop-off by deal stage
  • Debt vs equity allocation preference
  • Acceptable leverage and fee structures
  • Refinancing and reinvestment switch triggers

RESEARCH THEMES

What This Survey Investigates

Eight interconnected research themes that map the complete real estate financing journey from capital sourcing to portfolio exit.

TENETS 01

Capital Sourcing

  • Preferred debt-equity mix by asset class
  • Primary lender relationships, bank vs. NBFC
TENETS 02

Deal Origination

  • Off-market vs. brokered deal flow
  • Sponsor network, proprietary pipeline sources
TENETS 03

Underwriting Standards

  • LTV thresholds, DSCR floor by sector
  • Stress-test assumptions, vacancy rate inputs
TENETS 04

Diligence Friction

  • Title, legal, and environmental clearance delays
  • Documentation gaps slowing credit approval
TENETS 05

Pricing & Returns

  • IRR hurdles, preferred return waterfall structure
  • Spread expectations across risk tiers
TENETS 06

Portfolio & Risk

  • Concentration limits by geography and sector
  • Covenant monitoring, breach escalation protocols
TENETS 07

LP & Sponsor Trust

  • Reporting cadence, NAV transparency expectations
  • Track record signals driving re-up decisions
TENETS 08

Exit & Recycling

  • Preferred exit routes by asset type
  • Hold period discipline, capital recycling timelines

SAMPLING STRATEGY

Tell us about your ideal sample

Help us understand your target respondent profile. Select what applies, we'll design the optimal sample plan based on your inputs.

Sample size
How many respondents do you need?
Not Selected
Target audience
Who should we survey?
Not Selected
Region
Which regions should we cover?
Not Selected
Segments
How should we slice the data?
Not Selected
Discuss sample plan

METHODOLOGY

Survey approach

For the Real Estate Financing & Private Equity Study, we recommend a quant-first design with flexible data-collection modes to balance reach, depth, and verification across investor and lender segments.

PRIMARY
Online web surveySelf-administered survey shared via email / panels to capture structured responses at scale.
Best for
1
Ranking preferred debt and equity financing structures.
2
Benchmarking LTV thresholds across asset classes.
3
Comparing segments by fund size, geography, and strategy.
Deliverables
Financing preference matrix
LTV benchmark bands
Segment comparison report
OPTIONAL
CATI (phone survey)Interviewer-led telephone interviews to reach owners who are harder to get online.
Best for
1
Regional developers with limited digital survey participation.
2
Quick coverage across multiple city-tier markets.
Deliverables
Tier-city coverage data
Call-log diagnostics
SELECTIVE
Face-to-faceOn-ground surveys or interviews in key industrial clusters or high-value cohorts.
Best for
1
Large-ticket PE investors requiring deal-level verification.
2
Senior lenders in relationship-driven financing ecosystems.
Deliverables
Deal-flow insights
Lender relationship maps
OPTIONAL
FGDs
Deliverables
Themes and quotes
Positioning feedback
OPTIONAL
Mixed surveysAny 4-mode combo Online + CATI + F2F + FGDs to maximise reach and representation. Mode-specific quotas and weighting for clean comparisons.
Deliverables
Unified dataset
Mode-adjusted analytics
Our Recommendation
Start with: Online web survey as the core quant layer, supported by CATI to capture regional developers and smaller fund managers with lower digital survey participation.
Consider adding: F2F interviews for large-ticket PE investors and senior lenders, plus a focused FGD layer to pressure-test risk appetite framing and refine capital deployment messaging.

EXECUTION PROCESS

How we execute

A proven 9-step process from scoping to delivery, designed to ensure quality, speed, and actionable insights.

Define the decision frame

Confirm objectives, target cohorts, geographies, and reporting cuts

Step 01

Define the decision frame

Design the instrument

Build workstream modules mapped to outputs (drivers, friction, pricing, retention, trust)

Step 02

Design the instrument

Lock the questionnaire

Review wording, sequencing, LOI, and competitive context; approve final version

Step 03

Lock the questionnaire

Pilot and calibrate

Test comprehension and ease quality; refine quotas and remove friction where needed

Step 04

Pilot and calibrate

Run fieldwork

Execute collection with active quota management and feasibility controls

Step 05

Run fieldwork

Assure quality

Dedupe, attention checks, speed/consistency rules, removals with audit trail

Step 06

Assure quality

Prepare the dataset

Clean data and deliver codebook/variable definitions

Step 07

Prepare the dataset

Analyse and synthesise

Driver ranking, leakage diagnostics, pricing bands, segment insights

Step 08

Analyse and synthesise

Deliver and align

Executive deck (optional dashboard) and leadership readout with recommendations

Step 09

Deliver and align

COMMERCIAL TERMS

Request a Commercial Proposal

Pricing depends on cohort, geography, sample size, approach, LOI, and deliverables. Configure below for an indicative estimate.

Select Sample Size

100

Geography

  • India
  • APAC (Singapore, Vietnam, Philippines, Indonesia, Australia, NZ, Japan, Thailand)
  • Middle East (UAE, KSA, Qatar, Bahrain, Oman, Kuwait)
  • North America (US, Canada)
  • Europe
  • Africa (South Africa, Kenya, Nigeria, Egypt, Algeria)
  • LATAM (Brazil, Mexico)

Select Mode of Survey

  • Online
  • CATI
  • Online FGD (5 people per FGD)
  • F2F

Length of the Interview

  • Select
  • 0-15
  • 16-20
  • 21-30
  • 31-45
  • 46-60
  • Custom
Indicative Estimate
  • Indian Rupee (INR)
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  • Zimbabwean Dollar (ZWL)

$0.00

+ applicable taxes

Proposal turnaround typically 24–48 hours

Note: Estimate is indicative only. Final pricing is subject to scope finalization after discovery call.

REFERENCE CASELETS

Reference

Real-world examples of survey work in the real estate financing and private equity space.

CASELET 1

Developer debt preference & lender selection behaviour (India)

CASELET 2

PE fund positioning & LP commitment signals (India)

Developer debt preference & lender selection behaviour (India)

OBJECTIVE

Map how mid-market residential developers and commercial asset developers shortlist and select between scheduled banks , housing finance companies , and alternative credit funds across construction and refinancing stages.

WHAT WE DID

Ran a structured quant survey across 180 developer finance heads in six cities, capturing lender shortlist criteria , loan-to-cost thresholds , draw-down flexibility requirements , and covenant tolerance by asset class and ticket size band.

DELIVERED

A lender preference map by developer segment, a pricing corridor for acceptable all-in cost of debt, a ranked friction list by lender type, and a segment framework separating rate-sensitive from covenant-sensitive borrower profiles.
CASELET 1

Developer debt preference & lender selection behaviour (India)

CASELET 2

PE fund positioning & LP commitment signals (India)

Developer debt preference & lender selection behaviour (India)

OBJECTIVE

Map how mid-market residential developers and commercial asset developers shortlist and select between scheduled banks , housing finance companies , and alternative credit funds across construction and refinancing stages.

WHAT WE DID

Ran a structured quant survey across 180 developer finance heads in six cities, capturing lender shortlist criteria , loan-to-cost thresholds , draw-down flexibility requirements , and covenant tolerance by asset class and ticket size band.

DELIVERED

A lender preference map by developer segment, a pricing corridor for acceptable all-in cost of debt, a ranked friction list by lender type, and a segment framework separating rate-sensitive from covenant-sensitive borrower profiles.

FREQUENTLY ASKED QUESTIONS

Common Questions

Answers to frequently asked questions about this survey mandate.

What decisions will this survey enable?

Who is the buyer vs who are the respondents?

Can we see differences between core equity sponsors, value-add private equity funds and debt fund managers?

How will you measure capital source preference beyond simple ratings?

Will the survey map the full deal financing journey and drop-offs?

Can this survey inform product and pricing strategy?

How will findings improve our capital raising and origination pipeline?

Still have questions?

Schedule a discovery call to discuss your specific needs and get a custom quote.

Book a Discovery Call