REAL ESTATE & INVESTMENT

Real Estate vs Financial Asset Investment Survey

Capture how retail and high-net-worth investors evaluate, compare, and choose between property and financial assets across liquidity, returns, and risk tolerance, so you can sharpen acquisition targeting, refine product positioning, and convert higher-intent investor segments.

Pan-India sample
Retail & HNI investors (Active Investment Decision-Makers)
15-20 min
Talk to a Survey Consultant
Allocation shifts & conversion triggersIdentify where investors redirect capital away from real estate toward financial assets.
Risk perception & segment trade-offsBenchmark liquidity sensitivity, return expectations, and risk thresholds across investor profiles.
TRUSTED BY LEADING BRANDS
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CONTEXT & RELEVANCE

Why run this survey now

Most investors don't lose capital allocation confidence purely on market volatility. They lose it due to shifting liquidity preferences, yield comparison gaps, risk perception mismatches, regulatory uncertainty, and portfolio rebalancing pressure, none of which fully show up in asset price indices or fund flow reports.

If you are...

  • Real estate fund or developer
  • Wealth management product head
  • Equity or fixed income platform
  • Portfolio strategy or allocation lead
  • Distribution or advisory growth team

You're likely facing...

  • Real estate vs equity allocation tension
  • Liquidity vs yield trade-off confusion
  • Property = safe/illiquid perception
  • Equities = volatile/accessible perception
  • Investor switching at rebalancing stage

This will help answer...

  • Preference drivers beyond headline returns
  • Allocation shift triggers by segment
  • Real estate vs financial asset splits
  • Yield expectations vs fee tolerance
  • Retention risk at portfolio review

RESEARCH THEMES

What This Survey Investigates

Eight interconnected research themes that map the complete investor journey from initial capital allocation to portfolio rebalancing.

TENETS 01

Allocation & Intent

  • Current portfolio split, real estate vs equities
  • Planned allocation shifts, next 12 months
TENETS 02

Preference Drivers

  • Primary return expectation by asset class
  • Liquidity vs capital appreciation trade-off
TENETS 03

Risk & Horizon

  • Investment horizon by asset category
  • Risk tolerance, illiquid vs liquid holdings
TENETS 04

Discovery & Influence

  • Information sources before investment decisions
  • Advisor reliance vs self-directed research
TENETS 05

Pricing & WTP

  • Ticket size thresholds by asset type
  • Willingness to pay for advisory or platform fees
TENETS 06

Tax & Regulation

  • Tax efficiency perception across asset classes
  • Regulatory clarity as a switching trigger
TENETS 07

Portfolio Friction

  • Exit barriers, real estate vs listed instruments
  • Rebalancing frequency and trigger events
TENETS 08

Emerging Formats

  • REIT, fractional ownership, and InvIT awareness
  • Adoption barriers for hybrid investment products

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?
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Target audience
Who should we survey?
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Region
Which regions should we cover?
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Segments
How should we slice the data?
Not Selected
Discuss sample plan

METHODOLOGY

Survey approach

For the Real Estate vs Financial Asset Investment Survey, we recommend a quant-first design with flexible data-collection modes to balance reach, depth, and verification across investor segments and asset classes.

PRIMARY
Online web surveySelf-administered survey shared via email / panels to capture structured responses at scale.
Best for
1
Ranking real estate vs financial asset preference by investor profile.
2
Quantifying allocation shifts across property, equities, and fixed income.
3
Comparing segments by income tier, city tier, and age cohort.
Deliverables
Asset preference ranking
Allocation shift matrix
Segment comparison bands
OPTIONAL
CATI (phone survey)Interviewer-led telephone interviews to reach owners who are harder to get online.
Best for
1
Older or low-digital investors holding physical property assets.
2
Quick coverage across Tier 2 and Tier 3 cities.
Deliverables
Investor coverage map
Call-log diagnostics
SELECTIVE
Face-to-faceOn-ground surveys or interviews in key industrial clusters or high-value cohorts.
Best for
1
HNI and UHNI cohorts with large multi-asset portfolios.
2
Verifying stated allocation intent against actual investment behaviour.
Deliverables
HNI portfolio profiles
Behavioural intent 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, covering retail and mass-affluent investors across digital panels, segmented by asset class preference and city tier.
Consider adding: CATI for low-digital and older investor cohorts in Tier 2 and Tier 3 cities, plus F2F interviews with HNI and UHNI segments to pressure-test allocation intent and validate portfolio behaviour.

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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  • Argentine Peso (ARS)
  • Australian Dollar (AUD)
  • Aruban Florin (AWG)
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  • Barbadian Dollar (BBD)
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  • Bulgarian Lev (BGN)
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  • Brunei Dollar (BND)
  • Bolivian Boliviano (BOB)
  • Brazilian Real (BRL)
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  • Botswana Pula (BWP)
  • Belarusian Ruble (BYN)
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  • Chinese Yuan (CNY)
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  • Euro (EUR)
  • Fijian Dollar (FJD)
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  • British Pound (GBP)
  • Georgian Lari (GEL)
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  • Lesotho Loti (LSL)
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  • Mongolian Tögrög (MNT)
  • Macanese Pataca (MOP)
  • Mauritian Rupee (MUR)
  • Maldivian Rufiyaa (MVR)
  • Malawian Kwacha (MWK)
  • Mexican Peso (MXN)
  • Malaysian Ringgit (MYR)
  • Mozambican Metical (MZN)
  • Namibian Dollar (NAD)
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  • Nicaraguan Córdoba (NIO)
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  • Tunisian Dinar (TND)
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  • New Taiwan Dollar (TWD)
  • Tanzanian Shilling (TZS)
  • Ukrainian Hryvnia (UAH)
  • Ugandan Shilling (UGX)
  • United States Dollar (USD)
  • Uruguayan Peso (UYU)
  • Uzbekistani Som (UZS)
  • Vietnamese Đồng (VND)
  • Vanuatu Vatu (VUV)
  • Samoan Tālā (WST)
  • Central African CFA Franc (XAF)
  • East Caribbean Dollar (XCD)
  • West African CFA franc (XOF)
  • CFP Franc (XPF)
  • Yemeni Rial (YER)
  • South African Rand (ZAR)
  • Zambian Kwacha (ZMW)
  • 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 personal investment and wealth allocation space.

CASELET 1

Residential property vs. mutual fund preference mapping (India)

CASELET 2

Gold & fixed deposit loyalty friction diagnosis (North India)

Residential property vs. mutual fund preference mapping (India)

OBJECTIVE

A mid-size wealth platform needed to isolate how salaried urban investors and self-employed HNIs weigh residential property against equity mutual funds at the point of a first major allocation decision, including the triggers that lock in commitment.

WHAT WE DID

Ran a structured quant survey across 600 respondents in 6 metros, capturing allocation triggers, risk tolerance thresholds, liquidity expectations, and influencer sources at each stage of the investment decision, segmented by income band and asset ownership history.

DELIVERED

A segment-level preference map by investor archetype, a ranked trigger hierarchy for first-time allocators, and a set of channel levers showing which touchpoints shift declared intent toward financial assets over physical property.
CASELET 1

Residential property vs. mutual fund preference mapping (India)

CASELET 2

Gold & fixed deposit loyalty friction diagnosis (North India)

Residential property vs. mutual fund preference mapping (India)

OBJECTIVE

A mid-size wealth platform needed to isolate how salaried urban investors and self-employed HNIs weigh residential property against equity mutual funds at the point of a first major allocation decision, including the triggers that lock in commitment.

WHAT WE DID

Ran a structured quant survey across 600 respondents in 6 metros, capturing allocation triggers, risk tolerance thresholds, liquidity expectations, and influencer sources at each stage of the investment decision, segmented by income band and asset ownership history.

DELIVERED

A segment-level preference map by investor archetype, a ranked trigger hierarchy for first-time allocators, and a set of channel levers showing which touchpoints shift declared intent toward financial assets over physical property.

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 equity-first investors, property-first investors and mixed-portfolio investors?

How will you measure asset allocation preference beyond simple ratings?

Will the survey map the full investment decision journey and drop-offs?

Can this survey inform product and pricing strategy?

How will findings improve our investor acquisition and retention strategy?

Still have questions?

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

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