WOMEN'S BANKING & FINANCE

Women's Banking & Financial Inclusion Survey

Measure how women across income segments evaluate, compare, and choose formal banking, credit, and savings products, so you can sharpen acquisition targeting, fix conversion gaps, and refine channel positioning.

Pan-India sample
Women banking users (Primary Financial Decision-Makers)
15-20 min
Talk to a Survey Consultant
Onboarding friction & drop-offsIdentify where women applicants hesitate, stall, or exit before account activation.
Segment needs & product fitBenchmark credit, savings, and digital product preferences across income tiers.
TRUSTED BY LEADING BRANDS
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CONTEXT & RELEVANCE

Why run this survey now

Most financial institutions don't lose women customers purely on product gaps. They lose them due to trust deficits, misaligned onboarding journeys, income-documentation barriers, low financial literacy assumptions, and poorly segmented outreach, none of which fully show up in account activation reports or branch footfall data.

If you are...

  • Bank competing against fintech wallets
  • MFI or NBFC serving rural women
  • Women's product or credit head
  • Financial inclusion strategy lead
  • Distribution or channel growth head

You're likely facing...

  • Low activation: account to product
  • Trust gap: formal vs informal credit
  • Banks = safe/inaccessible perception
  • Fintechs = easy/untrustworthy perception
  • Segment drop-off: onboarding to usage

This will help answer...

  • Primary barriers to formal banking
  • Onboarding drop-off stage
  • Urban vs rural segment preference
  • Fee sensitivity and credit terms
  • Switching triggers and loyalty drivers

RESEARCH THEMES

What This Survey Investigates

Eight interconnected research themes that map the complete women's banking journey from account opening to long-term wealth accumulation.

TENETS 01

Discovery & Awareness

  • First financial institution approached
  • Awareness channels, peer referrals
TENETS 02

Preference Drivers

  • Product attributes ranked by women
  • Safety, convenience, gender-sensitivity
TENETS 03

Product & Access

  • Credit, savings, insurance uptake
  • Formal vs. informal financial tools
TENETS 04

Journey Friction

  • KYC, documentation drop-off points
  • Branch experience vs. digital gaps
TENETS 05

Pricing & WTP

  • Fee sensitivity across income segments
  • Willingness to pay for advisory services
TENETS 06

Usage & Stickiness

  • Transaction frequency, channel mix
  • Cross-product adoption within one bank
TENETS 07

Trust & Safety

  • Fraud concern, data privacy confidence
  • Gender-safe branch environment perception
TENETS 08

Competitive Positioning

  • Primary bank vs. challenger perception
  • Switching intent, retention triggers

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?
Not Selected
Segments
How should we slice the data?
Not Selected
Discuss sample plan

METHODOLOGY

Survey approach

For the Women's Banking and Financial Inclusion Survey, we recommend a quant-first design with flexible data-collection modes to balance reach, depth, and verification across urban, peri-urban, and rural women segments.

PRIMARY
Online web surveySelf-administered survey shared via email / panels to capture structured responses at scale.
Best for
1
Measuring product ownership and account usage rates.
2
Ranking barriers to formal banking adoption.
3
Comparing segments by income tier and geography.
Deliverables
Barrier ranking index
Segment gap matrix
Product penetration bands
OPTIONAL
CATI (phone survey)Interviewer-led telephone interviews to reach owners who are harder to get online.
Best for
1
Low-digital rural and peri-urban women respondents.
2
Quick coverage across dispersed district-level clusters.
Deliverables
Rural segment coverage
Call-log diagnostics
SELECTIVE
Face-to-faceOn-ground surveys or interviews in key industrial clusters or high-value cohorts.
Best for
1
Women-owned micro-enterprise cohorts needing contextual verification.
2
Self-help group clusters with low individual digital access.
Deliverables
Cluster insights
Rich journey maps
OPTIONAL
FGDs
Deliverables
Themes and quotes
Concept 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 low-digital rural and peri-urban women who fall outside panel reach.
Consider adding: F2F for self-help group clusters and women micro-enterprise cohorts, plus a focused FGD layer to pressure-test product messaging and identify norm-driven barriers to formal credit.

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)
  • United Arab Emirates Dirham (AED)
  • Afghan Afghani (AFN)
  • Albanian Lek (ALL)
  • Armenian Dram (AMD)
  • Netherlands Antillean Guilder (ANG)
  • Angolan Kwanza (AOA)
  • Argentine Peso (ARS)
  • Australian Dollar (AUD)
  • Aruban Florin (AWG)
  • Azerbaijani Manat (AZN)
  • Bosnia-Herzegovina Convertible Mark (BAM)
  • Barbadian Dollar (BBD)
  • Bangladeshi Taka (BDT)
  • Bulgarian Lev (BGN)
  • Bahraini Dinar (BHD)
  • Burundian Franc (BIF)
  • Bermudian Dollar (BMD)
  • Brunei Dollar (BND)
  • Bolivian Boliviano (BOB)
  • Brazilian Real (BRL)
  • Bahamian Dollar (BSD)
  • Bhutanese Ngultrum (BTN)
  • Botswana Pula (BWP)
  • Belarusian Ruble (BYN)
  • Belize Dollar (BZD)
  • Canadian Dollar (CAD)
  • Congolese Franc (CDF)
  • Swiss Franc (CHF)
  • Chilean Peso (CLP)
  • Chinese Yuan (CNY)
  • Colombian Peso (COP)
  • Costa Rican Colón (CRC)
  • Cuban Peso (CUP)
  • Cape Verdean Escudo (CVE)
  • Czech Koruna (CZK)
  • Djiboutian Franc (DJF)
  • Danish Krone (DKK)
  • Dominican Peso (DOP)
  • Algerian Dinar (DZD)
  • Egyptian Pound (EGP)
  • Eritrean Nakfa (ERN)
  • Ethiopian Birr (ETB)
  • Euro (EUR)
  • Fijian Dollar (FJD)
  • Falkland Islands Pound (FKP)
  • British Pound (GBP)
  • Georgian Lari (GEL)
  • Ghanaian Cedi (GHS)
  • Gibraltar Pound (GIP)
  • Gambian Dalasi (GMD)
  • Guinean Franc (GNF)
  • Guatemalan Quetzal (GTQ)
  • Guyanese Dollar (GYD)
  • Hong Kong Dollar (HKD)
  • Honduran Lempira (HNL)
  • Croatian Kuna (HRK)
  • Haitian Gourde (HTG)
  • Hungarian Forint (HUF)
  • Indonesian Rupiah (IDR)
  • Israeli New Shekel (ILS)
  • Iraqi Dinar (IQD)
  • Iranian Rial (IRR)
  • Icelandic Króna (ISK)
  • Jamaican Dollar (JMD)
  • Jordanian Dinar (JOD)
  • Japanese Yen (JPY)
  • Kenyan Shilling (KES)
  • Kyrgyzstani Som (KGS)
  • Cambodian Riel (KHR)
  • Comorian Franc (KMF)
  • South Korean Won (KRW)
  • Kuwaiti Dinar (KWD)
  • Cayman Islands Dollar (KYD)
  • Kazakhstani Tenge (KZT)
  • Lao Kip (LAK)
  • Lebanese Pound (LBP)
  • Sri Lankan Rupee (LKR)
  • Liberian Dollar (LRD)
  • Lesotho Loti (LSL)
  • Libyan Dinar (LYD)
  • Moroccan Dirham (MAD)
  • Moldovan Leu (MDL)
  • Malagasy Ariary (MGA)
  • Macedonian Denar (MKD)
  • Burmese Kyat (MMK)
  • 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)
  • Nigerian Naira (NGN)
  • Nicaraguan Córdoba (NIO)
  • Norwegian Krone (NOK)
  • Nepalese Rupee (NPR)
  • New Zealand Dollar (NZD)
  • Omani Rial (OMR)
  • Panamanian Balboa (PAB)
  • Peruvian Sol (PEN)
  • Papua New Guinean Kina (PGK)
  • Philippine Peso (PHP)
  • Pakistani Rupee (PKR)
  • Polish Złoty (PLN)
  • Paraguayan Guaraní (PYG)
  • Qatari Riyal (QAR)
  • Romanian Leu (RON)
  • Serbian Dinar (RSD)
  • Russian Ruble (RUB)
  • Rwandan Franc (RWF)
  • Saudi Riyal (SAR)
  • Solomon Islands Dollar (SBD)
  • Seychellois Rupee (SCR)
  • Sudanese Pound (SDG)
  • Swedish Krona (SEK)
  • Singapore Dollar (SGD)
  • Saint Helena Pound (SHP)
  • Sierra Leonean Leone (SLL)
  • Somali Shilling (SOS)
  • Surinamese Dollar (SRD)
  • São Tomé and Príncipe Dobra (STD)
  • Syrian Pound (SYP)
  • Swazi Lilangeni (SZL)
  • Thai Baht (THB)
  • Tajikistani Somoni (TJS)
  • Turkmenistani Manat (TMT)
  • Tunisian Dinar (TND)
  • Tongan Paʻanga (TOP)
  • Turkish Lira (TRY)
  • Trinidad and Tobago Dollar (TTD)
  • 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 women's financial services space.

CASELET 1

Savings product preference & channel trust among urban women (India)

CASELET 2

Credit access barriers & lender perception among rural women borrowers (India)

Savings product preference & channel trust among urban women (India)

OBJECTIVE

A digital-first NBFC needed to map how salaried urban women and self-employed urban women evaluate savings and deposit products, and which trust signals and channel touchpoints drive their final enrollment decision.

WHAT WE DID

Ran a structured quant survey across 6 cities with 480 respondents, capturing product shortlisting criteria , preferred onboarding channel , documentation tolerance , and trust attribution by institution type for each occupational segment.

DELIVERED

A segment-level preference map by occupational type, a ranked list of trust-building levers by channel, and a friction inventory covering the 4 highest-dropout steps in the digital enrollment journey.
CASELET 1

Savings product preference & channel trust among urban women (India)

CASELET 2

Credit access barriers & lender perception among rural women borrowers (India)

Savings product preference & channel trust among urban women (India)

OBJECTIVE

A digital-first NBFC needed to map how salaried urban women and self-employed urban women evaluate savings and deposit products, and which trust signals and channel touchpoints drive their final enrollment decision.

WHAT WE DID

Ran a structured quant survey across 6 cities with 480 respondents, capturing product shortlisting criteria , preferred onboarding channel , documentation tolerance , and trust attribution by institution type for each occupational segment.

DELIVERED

A segment-level preference map by occupational type, a ranked list of trust-building levers by channel, and a friction inventory covering the 4 highest-dropout steps in the digital enrollment journey.

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 unbanked, underbanked and fully banked women?

How will you measure financial product preference beyond simple ratings?

Will the survey map the full financial inclusion journey and drop-offs?

Can this survey inform product and pricing strategy?

How will findings improve our women-segment acquisition and retention strategy?

Still have questions?

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

Book a Discovery Call