FINTECH & DIGITAL PLATFORMS

FinTech Platform Experience Evaluation Survey

Measure how digital banking and payments users evaluate, compare, and choose between FinTech platforms on onboarding speed, feature depth, and fee transparency, so you can sharpen acquisition targeting, fix conversion drop-offs, and benchmark retention by segment.

Pan-India sample
FinTech platform users (Active Account Holders)
15-20 min
Talk to a Survey Consultant
Onboarding friction & drop-offsIdentify where new users stall, disengage, or abandon platform registration.
Feature value & switching triggersRank the product capabilities and pricing signals that drive platform switching decisions.
TRUSTED BY LEADING BRANDS
Brand 0Brand 1Brand 2Brand 3Brand 4Brand 5Brand 6Brand 7Brand 8Brand 9Brand 10Brand 11Brand 12Brand 13Brand 14Brand 15Brand 16Brand 17Brand 18Brand 19Brand 20Brand 21Brand 22Brand 23Brand 24Brand 25Brand 26Brand 27Brand 28Brand 29Brand 30Brand 31

CONTEXT & RELEVANCE

Why run this survey now

Most FinTech platforms don't lose users purely on missing features. They lose them due to friction at onboarding, inconsistent transaction flows, weak support touchpoints, poor personalization, and unclear value communication, none of which fully show up in product analytics dashboards or NPS scores.

If you are...

  • FinTech platform competing on experience
  • Product head reviewing feature roadmap
  • Growth lead facing activation drop-offs
  • Revenue head benchmarking retention rates
  • Strategy lead preparing board-level positioning

You're likely facing...

  • Onboarding drop-off: KYC friction stage
  • Feature adoption vs. churn tension
  • Incumbents = trusted/slow perception
  • Challengers = fast/unreliable perception
  • Renewal gaps: pricing vs. service fit

This will help answer...

  • Experience drivers beyond product features
  • Onboarding drop-off stage and cause
  • Segment preference by platform type
  • Fee transparency vs. perceived value
  • Switching triggers and retention levers

RESEARCH THEMES

What This Survey Investigates

Eight interconnected research themes that map the complete FinTech user journey from platform discovery to long-term retention.

TENETS 01

Discovery & Awareness

  • First platform touchpoints, referral sources
  • Awareness channels by user segment
TENETS 02

Onboarding & Activation

  • KYC friction, verification drop-off points
  • Time-to-first-transaction by user cohort
TENETS 03

Feature & UX

  • Core feature usage frequency, depth
  • Interface clarity, navigation friction
TENETS 04

Trust & Security

  • Fraud concern, data privacy confidence
  • Security feature awareness by segment
TENETS 05

Pricing & Value

  • Fee transparency, willingness-to-pay thresholds
  • Perceived value vs. incumbent banking cost
TENETS 06

Retention & Stickiness

  • Multi-platform usage, primary wallet share
  • Churn triggers, re-engagement patterns
TENETS 07

Support & Resolution

  • Dispute resolution speed, channel preference
  • Self-service vs. agent escalation rates
TENETS 08

Competitive Positioning

  • Switching intent, competitor consideration set
  • Unmet needs driving platform comparison

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 FinTech Platform Experience Evaluation Survey, we recommend a quant-first design with flexible data-collection modes to balance reach, depth, and verification across user segments and platform touchpoints.

PRIMARY
Online web surveySelf-administered survey shared via email / panels to capture structured responses at scale.
Best for
1
Rating platform usability across onboarding and transaction flows
2
Ranking feature satisfaction by user tier and product type
3
Benchmarking NPS and churn risk across segments
Deliverables
Feature satisfaction scores
Churn risk matrix
Segment NPS bands
OPTIONAL
CATI (phone survey)Interviewer-led telephone interviews to reach owners who are harder to get online.
Best for
1
Low-digital users with limited app engagement history
2
Quick pulse across tier-2 and tier-3 city cohorts
Deliverables
Offline user coverage
Call-log diagnostics
SELECTIVE
Face-to-faceOn-ground surveys or interviews in key industrial clusters or high-value cohorts.
Best for
1
High-value enterprise clients requiring in-depth verification
2
Contextual mapping of embedded finance adoption barriers
Deliverables
Adoption barrier maps
High-value user profiles
OPTIONAL
FGDs
Deliverables
Themes and verbatims
Feature 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 for low-digital and tier-2 user segments with limited platform engagement.
Consider adding: F2F interviews for high-value enterprise cohorts and a focused FGD layer to pressure-test messaging and feature positioning with power users.

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 fintech platform experience space.

CASELET 1

Digital lending onboarding friction & drop-off diagnosis (India)

CASELET 2

Payment platform switching intent & messaging territories (Southeast Asia)

Digital lending onboarding friction & drop-off diagnosis (India)

OBJECTIVE

A digital-first NBFC needed to isolate where first-time borrowers and repeat applicants abandoned their onboarding flow, and which verification steps , document upload stages , and credit decision wait times drove the highest exit rates.

WHAT WE DID

Ran a structured quant survey across 480 respondents in 6 cities, capturing step-level drop-off triggers , perceived wait time tolerance , trust signals by channel , and feature-level satisfaction scores at each onboarding milestone.

DELIVERED

A stage-by-stage friction map across the onboarding journey, a ranked list of exit triggers by borrower segment , and a set of experience levers prioritised by effort-to-impact ratio for the product and growth teams.
CASELET 1

Digital lending onboarding friction & drop-off diagnosis (India)

CASELET 2

Payment platform switching intent & messaging territories (Southeast Asia)

Digital lending onboarding friction & drop-off diagnosis (India)

OBJECTIVE

A digital-first NBFC needed to isolate where first-time borrowers and repeat applicants abandoned their onboarding flow, and which verification steps , document upload stages , and credit decision wait times drove the highest exit rates.

WHAT WE DID

Ran a structured quant survey across 480 respondents in 6 cities, capturing step-level drop-off triggers , perceived wait time tolerance , trust signals by channel , and feature-level satisfaction scores at each onboarding milestone.

DELIVERED

A stage-by-stage friction map across the onboarding journey, a ranked list of exit triggers by borrower segment , and a set of experience levers prioritised by effort-to-impact ratio for the product and growth teams.

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 retail users, SME account holders and enterprise clients?

How will you measure platform preference beyond simple ratings?

Will the survey map the full platform adoption journey and drop-offs?

Can this survey inform product and pricing strategy?

How will findings improve our platform growth and retention targets?

Still have questions?

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

Book a Discovery Call