FOOD & RESTAURANT TECH

Restaurant Aggregator Platform Preference Survey

Map how restaurant owners and operators evaluate, compare, and choose between aggregator platforms on commission rates, order volume, and visibility tools, so you can sharpen acquisition positioning, fix pricing tiers, and improve partner retention.

Pan-India sample
Restaurant owners and operators (Platform Decision-Makers)
15-20 min
Talk to a Survey Consultant
Onboarding friction & drop-offsIdentify where restaurant owners stall, disengage, or abandon platform sign-up.
Commission sensitivity & platform trade-offsBenchmark commission thresholds, exclusivity tolerance, and visibility feature priorities by segment.
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CONTEXT & RELEVANCE

Why run this survey now

Most restaurant operators don't lose platform orders purely on commission rates. They lose them due to inconsistent delivery reliability, poor menu visibility, opaque ranking algorithms, weak customer data access, and misaligned promotional mechanics, none of which fully show up in platform dashboards or monthly settlement reports.

If you are...

  • Multi-outlet restaurant chain operator

  • Cloud kitchen network scaling cities

  • Platform partnerships or revenue head

  • Menu and pricing strategy lead

  • Aggregator platform category manager

You're likely facing...

  • Platform fee vs. order volume tension

  • Ranking drop: visibility vs. spend

  • Aggregators = reach/margin squeeze perception

  • Multi-platform split: loyalty vs. cost

  • Reorder gaps: platform vs. direct channel

This will help answer...

  • Platform preference drivers beyond fees

  • Order drop-off stage by platform

  • Segment preference: QSR vs. casual

  • Commission tolerance vs. visibility trade-off

  • Switching triggers across aggregator platforms

RESEARCH THEMES

What This Survey Investigates

Eight interconnected research themes that map the complete diner journey from platform discovery to repeat ordering.

TENETS 01

Discovery & Onboarding

  • First platform encountered, trigger channel
  • App install to first order gap
TENETS 02

Preference Drivers

  • Primary platform selection criteria
  • Cuisine availability vs. delivery speed trade-off
TENETS 03

Ordering & UX

  • Menu browsing to checkout completion rate
  • Search, filter, and cart friction points
TENETS 04

Delivery Experience

  • Estimated vs. actual delivery time variance
  • Packaging condition, order accuracy on arrival
TENETS 05

Pricing & WTP

  • Platform fee, surge, and delivery charge tolerance
  • Discount dependency vs. full-price ordering behaviour
TENETS 06

Loyalty & Retention

  • Subscription plan uptake and renewal intent
  • Switching triggers after a negative experience
TENETS 07

Trust & Ratings

  • Restaurant rating credibility and review reliance
  • Food safety, hygiene badge influence on selection
TENETS 08

Platform Switching

  • Multi-platform usage frequency and split
  • Conditions that shift primary platform status
Request a scope validation call

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?
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Discuss sample plan

METHODOLOGY

Survey approach

For the Restaurant Aggregator Platform Preference Survey, we recommend a quant-first design with flexible data-collection modes to balance reach, depth, and verification across restaurant owner and operator segments.

PRIMARY
Online web surveySelf-administered survey shared via email / panels to capture structured responses at scale.
Best for
1
Ranking platform preference by cuisine type and city tier.
2
Measuring commission sensitivity and switching intent.
3
Comparing segments by outlet count, format, and region.
Deliverables
Platform preference ranking
Commission threshold matrix
Segment gap analysis
OPTIONAL
CATI (phone survey)Interviewer-led telephone interviews to reach owners who are harder to get online.
Best for
1
Single-outlet owners with low digital engagement.
2
Quick coverage across Tier 2 and Tier 3 cities.
Deliverables
Tier-wise coverage data
Call-log diagnostics
SELECTIVE
Face-to-faceOn-ground surveys or interviews in key industrial clusters or high-value cohorts.
Best for
1
Multi-outlet chains and high-GMV restaurant partners.
2
Dense food-court clusters requiring on-ground verification.
Deliverables
Cluster-level insights
Partner journey maps
OPTIONAL
FGDs
Deliverables
Themes and verbatims
Proposition 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 single-outlet owners and Tier 2 and Tier 3 city operators with low digital presence.
Consider adding: F2F interviews for high-GMV multi-outlet chains and a focused FGD layer to pressure-test platform switching triggers and commission messaging.
Confirm approach
Request timeline

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)
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  • 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)
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  • Euro (EUR)
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  • British Pound (GBP)
  • Georgian Lari (GEL)
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  • Gibraltar Pound (GIP)
  • Gambian Dalasi (GMD)
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  • Guatemalan Quetzal (GTQ)
  • Guyanese Dollar (GYD)
  • Hong Kong Dollar (HKD)
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  • Croatian Kuna (HRK)
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  • Icelandic Króna (ISK)
  • Jamaican Dollar (JMD)
  • Jordanian Dinar (JOD)
  • Japanese Yen (JPY)
  • Kenyan Shilling (KES)
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  • Lao Kip (LAK)
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  • 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)
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  • Thai Baht (THB)
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  • Turkmenistani Manat (TMT)
  • Tunisian Dinar (TND)
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  • 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 food-tech and restaurant platform space.

CASELET 1

Diner segment pricing tolerance & platform switching triggers (India)

CASELET 2

Restaurant partner onboarding friction & commission perception audit (India)

Diner segment pricing tolerance & platform switching triggers (India)

OBJECTIVE

A quick-service restaurant brand needed to quantify how frequent diners , occasional orderers , and deal-driven users weigh delivery fees, discount depth, and estimated time against platform loyalty across Tier 1 and Tier 2 cities.

WHAT WE DID

Ran a structured quant survey across 1,200 respondents in 8 cities, capturing platform shortlisting criteria , fee sensitivity thresholds , discount redemption frequency , and stated switching triggers at each ordering occasion type.

DELIVERED

A segment-level pricing corridor by diner archetype, a ranked switching trigger list by city tier, and a platform preference map isolating the fee and discount combinations that hold each segment in place.
Talk to Survey Consultant
CASELET 1

Diner segment pricing tolerance & platform switching triggers (India)

CASELET 2

Restaurant partner onboarding friction & commission perception audit (India)

Diner segment pricing tolerance & platform switching triggers (India)

OBJECTIVE

A quick-service restaurant brand needed to quantify how frequent diners , occasional orderers , and deal-driven users weigh delivery fees, discount depth, and estimated time against platform loyalty across Tier 1 and Tier 2 cities.

WHAT WE DID

Ran a structured quant survey across 1,200 respondents in 8 cities, capturing platform shortlisting criteria , fee sensitivity thresholds , discount redemption frequency , and stated switching triggers at each ordering occasion type.

DELIVERED

A segment-level pricing corridor by diner archetype, a ranked switching trigger list by city tier, and a platform preference map isolating the fee and discount combinations that hold each segment in place.

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 quick-service restaurants, casual dining outlets and cloud kitchen operators?

How will you measure aggregator platform preference beyond simple ratings?

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

Can this survey inform product and pricing strategy?

How will findings improve our platform 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