TYRES & AUTO RETAIL

Tyre Retailer Consumer Advisory & Brand Recommendation Behaviour Survey

Map how tyre buyers evaluate fitment advice, compare brand recommendations, and choose retailers across walk-in and service contexts, so you can sharpen conversion positioning, fix channel segmentation, and benchmark recommendation-driven acquisition.

Pan-India sample
Tyre retail consumers (Recent Tyre Purchasers)
15-20 min
Talk to a Survey Consultant
Advisory influence & conversion gapsIdentify where retailer recommendations accelerate or stall brand selection decisions.
Brand switching & loyalty signalsIsolate the price, performance, and trust thresholds that drive brand substitution.
TRUSTED BY LEADING BRANDS
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CONTEXT & RELEVANCE

Why run this survey now

Most tyre retailers don't lose customers purely on price. They lose them due to misread brand trust signals, inconsistent fitment advice, weak upsell framing, poor segment-to-need matching, and staff recommendation gaps, none of which fully show up in POS transaction data or distributor sell-out reports.

If you are...

  • Tyre brand competing on retail shelf
  • Retailer network head, multi-outlet
  • Category or product planning lead
  • Fleet and commercial sales head
  • Aftersales and loyalty programme owner

You're likely facing...

  • Brand recommendation gaps at counter
  • Premium vs. economy fit confusion
  • Staff advice: inconsistent across outlets
  • Import vs. domestic brand perception split
  • Repeat purchase drop-off, no clear trigger

This will help answer...

  • Retailer recommendation drivers by brand
  • Counter advisory drop-off stage
  • Segment preference: fleet vs. retail
  • Margin vs. trust trade-off signals
  • Switching triggers at replacement cycle

RESEARCH THEMES

What This Survey Investigates

Eight interconnected research themes that map the complete tyre buyer journey from fitment trigger to retailer advocacy.

TENETS 01

Purchase Triggers

  • Replacement vs. new fitment events
  • Seasonal, mileage, and damage triggers
TENETS 02

Retailer Discovery

  • Channel mix, online vs. forecourt
  • First-touch retailer awareness sources
TENETS 03

Brand Recommendation

  • Retailer-led vs. consumer-led brand choice
  • Recommendation acceptance and override rates
TENETS 04

Brand Preference Drivers

  • Performance, price, and origin attributes
  • Domestic vs. import brand trade-offs
TENETS 05

Pricing & WTP

  • Per-tyre spend thresholds by segment
  • Discount, EMI, and bundled fitment sensitivity
TENETS 06

Fitment & Servicing

  • In-bay service quality and wait time
  • Wheel alignment, balancing, and TPMS expectations
TENETS 07

Trust & Loyalty

  • Repeat visit intent and retailer switching triggers
  • Staff credibility and post-sale follow-up
TENETS 08

Advocacy & Referral

  • Word-of-mouth referral frequency and triggers
  • Online review posting behaviour by channel

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 Tyre Retailer Consumer Advisory and Brand Recommendation Behaviour Survey, we recommend a quant-first design with flexible data-collection modes to balance reach, depth, and verification.

PRIMARY
Online web surveySelf-administered survey shared via email / panels to capture structured responses at scale.
Best for
1
Ranking brand recommendation triggers by retailer type
2
Measuring advisory influence on consumer tyre brand choice
3
Comparing segments by vehicle category and geography
Deliverables
Recommendation driver ranking
Brand preference matrix
Retailer segment scorecard
OPTIONAL
CATI (phone survey)Interviewer-led telephone interviews to reach owners who are harder to get online.
Best for
1
Roadside and semi-urban tyre retailers with low digital access
2
Quick coverage across Tier 2 and Tier 3 retail clusters
Deliverables
Retailer coverage map
Call-log diagnostics
SELECTIVE
Face-to-faceOn-ground surveys or interviews in key industrial clusters or high-value cohorts.
Best for
1
High-volume multi-brand retailers requiring in-depth advisory profiling
2
Fleet and commercial vehicle tyre purchase decision cohorts
Deliverables
Retailer advisory maps
Purchase journey profiles
OPTIONAL
FGDs
Deliverables
Themes and verbatims
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 cover semi-urban and Tier 2 tyre retailers with limited digital presence.
Consider adding: Face-to-face interviews for high-volume multi-brand retail outlets and a focused FGD layer to pressure-test brand recommendation messaging and distributor incentive structures.

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 tyre retail advisory space.

CASELET 1

Retailer brand steer & fitment category preference (North India)

CASELET 2

Consumer trust signals & advisory credibility at tyre retail (West India)

Retailer brand steer & fitment category preference (North India)

OBJECTIVE

A pan-India tyre distributor needed to quantify how multi-brand tyre retailers steer walk-in customers toward specific brands, and which margin structures , scheme incentives , and brand pull signals most strongly shape that recommendation at the counter.

WHAT WE DID

Ran a structured quant survey across 320 independent tyre retailers in Tier 1 and Tier 2 cities, capturing brand shortlisting criteria , scheme recall scores , counter-level push triggers, and the gap between retailer preference and stated customer demand by fitment category.

DELIVERED

A brand recommendation priority map by retailer segment, a ranked scheme influence index across five competing brands, and a counter-level friction list identifying where distributor support breaks down before the final fitment decision.
CASELET 1

Retailer brand steer & fitment category preference (North India)

CASELET 2

Consumer trust signals & advisory credibility at tyre retail (West India)

Retailer brand steer & fitment category preference (North India)

OBJECTIVE

A pan-India tyre distributor needed to quantify how multi-brand tyre retailers steer walk-in customers toward specific brands, and which margin structures , scheme incentives , and brand pull signals most strongly shape that recommendation at the counter.

WHAT WE DID

Ran a structured quant survey across 320 independent tyre retailers in Tier 1 and Tier 2 cities, capturing brand shortlisting criteria , scheme recall scores , counter-level push triggers, and the gap between retailer preference and stated customer demand by fitment category.

DELIVERED

A brand recommendation priority map by retailer segment, a ranked scheme influence index across five competing brands, and a counter-level friction list identifying where distributor support breaks down before the final fitment decision.

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 independent tyre dealers, multi-brand fitment centres and OEM-authorised service outlets?

How will you measure brand recommendation behaviour beyond simple ratings?

Will the survey map the full retail advisory journey and drop-offs?

Can this survey inform product and pricing strategy?

How will findings improve our retailer engagement and trade marketing spend?

Still have questions?

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

Book a Discovery Call