Industry overview
What is shaping hospitality
Hotels, restaurants and travel brands are judged on every stay, meal and review. Guest experience, consistency and online reputation drive bookings.
- Online reviews strongly influence bookings
- Consistency across properties builds trust
- Guests expect personalised service
Client background
A casual dining restaurant group, working in Bengaluru, Hyderabad & Chennai. Client identity is withheld to protect confidentiality.
- Organisation
- A casual dining restaurant group
- Sector
- Hospitality
- Team engaged
- Market Research
- Services
- Quantitative research, Offline data collection, Financial modelling
Client challenge
Rising costs of vegetables, dairy and cooking oil were squeezing margins across the group’s restaurants. Management needed to raise prices and refresh the menu, but feared losing regular diners to competitors in the busy dining districts of Bengaluru, Hyderabad and Chennai.
Research objectives
- Deliver on the brief: testing new menu items and prices for a restaurant group.
- Understand the views, needs and behaviour of diners.
- Produce results that can be compared across groups and locations.
- Give the client evidence it can act on within 6 weeks.
Target audience
The work focused on 1,200 diners.
- diners1,200
Audiences we typically reach in hospitality
Guests and dinersCorporate travel buyersFront-line staffTravel agentsOnline reviewers
Geographic coverage
Coverage: Bengaluru, Hyderabad & Chennai. Market: India.
- India
Research methodology
A structured analytical design combining desk research, modelling and primary evidence.
- 1Brief
- 2In-restaurant tasting tests
- 3Price acceptance survey
- 4Margin model
- 5Insight
We ran tasting sessions in restaurants with regular diners, who tried proposed new dishes and rated taste, portion and value. Diners were then asked structured price-acceptance questions for both new and existing favourites. Our finance team combined the results with recipe costs to model margins and expected demand under different pricing scenarios.
Quantitative researchOffline data collectionFinancial modelling
Sampling strategy
- diners
- 1,200
- Respondents were selected across Bengaluru, Hyderabad & Chennai using quotas set in advance for each location and respondent type, so no single area or group dominated.
Data collection
- Trained local-language interviewers conducted interviews in person, supervised in the field.
- Secondary sources and client data were compiled and cross-checked before modelling.
Data quality & validation
- Back-checks on a share of completed interviews
- Time and location checks on field interviews
- Supervisor accompaniment in the field
- Logic and range checks on the final data
- Work carried out under our ISO 20252 quality procedures
Data analysis
- Cross-tabulation by key groups and locations
- Significance testing on the differences that mattered
- Price and trade-off analysis
- Market model built from secondary data and primary evidence
Key findings
- Testing with real diners replaced guesswork with evidence in pricing decisions.
Recommendations
- Several new dishes tested strongly even at higher prices, while a few popular staples were very price sensitive.
- The group raised prices selectively, introduced the strongest new dishes as premium options and kept staples close to existing prices.
What we recommended, and the client put into practice
Business impact
- Margins improved without a drop in footfall.
Deliverables & next steps
- Insight report and management presentation
- Cleaned data file and data tables
- Repeat the measure after changes are in place to track progress.
- A natural follow-on question: are properties delivering brand standards?
Client identity is withheld to protect confidentiality.