Illustrative engagement. A representative scenario showing how we approach this kind of work in entertainment. It does not describe a specific client; outcomes are described qualitatively.
Industry overview
What is shaping entertainment
Live events, theme parks and entertainment brands sell experiences. Ticketing, crowd experience and sponsor value decide whether people come back.
- Ticket pricing and booking ease affect attendance
- On-site experience drives repeat visits
- Sponsors expect audience evidence
Client background
An entertainment start-up, working in Tier-2 Indian cities. This is an illustrative engagement: a representative scenario showing how we approach this kind of work, not a named client project.
- Organisation
- An entertainment start-up
- Sector
- Entertainment
- Team engaged
- Market Research
- Services
- Market sizing and competitive intelligence, Online surveys, Consumer panel
Client challenge
The start-up wanted to expand beyond metros but did not know which cities had enough demand.
Research objectives
- Deliver on the brief: sizing demand for escape rooms in new cities.
- Understand the views, needs and behaviour of young adults.
- Produce results that can be compared across groups and locations.
- Give the client evidence it can act on within 5 weeks.
Target audience
The work focused on 1,500 young adults.
- young adults1,500
Audiences we typically reach in entertainment
Event-goersTheme-park visitorsTicket buyersSponsorsFamilies
Geographic coverage
Coverage: Tier-2 Indian cities. Market: India.
- India
Research methodology
A structured analytical design combining desk research, modelling and primary evidence.
- 1Brief
- 2Consumer survey
- 3Competitor mapping
- 4Insight
We surveyed young adults in shortlisted cities about leisure spending and interest in group experiences, and mapped existing entertainment options.
Market sizing and competitive intelligenceOnline surveysConsumer panel
Sampling strategy
- young adults
- 1,500
- Online respondents were drawn from verified panel members who matched the screening criteria, with quotas on key profile attributes.
Data collection
- The online survey was mobile-friendly and offered in respondents' languages.
- Secondary sources and client data were compiled and cross-checked before modelling.
Data quality & validation
- Digital fingerprinting and duplicate checks
- Attention, speed and straight-lining checks
- Review of open-ended answers
- 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
- Market model built from secondary data and primary evidence
Key findings
- Two cities showed strong interest and few competitors.
Choose cities where interest is high and choice is low.
Recommendations
- Build on the core insight: choose cities where interest is high and choice is low.
- Focus effort where the evidence was strongest: two cities showed strong interest and few competitors.
- Re-measure after the changes to confirm the effect.
Business impact
- The start-up opened there first.
What changed in the business as a result of the work. Impact is described qualitatively.
Deliverables & next steps
- Cleaned data file and data tables
- Repeat the measure after changes are in place to track progress.
- A natural follow-on question: who comes, and why?