Illustrative engagement. A representative scenario showing how we approach this kind of work in education. It does not describe a specific client; outcomes are described qualitatively.
Industry overview
What is shaping education
Schools, universities, edtech companies and education programmes need evidence from students, parents and teachers, and marketing that reaches families at the right time.
- Parents research schools and courses online
- Edtech usage depends on teacher and parent support
- Programmes must show learning outcomes
Client background
An edtech company, working in India & Indonesia. This is an illustrative engagement: a representative scenario showing how we approach this kind of work, not a named client project.
- Organisation
- An edtech company
- Sector
- Education
- Team engaged
- Market Research
- Services
- Quantitative research, UI/UX design, Online surveys
Client challenge
Many learners signed up but stopped within two weeks.
Research objectives
- Answer the core question: why students drop out of an online course app.
- Understand the views, needs and behaviour of learners.
- Measure how widespread each pattern is, and explain the reasons behind it.
- Give the client evidence it can act on within 6 weeks.
Target audience
The work focused on 2,000 learners.
- learners2,000
Audiences we typically reach in education
StudentsParentsTeachers and principalsEdtech usersEmployers
Geographic coverage
Coverage: India & Indonesia. Markets: India and Indonesia.
- India
- Indonesia
Research methodology
A mixed-method design: structured research measured how widespread each pattern was, and qualitative conversations explained why.
- 1Brief
- 2Learner survey
- 3Usage interviews
- 4Insight
We surveyed active and inactive learners and interviewed some about their study routines and obstacles.
Quantitative researchUI/UX designOnline surveys
Sampling strategy
- learners
- 2,000
- Online respondents were drawn from verified panel members who matched the screening criteria, with quotas on key profile attributes.
- Qualitative participants were recruited purposively to cover the full range of experiences that mattered, rather than for statistical representation.
Data collection
- The online survey was mobile-friendly and offered in respondents' languages.
- Interviews and discussions were led by experienced moderators using a guide agreed with the client.
Data quality & validation
- Digital fingerprinting and duplicate checks
- Attention, speed and straight-lining checks
- Review of open-ended answers
- Recordings and transcripts for every session
- Re-screening of qualitative recruits
- 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
- Thematic coding of interviews and discussions
- Journey and decision mapping
Key findings
- Learners stopped when lessons felt too long on mobile data.
Design for the learner's real day, not the ideal one.
Recommendations
- Build on the core insight: design for the learner's real day, not the ideal one.
- Focus effort where the evidence was strongest: learners stopped when lessons felt too long on mobile data.
- Re-measure after the changes to confirm the effect.
Business impact
- The company introduced shorter lessons and offline downloads.
What changed in the business as a result of the work. Impact is described qualitatively.
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: did the programme improve learning?