YOUR PROJECT OUTCOME
A research protocol, collection instruments, an anonymised dataset, verified AI analysis and a decision dossier covering segments, limitations and subsequent tests.
Who it is for
Entrepreneurs, marketing leaders and consultants validating needs, demand or a new offer through primary research.
What you need to start
A bounded commercial question and access to real participants through appropriate recruitment. Alternatively, clearly identified teaching data may be used; this does not constitute market validation.
The curriculum
01The research question and hypotheses
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Define the decision and use AI to compare three alternative explanations. Establish what to measure and what could disprove the hypothesis, avoiding research designed only to confirm a belief.
02Sampling, recruitment and data quality
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Define inclusion criteria, participant diversity and representativeness limits. Use AI to challenge the design and selection risks; distinguish convenience samples from justified generalisations.
03Interviews and surveys
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Prepare neutral questions, discussion guides and pilots with AI. Review leading language, question order and response burden before collecting answers from real people.
04Responsible collection and preparation
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Manage permissions, minimisation and anonymisation. Use AI to support transcription and organisation only under appropriate tool and data conditions, checking text against authorised recordings or notes.
05Qualitative analysis with human oversight
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Build a coding framework and compare human and AI classifications. Preserve verifiable quotations, contrary cases and disagreements, preventing summaries from erasing nuance or inventing motives.
06Quantitative analysis and segmentation
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Clean data, verify calculations and distinguish observed differences from robust conclusions. Use AI to suggest segments based on relevant needs and behaviours, checking them against the dataset and sample limitations.
07From stated demand to willingness to pay
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Compare interviews, observed behaviour and offer tests. Design a transparent experiment with AI, defining metrics, resources and thresholds; distinguish interest, intention and purchase.
08The dossier and the decision
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Present findings, sources, AI analysis and human revisions. Form a decision proportionate to the evidence and a verification plan; identify real data, teaching data and synthetic hypotheses separately.
The final project
Research into an offer with a protocol, interview guide or survey, a reasoned sample, an anonymised dataset, an AI-verification register and a decision dossier. Work based on teaching data remains explicitly identified as simulation.
Planned assessment criteria
Planned review criteria include design quality, question neutrality, data provenance, analytical accuracy and proportionate conclusions. Synthetic AI-generated responses are not counted as evidence from real customers.
Tools and materials
- AI assistant for research design and verified analysis
- Survey and interview tools
- Spreadsheet or analysis environment
- Anonymised datasets
- Coding, source and review register
Listed tools are examples, not partnerships. Access requirements and possible additional costs will be specified before enrolment.
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