Proposed hypothesis
Does equipment guidance support better buying decisions?
Task, season and available-size context may improve paid conversion without reducing margin or recommendation quality.
Offer your expertise →The catalogue presents potential research directions. A published hypothesis does not imply open recruitment, an approved budget or data access. We agree on each task’s terms before work begins.
Context
HONOR connects online selection, fitting and purchase. We propose a separate test of recommendation usefulness.
What we test
Task, season and available-size context may improve paid conversion without reducing margin or recommendation quality.
Why it matters
We need to distinguish useful guidance from a fluent AI response.
What is known
The 12-store network and connected profiles are described as implemented. The causal sales effect of AI recommendations has not been established.
Data and resources
By agreement: de-identified product examples, stock, selection history and paid orders. Customer data is not publicly accessible.
Test plan
Record baseline conversion; compare guidance approaches in comparable groups; check availability, size and task fit.
Primary metric
Paid purchase rate among test participants.
Success and stop criteria
Set the effect threshold and duration before testing. Guardrails: margin, returns and recommendation errors. Stop for unacceptable quality or an unreliable comparison.
Skills and contribution
Retail specialist, UX researcher, AI engineer and experiment analyst. Contribution: test cases, a guidance prototype, error review and valid comparison.
Timing
Agree after defining data, scope and comparison.
Participation terms
Propose a research contribution, project work or partnership. Agree on payment, rights, access and publication separately before starting.
Ownership
Assign hypothesis and business owners, delivery and measurement responsibilities before starting.
Evidence pack
A hypothesis brief, baseline, comparison protocol, observations, errors and a scale, iterate or stop decision. Public evidence excludes confidential data.
Have an approach to this question?
Share one relevant example and the contribution you propose. This hypothesis will already be selected in the form.