Research Governance

Sampling Strategy

A sampling strategy is the plan for selecting participants, cases, sites, tasks, or data sources for a study.

Concept facts

A sampling strategy is the plan for selecting participants, cases, sites, tasks, or data sources for a study.

Also known as
Sampling plan, participant selection strategy, qualitative sampling, purposive sampling.
Used in
User research, interview studies, usability testing, surveys, field research, service evaluation, and mixed-methods studies.
Interpret with
Recruitment criteria, research participant, data saturation, research protocol, survey, and usability testing.

Plain-language explanation

A sampling strategy explains who or what will be included in a study and why. It helps ensure that the research includes the people, contexts, and workflows needed to answer the research question.

In UX and digital service work, sampling is not just about the number of participants. It is also about whether the right roles, risk groups, locations, devices, service states, and access conditions are represented.

Why it matters

Poor sampling can make research findings misleading. A service may work well for confident urban users but fail for rural users, low-literacy users, staff-mediated users, people with disabilities, or users facing identity verification problems.

A sampling strategy helps teams avoid designing only for the easiest participants to recruit.

Use contexts

A sampling strategy is used when:

  • planning participant recruitment
  • deciding which user groups or staff roles to include
  • comparing urban and rural contexts
  • studying high-friction or high-risk journeys
  • ensuring that edge cases and excluded users are not ignored
  • explaining the limits of research findings

Application guidance

Sampling should follow the research question. A usability test may need participants who match a target user group. A service evaluation may need applicants, frontline staff, supervisors, and support agents. A digital transformation study may need both formal decision-makers and people doing daily operational work.

Teams should document inclusion and exclusion criteria, recruitment channels, sample diversity, and known gaps.

Practical example

A bank redesigns its digital onboarding journey. Recruiting only young smartphone users from Dhaka would miss important risks.

A better sampling strategy includes first-time account applicants, existing customers updating KYC information, rural agent-assisted users, older users, users with document mismatches, branch staff, call center agents, and compliance reviewers.

This sample helps the team understand where onboarding fails: not only in the interface, but also in document verification, agent guidance, customer trust, and exception handling.

Interpretive boundaries

A sampling strategy does not guarantee representativeness unless the study is designed for statistical inference. Many UX studies use purposive or theoretical sampling rather than random sampling.

The strategy should be transparent about what the sample can and cannot support.

Applied at Userhub

Userhub defines sampling strategies to ensure that UX research includes relevant users, service roles, contexts, and risk conditions.

This is especially important for public services, financial services, development programs, institutional platforms, and staff-mediated digital journeys.

See Userhub UX Lab for applied UX research and evaluation context.

Sources and references

Patton, M. Q. (2015). Qualitative Research & Evaluation Methods: Integrating Theory and Practice (4th ed.). SAGE Publications.

Palinkas, L. A., Horwitz, S. M., Green, C. A., Wisdom, J. P., Duan, N., & Hoagwood, K. (2015). Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Administration and Policy in Mental Health and Mental Health Services Research, 42(5), 533–544. https://doi.org/10.1007/s10488-013-0528-y

Robinson, O. C. (2014). Sampling in interview-based qualitative research: A theoretical and practical guide. Qualitative Research in Psychology, 11(1), 25–41. https://doi.org/10.1080/14780887.2013.801543

Teddlie, C., & Yu, F. (2007). Mixed methods sampling: A typology with examples. Journal of Mixed Methods Research, 1(1), 77–100. https://doi.org/10.1177/2345678906292430

Cite this entry

APA

Userhub. (2026). Sampling Strategy. UX Reference. https://userhub.com.bd/reference/sampling-strategy/