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  1. M&E Library
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  3. Key Informant Interviews
Core ConceptData Collection5 min read

Key Informant Interviews

In-depth, semi-structured interviews with individuals selected for their specific knowledge, experience, or perspectives relevant to the evaluation questions.

When to Use

Key informant interviews (KIIs) are the right method when you need to understand context, mechanisms, perceptions, or decision-making processes that structured questionnaires cannot capture. Use them when:

  • Explanatory depth is needed: survey data shows what happened; KIIs explain why
  • Specific knowledge holders must be reached: government officials, programme managers, community leaders, technical specialists, or service providers who hold unique perspectives
  • Triangulation is required: KIIs complement quantitative data by providing explanatory context and validating or challenging survey findings
  • Rapid assessment timelines: KIIs can be designed and conducted in days, making them well-suited to rapid assessments, situational analyses, and emergency contexts

KIIs are not appropriate for collecting data that should be statistically representative (use surveys), for group dynamics or community-level perspectives (use focus group discussions), or for direct observation of behaviour (use observation methods).

How It Works

Step 1: Define the purpose and key informant types

What specific information do you need, and who holds it? Identify the types of informants: programme staff (implementation perspective), community leaders (community perspective), service providers (delivery perspective), government officials (policy perspective), beneficiaries (experience perspective). Aim for diversity across perspective types.

Step 2: Develop the interview guide

Write a semi-structured guide with 5-10 open-ended question areas (not scripts). Organise from general to specific. Ensure each question area maps to an evaluation question. Include probes for follow-up. The guide should be a reference, not a rigid script, follow where the interview leads.

Step 3: Select informants purposively

Purposive sampling is standard for KIIs: select individuals because of their specific knowledge or position, not randomly. Aim for 20-40 informants for most evaluations, targeting saturation, when new interviews are producing no new themes.

Step 4: Conduct the interviews

Use a two-person team where possible: one interviewer, one notetaker. Record with consent. Build rapport before sensitive questions. Use active listening, silence, and probes to draw out depth.

Step 5: Analyse thematically

Organise notes or transcripts by theme, not by interview. Look for patterns, contradictions, and outliers. Compare findings across informant types.

Step 6: Triangulate with other data sources

KII findings should be triangulated with survey data, document review, and (where applicable) focus group discussions before conclusions are drawn. No single KII finding should drive a major conclusion without corroboration.

Key Components

  • Interview guide: 5-10 open-ended question areas with probes, organised by theme
  • Informant typology: a defined set of informant roles to be covered, with rationale
  • Sampling matrix: tracking which informant types have been interviewed and ensuring diversity
  • Note-taking protocol: standardised approach to capturing verbatim quotes and observations
  • Analysis framework: a thematic coding structure aligned to evaluation questions
  • Triangulation matrix: tracking how KII findings compare to other data sources

Best Practices

Use semi-structured, not structured. Fully scripted interviews produce survey-quality data through an inefficient method. The value of KIIs comes from following unexpected threads. Keep the guide as a reference, not a constraint.

Prioritise listening over talking. Interviewers who fill silences with more questions get less data. Silence prompts elaboration. Restate, don't redirect.

Record with consent, transcribe selectively. Full transcription of all interviews is expensive and rarely necessary. Transcribe verbatim only key passages; use detailed notes for the rest.

Include data quality checks. If a finding appears in only one interview and contradicts all other data, treat it with caution. Note it as an outlier, not a conclusion.

Debrief after each interview. Immediately after each interview, the team should spend 10 minutes noting key findings, surprises, and follow-up questions. This debriefing captures context that does not appear in notes and guides the next interview.

Common Mistakes

Over-relying on official informants. Programme managers and government officials are easy to reach but may give politically safe rather than candid responses. Balance official perspectives with community-level informants.

Leading questions. "Would you agree that the programme improved access?" is a leading question. "How has access changed since the programme started?" is not. Poor question design in KIIs produces confirmation bias, not evidence.

No analysis framework. Analysing KII data without a structure ("just reading the notes") produces vague, anecdotal findings. Use a thematic coding framework aligned to evaluation questions.

Treating KII as substitute for survey. KIIs provide depth, not representation. Findings from 25 interviews cannot be extrapolated to a population of 10,000. Present findings as perspectives, not statistics.

Examples

Mid-term review, West Africa. A DFID-funded governance programme in Ghana conducted 32 KIIs as part of its mid-term review, covering district officials, CSO representatives, community leaders, and programme staff. The interviews revealed a mechanism not visible in monitoring data: the programme's most effective activities were those where district officials participated as co-facilitators rather than passive recipients. This finding informed a design revision for Phase 2.

Rapid assessment, East Africa. Following a drought in the Horn of Africa, an OCHA-funded team conducted 15 KIIs with local government, NGO staff, and community leaders over 3 days to assess the most critical gaps in the humanitarian response. KII findings were triangulated with observation data and secondary data from satellite imagery analysis. The combined assessment informed resource prioritisation for the following 30 days.

Related Topics

  • Focus Group Discussions, a group method that produces different data than individual KIIs
  • Survey Design, the complementary quantitative method for representative data
  • Qualitative Data, the type of data KIIs produce and how to handle it
  • Mixed Methods Evaluation, how KIIs combine with quantitative methods for triangulation
  • Rapid Assessment, contexts where KIIs are used as the primary data collection method

At a Glance

Collects in-depth qualitative data from knowledgeable individuals to understand mechanisms, context, and perceptions that surveys cannot capture.

Best For

  • Understanding why outcomes occurred or did not occur
  • Capturing perspectives of decision-makers, experts, and community leaders
  • Supplementing quantitative data with explanatory depth
  • Rapid assessments and needs analyses

Complexity

Medium

Timeframe

1-3 weeks for instrument design, scheduling, and data collection; 1-2 weeks for analysis

Linked Indicators

19 indicators across 3 donor frameworks

USAIDDFIDUNICEF

Examples

  • Number of key informant types represented in the interview sample
  • Proportion of interviews with notes or recordings enabling triangulation
  • Degree to which KII findings confirm or contradict quantitative data

Related Topics

Core Concept
Focus Group Discussions
A qualitative data collection method that brings together 6-10 participants to discuss a specific topic, generating rich insights through group interaction and shared experiences.
Core Concept
Survey Design
The process of designing structured questionnaires and survey protocols to collect reliable, valid, and actionable data from a defined population.
Core Concept
Observation Methods
A systematic approach to collecting data by directly watching and recording behaviours, interactions, and processes as they occur in natural settings.
Term
Qualitative Data
Non-numerical information captured through words, images, or observations that reveals the how and why behind programme outcomes, providing depth and context to quantitative findings.
Core Concept
Mixed Methods Evaluation
An evaluation approach that systematically combines quantitative and qualitative data to provide a more complete understanding of programme effects, mechanisms, and context.
Core Concept
Data Quality Assurance
A systematic process for verifying that collected data meets five quality dimensions, Validity, Integrity, Precision, Reliability, and Timeliness, ensuring data is fit for decision-making.
Term
Rapid Assessment
A condensed data collection approach designed to generate actionable insights quickly, typically using streamlined qualitative and quantitative methods in time-constrained contexts.