Insights Engineer

Agentic research: Research where AI agents plan, field, analyse and report, with a human setting the question and reviewing the output.
AI-moderated interview: A qualitative interview run by a conversational AI that asks follow-up questions in real time.
Always-on research: Research that runs continuously and reports on a schedule instead of arriving as a one-off study.
Analytics engineer: A data role that turns raw data into clean, tested, documented datasets, usually in SQL.
Automate the second time: The rule that anything asked twice becomes a system, and anything asked monthly becomes a read that runs before anyone asks.
Automated quantitative research: Platforms that run advanced survey methods end to end, from questionnaire to sample to analysis, without a specialist vendor.
Brand tracker: A recurring survey that measures awareness, consideration, usage and perception of a brand and its competitors.
Codeframe: The set of themes or codes used to classify open-ended responses or transcript passages so they can be counted and compared.
Concept test: A study that puts a product, service or message idea in front of consumers to gauge appeal, relevance and purchase intent before money is spent.
Conjoint analysis: A quantitative method that infers how much people value each feature of a product by asking them to choose between bundles.
Consumer insights: The function inside a company that understands customers' attitudes, motivations and behaviour.
Consumer insights manager: The mid-to-senior role that runs a brand's research programme and its vendors. The insights engineer takes over this role.
Decision memo: A one-page document that pairs a finding with a specific recommended action and the person who owns it.
Decisions moved: A measure of insights value, counted as the business decisions that changed because of a finding and its recommendation.
Discussion guide: The structured list of topics, questions and probes a moderator follows in a qualitative interview or group.
Ethnography: Observing people in their own context, at home, in store or at work, instead of asking them questions in a research setting.
Forward-deployed: Working inside the business team that owns the decision, instead of in a central research function down the hall.
Hours returned: A measure of insights value, counted as the operator hours given back by automating a recurring task.
Hypothesis-first brief: A research starting point that names the decision, who makes it and the baseline before anyone touches data.
Implicit testing: Methods that measure reactions people cannot or will not report directly, such as response-time association tests.
Incidence rate: The percentage of people screened who qualify for a study. Low incidence makes fieldwork slow and expensive.
Insight agent: An AI agent that answers business questions from a company's past research and can run new research when the answer is not there.
Insight product: A deliverable that keeps working after it ships, such as a dashboard, an agent, a decision tool or a scheduled read.
Insights analyst: The traditional consumer insights role. Scopes studies, manages vendors, analyses results and presents the findings.
Insights engineer: A consumer insights professional who builds the system that answers a research question, instead of running another study.
Insights repository: A searchable, tagged store of past research, findings and raw data that the whole organisation can query.
Insights stack: The data sources, tools and systems an insights function runs on, seen as infrastructure and not as a list of vendors.
MaxDiff: Maximum difference scaling. Respondents pick the best and worst item from small sets, which produces a ranked list with real spacing.
Net Promoter Score: A loyalty metric based on one question. How likely are you to recommend us, scored 0 to 10.
Open-end coding: Assigning themes to free-text survey answers or transcripts so they can be counted and compared.
Qual at scale: Qualitative research run at sample sizes that used to be possible only in quantitative work.
Research design as code: Treating survey instruments, discussion guides, codeframes and analysis as versioned, testable, reusable files.
Research ops: The operational side of research, covering recruiting, tooling, consent, repositories and process.
Research panel: A pre-recruited pool of people who have agreed to take part in surveys and studies, usually for an incentive.
Segmentation: Dividing a market or customer base into groups that differ in needs, attitudes or behaviour so each can be targeted differently.
Social listening: Monitoring public conversation on social platforms, forums and review sites for mentions, themes and sentiment about a brand or category.
Synthetic panel: A group of synthetic respondents built to mirror a target audience.
Synthetic respondent: An AI-generated persona that answers research questions in place of, or ahead of, a human respondent.
Text analytics: Automated analysis of unstructured text, such as reviews, support tickets and open-ends, for themes and sentiment.
Triangulation: Checking a finding against more than one source or method before acting on it.