Constructs & metrics

Constructs and metrics are the measurement framework of a study — the part that makes vDynamiq a research instrument rather than just a storytelling tool. The story is the wrapper; the framework is what actually gets measured, and it’s what keeps results comparable across every study group and persona.

The three levels

• A construct is what you are measuring — an underlying concept such as brand awareness, brand trust, satisfaction, or purchase intent. Constructs are the vocabulary of the research: they’re what you ultimately report on.
• A metric is a specific, measurable point within a construct — the concrete thing that produces a data point. A construct is typically measured by one or more metrics.
• A scene is how a metric is captured — a narrated, visual moment with an interaction that records the respondent’s answer.

ConstructWhat you measure — e.g. Brand trust

→

MetricA specific measurable point within it

→

SceneHow it's measured for the respondent

For example, the construct Brand trust might be measured by metrics such as “I would recommend this brand to a friend” and “This brand keeps its promises” — each of which becomes its own scene.

Why the framework comes first

vDynamiq builds the framework before it writes any scenes, because the framework is what answers your brief. When you describe your objective, vDynamiq derives the constructs and metrics that would actually answer it — the measurement plan — and only then designs scenes to capture them.

This is the reason you never start by typing questions in vDynamiq: the questions follow from the metrics, not the other way around. Starting from measurement keeps the study focused on what you set out to learn and prevents the scope creep that turns surveys into sprawling, fatiguing grids. You review and adjust the proposed framework like everything else — see Framework (build step).

The funnel: how constructs relate

Constructs are rarely a flat list. Many map to stages of a decision journey — for example awareness → consideration → preference → purchase. vDynamiq captures this ordering (a construct’s funnel position) and uses it to organise the framework and structure the analysis, so results read as a coherent journey rather than a disconnected pile of numbers.

This is what lets a dashboard present a brand funnel — showing where audiences drop off between stages — instead of an unordered set of scores. It’s especially powerful when combined with study groups: you can see how one segment’s funnel differs from another’s.

The shared-scale guarantee

Because a metric is defined once at the construct level, every persona’s scene for that metric measures it on the same scale. The scene shown to Arjun (Metro Gen-Z Male) and the one shown to Meera (Rural Female) may look completely different, but both emit a value for the same metric — so the aggregation layer can compare segments directly and roll every answer up to construct-level scores.

This single guarantee is what makes tailored storytelling safe for serious research: framing varies, measurement doesn’t.

How metrics become scenes

• One metric → one scene (with a variant per persona). Each metric in your framework becomes a scene that measures it.
• The interaction fits the metric. vDynamiq chooses an interaction type suited to what’s being measured — a ranking for priorities, a 0–10 scale for likelihood-to-recommend, an open voice answer for spontaneous recall, and so on.
• Answers roll up. Responses to a metric’s scene aggregate into that metric, and metrics aggregate into their construct — producing the scorecards you read on the dashboard.

Where to go next

• Scenes — how a metric becomes a respondent-facing moment.
• Interaction types — the ways a metric can be answered.
• Responses & aggregation — how metric answers become construct scores.