Quantitative Research

What this covers

Quantitative research turns a question into a number precise enough to defend in a room that will push back on it: how large the opportunity is, which concept performs better, what price the market will bear, whether a campaign moved anything. The scope spans concept and product testing, brand and advertising tracking, pricing studies, usage and attitude research, and post-launch measurement — standalone, or run as a repeating wave. Every design starts from the analysis plan rather than the questionnaire: we work out what has to be cross-tabulated, and at what level of confidence, before a single item gets written, because a questionnaire drafted first tends to collect data nobody can actually read the way they need to.

When you need it

This is the right tool when the decision in front of you needs a defensible number rather than a narrative: sizing a market before committing budget, choosing between concepts before creative is locked, setting a price point before it ships, or confirming that movement in a tracked metric is real rather than noise. It is the wrong tool when the real question is why something is happening rather than how much — that is qualitative’s job, and the two pair well when a number needs an explanation sitting behind it, run sequenced or in parallel.

How an engagement runs

The decision the study has to support gets agreed first, then the analysis plan, then the questionnaire, in that order — reversing it is the most common way a study ends up returning data nobody can act on. Sample size is set by the precision you need at the level you will actually read results — total, by segment, by market — not by what is left in the budget once other costs are covered. Screening criteria and attention checks are specified up front and applied identically across every market and every wave, so a difference in the data reflects the market rather than a scripting inconsistency. Once field opens, completes are reviewed on a running basis for straightlining, speeding, and other patterns that indicate a respondent was not really engaging — caught and excluded before they reach a table, not after a client notices something off. For tracking work, the instrument and the weighting approach stay fixed wave over wave unless a change is agreed and documented, so movement in the numbers is comparable rather than an artifact of a changed method.

What you get

A cleaned and weighted dataset, banner tables built against the plan agreed before fieldwork opened, and a readout written for the person making the decision — it leads with the answer, not a walk through the method section. Raw data and a full method note ship as standard: sampling frame, weighting approach, fieldwork dates, response rates, and any deviation from the original design, all documented so the study still holds up to scrutiny months after delivery.