Quantitative Research

KPI

KPI

Last updated

Qualitative insights at the speed of your business

Conveo automates video interviews to speed up decision-making.

Definition:

A key performance indicator (KPI) is a quantifiable measure used to evaluate progress toward a specific business goal, whether at the organisational, team, or campaign level. In research and insights contexts, KPIs often include metrics like brand awareness, customer satisfaction scores, concept appeal ratings, or purchase intent. Effective KPI selection requires clarity about what success looks like before a study launches, not after results arrive. For qualitative research teams, KPIs help frame the questions worth asking and give stakeholders a shared reference point for interpreting findings. Without that anchor, even rich qualitative data can struggle to land in a boardroom.

How Conveo Does It

Conveo helps enterprise teams connect qualitative findings directly to the KPIs that matter to their stakeholders. AI-moderated video interviews launch in under 30 minutes and return findings in days, so teams can track KPI-relevant signals like brand perception or concept appeal while decisions are still open. Every insight traces back to a real participant who said it, with verbatim quotes and video clips that make KPI movement legible and credible to leadership, not just the insights team.

Frequently asked questions.
In market research, a KPI is a specific, measurable outcome the study is designed to inform or track. Common research KPIs include brand awareness levels, purchase intent scores, concept appeal ratings, and customer satisfaction measures. Defining KPIs before fieldwork begins keeps the study focused and ensures findings connect directly to the business question, rather than generating interesting data that never reaches a decision.
KPIs give qualitative research a clear destination. Without them, discussion guides tend to sprawl and stakeholder reports become hard to act on. When a team knows the KPI it is trying to understand, such as why satisfaction has dropped or what is driving low concept appeal, it can design a study that surfaces the right depth of explanation. KPIs also help researchers frame findings in language that resonates with commercial stakeholders rather than staying inside methodology.
All KPIs are metrics, but not all metrics are KPIs. A metric is any measurable data point, such as interview completion rate or session length. A KPI is a metric that has been selected because it directly reflects progress toward a strategic goal. In research, the distinction matters because teams often collect dozens of data points but need to agree on which few actually signal success. Treating every metric as a KPI dilutes focus and makes stakeholder reporting harder to act on.
AI is compressing the time between a KPI shift and a credible explanation for it. Traditionally, a brand tracker might flag a drop in purchase intent weeks before qualitative work could explore why. AI-moderated research closes that gap, running interviews at scale and returning thematic analysis within days. Teams can now treat KPI monitoring and qualitative diagnosis as a continuous loop rather than two separate projects with a six-week gap between them.
Enterprise teams typically anchor continuous research programs to a core set of KPIs, such as brand health, customer satisfaction, or innovation pipeline strength, and design study waves around tracking movement in those measures. When a KPI shifts, qualitative work explores the cause. Conveo's Storylines capability supports this directly, running research in chapters and waves so findings connect across studies and teams can see how KPI-relevant themes evolve over time rather than treating each study as a standalone event.
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