Two kinds of evidence.
One closed loop.
Qualitative research is the core of this practice. But paired with the quantitative infrastructure of the DataDrives data practice, it becomes something no standalone agency offers: findings that get verified, on the record.
Qualitative: the why
- Moderated usability sessions: watch users succeed, struggle, abandon
- Discovery interviews: needs, mental models, jobs-to-be-done
- Field studies: in-context reactions at the moment of use
- Benchmark studies: standardized scores from real task performance
Quantitative: the proof
- A/B test design and analysis: hypotheses from research, verdicts from data
- Funnel & behavioral analysis: Adobe/Google Analytics, session replays, heat maps
- KPI dashboards: Power BI and Tableau builds your leadership already reads
- Tracked benchmark scores: UMUX-Lite and task success, release over release
A worked example.
Checkout completion falls sharply on mobile. The KPI tracker surfaces it no one had to go looking.
Data practiceModerated sessions on that exact flow reveal users can't tell whether their payment method saved so they quit.
Research practiceThe team ships a clear save confirmation. Completion recovers within two releases verified on the same tracker.
Both, on the recordA/B testing fits the same pattern: research generates the hypothesis and the test variants, the data practice runs the measurement, and the verdict is unambiguous.
Hire both halves separately, and the loop never closes.
A research agency never sees your funnels. An analytics consultancy never hears a user speak. Under one roof, every finding has a metric waiting to verify it one contract, no integration gap.