Cognistat partners with public sector agencies and socially-driven organisations to design better surveys, collect quality data, and turn evidence into action.
Cognitive Statistics & AI
Who We Are
CogniStat is a Melbourne-based data and evaluation consultancy. We specialise in the full data lifecycle — from survey and sampling design through to advanced analytics and program evaluation — helping our clients make decisions grounded in rigorous, reliable evidence.
We work primarily with public sector agencies, government departments, and organisations pursuing measurable social impact. Our clients come to us when the quality of data and methodology matters as much as the findings themselves.
Why CogniStat
We cover the entire data lifecycle, not just the analytics layer.
We design and control fieldwork quality ourselves — no outsourcing.
Rigorous quantitative techniques applied to real-world problems.
Deep familiarity with public and not-for-profit evaluation contexts.
What We Do
Each engagement draws on one or more of our core capabilities, tailored to your context and objectives.
Rigorous instrument design and statistically sound sampling frameworks that ensure your data represents the population you care about.
End-to-end fieldwork management with in-house quality controls, ensuring data integrity from collection through to delivery.
Advanced statistical techniques — from regression and multivariate analysis to predictive modelling — that surface meaningful insights.
Theory of change, impact measurement, and evaluation frameworks designed to demonstrate outcomes to funders and stakeholders.
Our Work
A sample of the work we do across sectors. Project details are available on request.
Government · Evaluation
Designed and executed a mixed-methods evaluation framework, including client surveys, service provider interviews, and outcome modelling against program theory of change.
Not-for-Profit · Survey Research
Developed a stratified sampling strategy and administered a large-scale community survey to inform a regional service planning process.
Policy · Analytics
Applied regression and segmentation modelling to administrative data to identify drivers of service uptake and inform targeted policy recommendations.
Insights & Resources
Articles, guides, and white papers on data methodology, survey practice, and evaluation.
Article
A well-designed survey instrument means nothing if the sample is biased. We explore common pitfalls and how to avoid them.
Read more →Guide
A practical guide to designing, fielding, and interpreting surveys in government and community service contexts.
Download guide →White Paper
How to construct a theory of change and evaluation framework that satisfies funders, informs practice, and holds up to scrutiny.
Read more →Get in Touch
Tell us about your project or research challenge. We'll respond within one business day.