Marketing claims require validation - we provide the statistical basis.

This is the title of the case study that should take up no more than a few lines.

computer_meeting_marketing_small
How does your product compare to competing brands - as good, or demonstably better?
This is the space for a nicely written and engaging synopsis that will entice people to read.

Client: Alba Science
Date: 2006 to present

Client: The London Fire Brigade
Date: September 2018

Marketing claims require proof. While these might be quantified by consumer trials, their veracity ultimately rests on solid statistical analysis - we provide rigourous analysis, whatever flavour required.

What we do about it

A good consumer product study is conducted very much like a pharmaceutical Randomised Control Trial (RCT). There is randomised treatment allocations, double/triple-blinding, appropriate blocking, placebos/controls, power analyses, pre-defined Statistical Analysis Plans (SAPs) and protocols, etc. Subsequent analysis is similarly treated with the rigour of a clinical trial - ultimately providing defensible comparisons of treatments, estimation of effect sizes and due inferential care.

Final claims of "treatment A is better than treatment B", "X% of subjects displayed improvements" are on a firm basis - fully defensible and robust under scrutiny.

Some technical bits

The studies here are typically consist of repeated measures on subjects over time, often with within-subject treatment comparisons. Modelling is typically via mixed models (perhaps generalised) or similar (Generalised Estimating Equations - GEEs) to account for correlated errors. Problematic responses may call for computer intensive inference e.g. block-bootstrapping. Studies frequency have a subject perception component, leading to discrete choice modelling.