Statistical techniques

mathematics computation

Are algorithms evil?

None of us can have failed to notice the recent debacle over Ofqual’s (the Office of Qualifications and Examinations Regulation) use of an algorithm to predict pupil grades. Once again, ‘algorithm fever’ has generated a flurry of news articles questioning whether we are sleepwalking into a dystopian future where human expert decision-making is replaced with …

Are algorithms evil? Read More »

An overview of the four main approaches to predictive analytics

This infographic provides an overview of the four main families of approaches to predictive analytics. Prediction encompasses applications that aim to estimate or predict the values of a key target field. Segmentation refers to techniques such as cluster analysis which attempt to find the most ‘naturally occurring” groups within a dataset. Association modelling discovers groups …

An overview of the four main approaches to predictive analytics Read More »

7 things you need to know about key driver analysis (KDA)

In most businesses it’s not enough to simply be measuring outcomes like customer satisfaction, sales, customer churn rates, subscription renewals, customer loyalty, cancellation rates and so on. To gain competitive advantage you also need to know what’s driving those outcomes. Which aspects of the service you provide most influence how likely someone is to renew …

7 things you need to know about key driver analysis (KDA) Read More »

What do we mean when we talk about data modelling? An overview of different types of models

The real world, whether it be the physical world, for example machines, or the natural world, for example human and animal behaviour, is very complex with many factors, some unknown, determining their behaviour and responses to interventions. Even if every contributory factor to a phenomenon is known, it is unrealistic to expect that the unique …

What do we mean when we talk about data modelling? An overview of different types of models Read More »

What do your customers care about most? Using key driver analysis to find out.

After basic significance tests, T-tests, Z-tests and so on, key drivers analysis (KDA) is probably the second most popular statistically-based technique in market research. Given an outcome of interest a KDA gives us a measure of the relative importance of a set of attributes (potential drivers).Typical outcomes of interest in research are: Satisfaction – customer, employee etc. Purchase intent – how …

What do your customers care about most? Using key driver analysis to find out. Read More »

Scroll to Top