Understand customers behaviors to improve sales
Use unsupervised learning to segment and understand customer behaviours.
Understand the most important factors that impact customer churn and prescribe an actionable strategy.
Identify associated product groups to “recommend” products for cross-selling.
Analyze structured and unstructured survey data to deepen your customer understanding .
Discover Graphext endless value and see first hand how it can change your business.
Taking on an investigation into the adverse reactions associated with the COVID-19 vaccination rollout in the USA, our team were aware of the increased need for transparency whilst conducting our analysis. This article documents the methodology behind our study of Vaccine Adverse Event Reporting System (VAERS) data.
Modelling data from the Vaccine Adverse Event Reporting System (VAERS) - a US government-sponsored vaccine reaction monitoring service - our team set out to investigate reports of adverse health effects related to the seismic rollout of the COVID-19 vaccination programme in the USA.
Attempting to discover the most influential features of a loan application when considering risk, our team built a model using the features of a loan application to predict whether an applicant would have a good or bad risk rating.
Our team set out to build an exceptional football team for less than 100M Euros. Using data provided in the FIFA 2020/2021 dataset - the video game - we built a prediction model in order to find the key performance attributes for each position. Then, we used this to pick out a team of excellent but undervalued players.
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