Due to agreements in place we are unable to include the name of the brand featured in this case study.
With a wealth of data and customer touch-points, the client was looking to better understand their customer requirements and behaviours through predictive data analysis and modelling techniques.
Following a competitive tender process, KeyElement was appointed as the technical partner to design and implement a new predictive data processing platform. In-depth analysis of customer data saw over 8 million customer records analysed. This allowed us to gather over 150 user requirements for the predictive model.
Using various data modelling & reconciliation techniques and an agile working process, we developed several predictive models to segment and generate customer communication lists. Constant communication and review with the client was essential to refine and optimise the data models and to ensure local legislation was met.
With the nature of the customer data being processed, robust security and traceability was a key requirement of the project. A multi-layered security approach was adopted to ensure access to sensitive information was limited to only essential personnel with full auditing and logging processes in place.
Our agile development process allowed us to get to a minimum viable product within a 32 week period. A massive positive impact of this was the ability to directly measure the accuracy of our predictions against new customer activity and behaviour. A continued iterative process of review and refinement over the following 6 months increased the accuracy of the models and the quality of the data.
With delivery of this solution, the client saw an increase in compliance and accuracy of target data list resulting in increased throughput and revenue.
We offer a range of data analysis and predictive modelling services. If you would like to discuss your requirements with one of our consultants, please get in touch .We would love to find out more about your project!