Data Clustering
Data CLUSTERING
Simbyte can help you group your dataset into clusters that contain similar characteristics. Clustering data is useful for exploring data, identifying anomalies such as duplicates, fraudulent behaviour or demographics, and creating predictions such as what may a customer purchase net.
Simbyte
Simbyte utilises advanced statistical methods and machine learning to analyse and cluster your data to help you with:
Use Cases
We use sophisticated algorithms to identify relationships between records that would not be normally derived through casual observation.
Demographic Clustering
Customer clustering by demographic/speciality to make the best use of your sales representatives
Demographic Clustering
Customer clustering by demographic/speciality to make the best use of your sales representatives
Demographic Clustering
Customer clustering by demographic/speciality to make the best use of your sales representatives
Demographic Clustering
Customer clustering by demographic/speciality to make the best use of your sales representatives
ADVANCED CUSTOMER SEGMENTATION
Almost any dataset has data that we can derive new insights from. Whether it is optimising your workforce, enhancing customer experience or identifying new markets, we have experience and the technology to identify.
We have had interesting insights from seemingly unrelated datasets that have ended up in businesses making changes in key areas. What are you missing?
