Adaptive Customer Segmentation
Adaptive customer segmentation covers the changing behavior of customers in time. Using machine learning algorithms on CRM and other operational databases lets us discover timely change in customers' needs.
What can we do with Data?
Customer Unification
In CRM systems the data gathered from many different sources. In years the quality of the data decreases in such systems, and it becomes an issue to capture the exact number of customer. The similarity metrics from machine learning can be utilised to resolve these issues.
Social Media Analytics
Companies can track their campaign performances, brand awareness through analyzing social media posts. Advanced machine learning, natural language processing (NLP) techniques are utilized for performing semantic analysis.
Anomaly Detection
In our paper we worked on how to identify anomalies through periodic data. The common approach, applying threshold and observing deviation is less efffective than unsupervised method, Markov modulated Poisson process. It is adaptive to changes in time. The paper can be reached from that link.
Network Matters
It is important who you know even for your neighborhood. Not only financial capital, but also the social capital also brings valuable resources, opportunities to individuals, groups, communities, and places. We can extract it from the social structure emerging from their interactions. More on that work is here: The bridging and bonding structures of place-centric networks: Evidence from a developing country