These days most companies are collecting Data to improve the nature of their business. Once Data has been collected, they need to structure and get value out of it.
Predictive Analytics is one popular technique to find value of out the given historical data, extract unseen patterns, and make predictions about the future outcomes using analytical techniques such as Statistical Modeling and Machine Learning.
Predictive Analytics can be applied in different industries such as utilities, financial institutions, construction sectors, healthcare, customs, and many more.
Predictive analytics follows a series of steps:
What are some of the use cases in Predictive Analytics?
- Customer segmentation: Understand your customers and improve their experience.
- Fraud detection: Implementing a strategy for automatic detection, prediction, and discovery of unusual patterns using historical and external Data.
- Recommendation system: Leverage Machine Learning and AI techniques and strategies to adapt recommendation to each of your customers.
- Credit scoring: Using Machine Learning techniques in order to determine your customers creditworthiness.
- Failure probability modeling: Using analytical techniques, using historical data and environmental data to predict failure before it happens.
- Demand forecasting: We build robust models that uses historical data from internal and external factors to respond to your business supply needs faster and more accurately.
- Anomaly detection: You might have data points or observations that deviate from normal dataset behaviour which shows critical incidents or unusual patterns. Using Machine Learning and statistical techniques, we can help you detect anomalies from your historical data.
- Churn prediction: Using Machine Learning techniques in order to predict which particular customer is at high risk of churn.
- Sales forecasting: Using statistical and Machine Learning methods, we can help you forecast your sells from historical data.
- Crime prediction: Using historical crimes data, it is possible to predict the probability of when and where the crime might happen.
From importing Data from different sources, integrating, cleaning to developing an accurate prediction model, our team of Machine Learning and Data Science experts will help you to create a fully-automated model to address your business needs.