The 3 ideal use cases for your first data science project
There are three use cases that prove especially popular with our customers. What sets them apart? First of all, they are relevant across industries, and their results are easy to understand. Secondly, you can use data already available in your organisation. There’s no need for additional efforts of data gathering. Finally, you can prepare them in no time with Dataiku’s AutoML. Let’s take a look.
Churn prediction - Predicting which customers are likely to stop buying the company’s products or services during a defined time frame. Reducing churn is a straightforward way to protect revenue, especially for businesses with high customer acquisition costs. Later, you can combine churn prediction with uplift modelling to identify those most likely to be persuaded by a marketing initiative.
Customer segmentation - divides the company’s customers into groups based on specific traits and factors they share. You can use segmentation for personalising targeted marketing campaigns aimed at customers with high churn risk. Personalisation also helps boost customer loyalty and conversions.
Real-time fraud detection, e.g. on credit card transactions - a predictive model automatically flags transactions as potentially fraudulent, which can be either blocked or sent for further investigation. Machine learning approaches yield fewer false positives than traditional rules-based systems and better adapt to new fraud patterns. This leads to less regulatory risk, reduced human workload and better customer satisfaction.
