In this talk at ProductTank London, Ali Gulez, a data scientist at Trainline gives a lesson in data products and their impact on business. Ali takes us through the role of data science in an organization and dives deeper into the following key points:
- Data products
- Hierarchy of needs
Watch the video to see Ali’s talk in full. Or read on for an overview of his key points.
What exactly is a data product? A data product is a machine learning model that provides value for the customer as well as the business. Data products can be either customer-facing or under the hood, from the ‘recommended for you’ feature on Netflix to the fraud detection systems on our bank accounts or credit cards. No matter which type, the aim is to provide invaluable information for the business to meet its goals and appeal to their customers.
Ali takes us through various examples of how data products are used at Trainline as he breaks down the concept of segmentation. Customer segmentation using machine learning allows businesses to gather behavioral data and divide their customers into groups. They can also gain insights that allow them to develop new revenue models. Price predictions allow businesses to inform their customers about deals based on historical trends. This can lead to a bigger conversion rate for the business and a much happier customer.
Hierarchy of Needs
The key takeaway of Ali’s talk shows that there is no one size fits all model for creating data products or hiring data scientists. Each business will have different requirements and different outcomes they would like to achieve by using data products. From a product manager’s point of view, understanding the steps which are required to create effective data products will allow them to find the right skill set to meet the team’s needs.