The potential and issues in data-driven development of web personas

The concept of personas that represent the key audience segments of a service, product, site, or a brand has been widely used in marketing. As of lately, personas are often used in digital services design and development. However, there are some frequent errors and issues that designers and developers come across in the process of developing realistic personas. Namely, personas are sometimes developed based on irrelevant data (e.g. statistically insignificant dataset), or have been developed based on assumptions, inadequate analyses or, most often - intuitively. Another issue is that once created, personas cannot be easily updated. There is great potential in using big data technologies to tackle these issues since it enables analyses of large amounts of data to gain insights into real user behavior patterns that lead to better business decisions. This paper explores the possibilities for developing data-driven web personas based on real user-data with the aim to save time in comparison with current data collection methods and also to enable easier updates. The preliminary study is presented using a dataset from an e-business site. The research results highlight the great potential of developing data-driven web personas based entirely on interactions between real users and a webshop, but also a number of identified issues in the process.