Web analytics can provide interesting insights around readers engagement, content they like, promotions that attract their interest. It's easy to detect different types of behaviours by collecting and aggregating that information, but still hard to understand the motivations, needs and wishes that drive those behaviours.
How can we build an ethnographic activity on top of an analysis of web patterns to turn high-level clusters into real personas?
The analysis of patterns related to the interaction with app and web content has initially lead to the identification of several clusters, representing the different levels of user egagement in relationship to the type of content they consume. The clusters helped screen for a sample of research participants (50 in total), with the objective to ask them to share their experiences, stories and desires through a digital diary. The diaries generated a large amount of information (photos and comments), that was analysed through visualisations and maps in order to see differences and similarities in the response of the participants.
This analysis highlighted the presence of very different behavioural
models within the same clusters, and lead to the identification of seven
A final round of individual interviews was then conducted only on a smaller selection (one person per each type of persona) leading to an enriched understanding of their needs and motivations.
The final outcome is a set of personas as well as a replicable process that allows to move from a quantitative to qualitative understanding, and to leverage web analytics to structure an efficient ethnographic process.