Singapore’s National Library Board is using data on elderly citizens’ reading preferences to better plan its library collections.
“The libraries collect information on the age of the borrower, the number of books that you borrowed, where you borrowed from, and the category of books,” said Daniel Lim, Data Science Consultant, Infocomm Development Authority. His team worked with NLB to develop and implement this project.
They analysed this data to create profiles of how library customers behave and found distinct differences in the reading habits of the elderly.
“One group of old people, they borrowed in the heartlands together with their grandchildren. And the other group went downtown; they tended to be retirees and they borrowed books on hobbies and social sciences,” Lim said.
The libraries at these locations are now able to plan different kinds of activities for the elderly. “This was very useful to the National Library Board because it helps them to plan what books they would stock in the libraries and what activities they would do”, he added.
The idea behind the technique is that librarians form mental models of who their typical customers are based on their intuition or anecdotal experience. The data analysis reveals new customer models that they would have otherwise missed out.