Using Big Data to Address Local Needs
Library staff are constantly looking for ways to better reach and serve their local communities. From post-event surveys to embedded librarianship to collecting circulation statistics, libraries have different strategies for gathering information and measuring service success. Market segmentation and big data, two terms popular in the corporate world, can also help libraries make informed decisions about collections and services.
CIVICTechnologies, a company that provides location-based web-software solutions to libraries, published the first big data study on library services in March 2016. “Core Customer Intelligence: Public Library Reach, Relevance and Resilience” investigates the habits of core customers across ten library systems in the United States[1]. The goal of the study is to help libraries retain core customers and reach and recruit new audiences.
Collecting Core Customer Intelligence
The report defines “core customers” as a library system’s top 20 percent of active cardholders who have checked out the most physical items. The ten library systems in this report were selected because they currently use CIVICTechnology’s CommunityConnect, an application that integrates library data with demographics[2].
Together, these ten library systems serve 7.8 million people. The report looked at four million cardholders who made 6.74 million book and physical media checkouts in 2014 (the privacy of the individual customers was protected). Each library’s customer and checkout data was aligned with census block data, and an outside firm performed the analysis. The report also defines customer types, a key tactic in market segmentation, such as “Green Acres” (rural upper-middle-class married couple families) and “NeWest Residents” (urban lower-middle-class mixed families)[3].
What the Report Found
As one might expect, core customer characteristics and behaviors are complex and unique from library system to library system. And even within individual library systems, the report found diversity within that top 20 percent of active cardholders. For example, some metro areas, such as Las Vegas, had “fragmented, diverse segments” of customer behavior.
Because of this diversity across systems, the report finds that the “business of public libraries is hyperlocal.” In other words, there is no one-size-fits-all model for core customer characteristics[4].
The report recommends that libraries use core customer intelligence do the following:
- Reach—The report found that libraries have core customers in every major community market segment. Data can help libraries gauge how effective their reach is.
- Relevance—The study found that libraries have relevance across a variety of customer segments. Libraries can benchmark and measure the strength of library connections to the community.
- Resilience—Data gives libraries the tools to stay flexible and adaptable in complex community and business environments.
The next steps from this report might be the creation of a toolkit or guide to exploring big data collection and reporting for public libraries. The report provides some excellent framework for getting started, but staff whose libraries did not participate in the study might wonder how they can use these same tactics. With some direction, other library systems can be empowered to make data-informed decisions as well.
Diving Even Deeper Into Library Data
While this report only covers ten library systems, it opens up a conversation about how libraries can borrow strategies from the sales and marketing world and it apply it to their own communities. Public Libraries Online’s Kristen Whitehair writes that there is great potential for crossover between the field of data science and libraries[5]. As libraries become more customer service-oriented, this sort of research is vital for longevity.
It would be fascinating to continue this research and expand it to digital items, such as e-books or audiobooks, library online database use, or even programming. Library Journal’s Lisa Peet interviewed some of the participating libraries, who shared that they’d like to see a similar study on these various facets of library service[6]. Hopefully this initial study helps pave the way for libraries to continue learning more about the customers they serve.
References
[1] Mark Futterman and Danielle Patrick Milam, “Core Customer Intelligence: Public Library Reach, Relevance, and Resilience,” CIVICTechnologies, March 2016.
[2] Ibid.
[3] Ibid.
[4] Ibid.
[5] Kristin Whitehair, “More than Buzz Words: Big Data and Data Science,” Public Libraries Online, May 9, 2016.
[6] Lisa Peet, “Core Customer Study Analyzes Library Demographics,” Library Journal, March 29, 2016.
Tags: big data, library data, patron data
