August 4, 2016
Public libraries aren’t normally thought of as businesses. But like businesses, libraries require significant investments, have to operate within budgets, and need to understand their “customers” in order to carry out their mission effectively.
A group of 10 public library systems from around the United States recently participated in a study analyzing data from nearly 70 million checkout transactions involving 4 million library cardholders. The findings of the report will help these libraries tailor their services to their local communities.
Data Informed spoke with Danielle Milam, Development Director at the Las Vegas-Clark County Library District Foundation, about the study, the insights it revealed, and how those insights are being used to better serve library patrons.
Data Informed: What was the impetus for participating in the library usage study? What questions were you trying to answer? Were there specific business problems you were trying to address?
Danielle Milam: We don’t library like we used to. The public library today is an open platform for learning. We are evolving from a business of transactions to a business of experiences. There is growing demand for resources that bridge both digital and physical worlds. If we are able to make this transition successfully and align our services with the interests and motivations of people who use and need libraries, we stand to greatly improve and sustain our value and place in society.
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| Danielle Milam, Development Director, Las Vegas-Clark County Library District Foundation |
Another big challenge is maintaining a high-level of services with shrinking public resources. We have to do more with less.
So with that in mind, we teamed up with nine other libraries across the United States to conduct the industry’s first study that combined big data with market segmentation data to gather intelligence on customer characteristics and usage patterns.
How would you have addressed these problem(s) traditionally, and what made you consider data analytics as a way to approach this problem?
Milam: Public libraries traditionally have used expensive customer intelligence tools like town halls, surveys, and focus groups that give us a lot of information on a small number of people. With big data, we get a broad and detailed community overview of who is using our libraries and who is not. We get geographic and quantitative data that gives us insights on the complexity of our communities and the variety of our library customers. When we can identify the core customers with the highest use of library materials, we can find and attract new customers like them. If we understand the people and places, we can anticipate and shape the next generation of library services.
We chose big data analysis to understand our communities and customer base better. We also wanted to identify and understand the implications of demographic trends that are shaping our communities. How do we shift our business models to meet the needs of growing variety of Hispanic and single-parent households? How do the strategies of libraries that have robust use by wealthy households differ from libraries that work with a variety of low-income households?
Please take us through the process. What data sources did you analyze, what data did you provide for the study, and what insights did they reveal about your organization, your customers, and your community?
Milam: To complete the core customer analytics part of our project, we contracted with Fuzzy Logix to crunch the big data already available from CIVICTechnologies. This enabled us to quickly analyze community market segments as well as cardholder and core customer usage patterns at the 10 libraries.
The analytics revealed a wealth of hyperlocal data that now is used to develop strategies to expand our customer base among the predominant local market segments, to market services and programs more effectively based on customer preferences, and to design effective service strategies that are a match with local demographics, lifestyles, cultures, and community challenges.
The big “a-ha” insight from this study is that relevance is local. In the past, libraries would benchmark themselves with other libraries of a similar size, service population or demographics, or a similar operational budget. Now, each of the 10 libraries have incredibly detailed information on exactly whom they serve. They can look to other communities for service models and ideas, but survival depends on how well they cultivate and maintain their local customers and continue to create value for predominant local market segments. For example, although they are similar in size and demographics, this report showed big differences in market segments between Denver (a predominance of singles households) and Las Vegas (a predominance of family households).
What were the most surprising insights the data produced?
Milam: We were surprised to find notable alignment between the unique distributions of market segments in the general population and the market segments that make up library core customer and cardholder bases in each community. We don’t think many industries can show that they reach and are relevant to the variety of rich and poor, educated and uneducated, young and old, U.S. citizen and immigrant populations that regularly use American public libraries. For example, in Houston the public library found that Hispanics represent 28 percent of the city library’s core customers and 33 percent of its total library cardholders, even though they make up only 19 percent of the city’s total population. The state of Washington’s King County Library System learned that 42 percent of its core customers come from wealthy households.
What actions have you taken as a result of the data insights?
Milam: We are learning that using this granular local data makes our organizations surprisingly resilient, nimble, and flexible in times of rapid and disruptive change. We can pivot faster, and target resources and initiatives better. We can let go of old service strategies that have little impact. In Las Vegas, when we discovered that over 76 percent of our community is made up of 21 different kinds of family households, staff used the data to quickly shift strategies on collections, services, marketing, outreach, and new partnerships that strengthen the community ecosystem for pre-K, student success, workforce, and college pathways.
Overall, we have come to understand that we don’t have to be all things to all people. We are learning to use this big-data approach to drill down into those markets that matter. We can now measure our uptick in library use by specific market segments.
The study also gave our industry a wake-up call on the need to gather data on active library cardholders who are not checking out books or DVDs. Are they using the computer labs and downloadable products? What programs and trainings are they attending? Which segments are likely to migrate to new digital formats? What household segments might face barriers? We are working together now to address those questions and data gaps.
What results have you seen from acting on the insights the data revealed?
Milam: The results of this study have shifted the dialogue in our industry and communities. Staff feel empowered by good local data. Library systems have a new ability to develop effective community-wide strategies, while branch libraries can tailor to neighborhood conditions. It has helped public libraries reposition themselves as they provide deep data on community challenges, create effective change initiatives, and get a bigger bang from public investments and resources.
Source: Data Informed
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