Using Google Analytics, Voyant and Other Tools to Better Understand Use of Manuscript Collections at L. Tom Perry Special Collections

[Excerpt] Developing strategies for making data-driven, objective decisions for digitization and value-added processing. based on patron usage has been an important effort in the L. Tom Perry Special Collections (hereafter Perry Special Collections). In a previous study, the authors looked at how creating a matrix using both Web analytics and in-house use statistics could provide a solid basis for making decisions about which collections to digitize as well as which collections merited deeper description. Along with providing this basis for decision making, the study also revealed some intriguing insights into how our collections were being used and raised some important questions about the impact of description on both digital and physical usage. We have continued analyzing the data from our first study and that data forms the basis of the current study. It is helpful to review the major outcomes of our previous study before looking at what we have learned in this deeper analysis. In the first study, we utilized three sources of statistical data to compare two distinct data points (in-house use and online finding aid use) and determine if there were any patterns or other information that would help curators in the department make better decisions about the items or collections selected for digitization or value-added processing. To obtain our data points, we combined two data sources related to the in-person use of manuscript collections in the Perry Special Collections reading room and one related to the use of finding aids for manuscript collections made available online through the department’s Finding Aid database ( http://findingaid.lib.byu.edu/). We mapped the resulting data points into a four quadrant graph (see figure 1)

Using Google Analytics, Voyant and Other Tools to Better Understand Use of Manuscript Collections at L. Tom Perry Special Collections

[Excerpt] Developing strategies for making data-driven, objective decisions for digitization and value-added processing. based on patron usage has been an important effort in the L. Tom Perry Special Collections (hereafter Perry Special Collections). In a previous study, the authors looked at how creating a matrix using both Web analytics and in-house use statistics could provide a solid basis for making decisions about which collections to digitize as well as which collections merited deeper description. Along with providing this basis for decision making, the study also revealed some intriguing insights into how our collections were being used and raised some important questions about the impact of description on both digital and physical usage. We have continued analyzing the data from our first study and that data forms the basis of the current study. It is helpful to review the major outcomes of our previous study before looking at what we have learned in this deeper analysis. In the first study, we utilized three sources of statistical data to compare two distinct data points (in-house use and online finding aid use) and determine if there were any patterns or other information that would help curators in the department make better decisions about the items or collections selected for digitization or value-added processing. To obtain our data points, we combined two data sources related to the in-person use of manuscript collections in the Perry Special Collections reading room and one related to the use of finding aids for manuscript collections made available online through the department’s Finding Aid database ( http://findingaid.lib.byu.edu/). We mapped the resulting data points into a four quadrant graph (see figure 1).Using_Google_Analytics.pdf: 29 downloads, before Oct. 1, 2020