Usage and Predictive Analytics for Academic Publishing
The scholarly publishing sector been restructuring since the 1970's ; digitized content started to replace the printed work and then the internet came as the absolute disrupting force in information flow. Yet, participating institutions like publishers, libraries, universities and aggregators, proved flexible.
While the basic principles of scholarly ecosystem survive, technological advancements such as big data analytics, have transformed once again the face of academic publishing. Publishers, libraries, universities and aggregators across the world have been using COUNTER usage reports to demonstrate the value of their resources and offerings.
As the Office of Scholarly Communication, of the University of California state:
Transformative agreements represent a new way of doing business with publishers. Effective cost reduction proposals require deep insight into the value of content to a library’s users and the marketplace in which the publisher is operating. To support negotiations for these dual aims, libraries must develop data analysis tools and strategies that go beyond the standard return on investment that is commonly used to measure the value of traditional subscriptions.
COUNTER reports ensure that publishers and vendors are able to (a) provide usage data to their customers in the desirable format, (b) benchmark the different delivery channels, (c) create "usage personas" via aggregated data and (d) know more on usage patterns.
In addition, COUNTER reports help librarians to (a) benchmark vendors, (b) review the value gained from subscriptions (i.e. cost-per-download, cost-per-use, etc) , (c) take informed decisions, and (d) plan future infrastructure effectively.
Getting ahead of the competition with predictive analytics
The academic publishing stakeholders also exploit predictive analytics in order to serve their users in the best way possible. In fact, studying datasets like COUNTER reports, citation data and subscription costs, can help them distinguish from competition by
- identifying the key drivers of business performance: assessing the impact of editorial and publication data can allow publishers to discover the future leading authors and researchers, giving them thus a significant advantage in booking “first-to-publish” or even exclusive editorial rights. Furthermore, diving into search terms or thematic patterns, will permit them to pinpoint the “next best thing” into research topics and even plan the creation of new journals.
- gaining meaningful insights on new approaches to monetize content: incorporating data analysis will support negotiating teams to set up open access models and also allow publishers to optimize customer experience by providing the appropriate, even unique, content to the right audience, via the optimal channel, at the right price and on time.
Resources:
- Project COUNTER
- Fyfe, A. & Coate, Kelly & Curry, S. & Lawson, Stuart & Moxham, Noah & R?stvik, C.M.. (2017). Untangling academic publishing: A history of the relationship between commercial interests, academic prestige and the circulation of research.
- Francis Dodds, The future of academic publishing: Revolution or evolution revisited, Learned Publishing, 10.1002/leap.1258, 32, 4, (345-354), (2019).
- Negotiating with scholarly journal publishers: A toolkit from the University of California
- Photo by Chris Liverani on Unsplash