In just a few months’ time, the pandemic sped the adoption of digital technologies by several years. 

In Hum’s State of Personalization Report for Publishers, we explored the ways that constant connectivity and increased capability for digital connection have also changed the way consumers behave and consume content. 

The publishers that aren’t able to transition from a one-size-fits-all approach to a personalized one, tailoring content directly to each reader, will struggle to stay competitive. 

One of the key technologies helping organizations navigate this shift is AI and machine learning. Artificial intelligence and machine learning refer to algorithms that are continually collecting and analyzing member behavior, recognizing patterns and predicting what a user’s next step might be. 

Here are three key ways artificial intelligence is helping scholarly publishers: 

Automating manual tasks

One of the most common use cases for artificial intelligence across industries is the ability to automate manual, repetitive, or time-consuming processes, reducing the strain on your team’s time. Publishers can use AI to quickly identify papers that don’t meet journal standards and automate several of the tasks that are important in improving the quality of published papers. 

There are emerging AI tools that can help publishers::

  • Run copyright and plagiarism tests
  • Flag inaccurate or incorrectly attributed data
  • Conduct reference checks
  • Determine the length of time required to read a paper
  • Translate digital content into other languages

When implemented correctly, artificial intelligence augments your team’s ability to publish high quality papers, knocking out the manual and mundane tasks and giving your team greater bandwidth for decision-making.

Simplifying the peer review process 

Artificial intelligence doesn’t just save time for publishers in-house; it can also add efficiencies when it comes to peer review. When AI is used to validate statistics and summarize the conclusions of research articles, the entire peer review process takes less time. 

Machine learning can even help scholarly publishers with the recruitment process by leveraging first-party data to identify top author or reviewer candidates, showing those with a higher likelihood to submit or review. 

Recommending new content

Your readers - the younger ones, in particular - are increasingly plugged into platforms like TikTok, Netflix, and Amazon that deliver hyper-personalized recommendations of what to watch, read, or buy next. 

Pair that with decreased attention spans and the constant barrage of media we filter through daily, and you’ll begin to understand why smart content delivery is setting great publishers apart from the rest. 

In order to serve people the right content, publishers have to be in tune - not only with what readers have engaged with in the past - but in predicting what they’d like to see next.

Artificial intelligence and machine learning make it possible for publishers to personalize each reader’s journey by delivering content selected just for them, based on reading habits and preferences. (This, in turn, bolsters engagement, which drives reader retention, subscriptions, and advertising revenue)

Natural language processing (NLP) is a type of AI that allows computers to understand speech or text as written language. Hum’s content intelligence tools leverage NLP to analyze and learn from your full content library, identifying key themes, topics, taxonomies, keywords, and tracking engagement across key segments. 

 

Artificial intelligence has massive potential to personalize your readers’ experience and keep them engaged. As technology continues to evolve and organizations seek more sophisticated ways of leveraging first-party data to build relationships with their readers, the opportunities to apply AI and machine learning will only expand. 

Interested in learning more about how reader expectations are changing and see other tactics publishers are using to drive personalization for readers? 

Download your free copy of the State of Personalization for Publishers report!