5 Reasons Why You Should Stop Asking Your Editors To Tag Articles
July 8, 2019

Manual tagging is dead. If you are still forcing your team to manually tag content, then you are wasting valuable time and money. Let me tell you why:

  • It’s hard to maintain consistency: even though your team might have clear guidelines on how to tag articles, there’s always room for human error. Also, maintaining and following those guidelines is quite difficult. For example, always tagging “Donald Trump” as “Donald J. Trump” as opposed to “President Trump” or “Donald Trump”. Maintaining consistency is crucial in data analytics to give objective and clear information on the performance of a certain topic.
  • It’s time-consuming: manually tagging each article takes a lot of time – especially considering the volume of content being published each day.
  • Takes focus away: instead of focusing on what they do best, i.e. writing, editors are wasting a lot of time over manual tagging of articles.
  • Lack of understanding: many individuals do not understand the value of article tags and their implications when it comes to analytics used to formulate content strategies. Therefore, these individuals do not put the required effort and diligence in their tags.
  • Subjectivity: when tagging an article manually, the process is biased and subjective, hence excluding niche tags that readers might actually be looking for.
  • It simply isn’t the solution for automating “Related Content“: using tags to try to automate Related Content produces unacceptable results mainly because of the points mentioned above. Using A.I.-based services is the only solution.

The solution: automate!

Tags and keywords in articles help readers dig deeper into related stories and topics, and give search audiences another way to discover stories. Those tags can also help newsrooms create new products and find inventive ways of collecting content. Also, by doing so, newsrooms can then refer to their site analytics to see whether the time invested in such stories is paying off in terms of engagement time and social sharing. Many publishers, such as The New York Times, have been adopting artificial intelligence in order to make tagging easier.

Using automation tools, such as Magnet, you can tag your articles seamlessly and consistently, all while saving your editors’ time and improving accuracy. In addition to automatic tagging, Magnet is used for understanding audiences, identifying subscription habits and patterns, and highlighting subscriber preferences.

An API is also available to automate tagging. Check out our fully RESTful API documentation here.

Interested in automating your tags? Get in touch today to book a demo.

Klangoo NLP
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