Universal Solutions Update

Explore, Monitor, Analyze: AI Tagging

Related products: Explore Monitor Measure
Explore, Monitor, Analyze: AI Tagging

Supercharge your media monitoring with an advanced tagging experience powered by machine learning!



What is it?

Our new content tagging experience leverages AI Large Language Models (LLMs) to suggest content categories based on the document content. Wherever you can find a universal content stream including Explore, Analyze, and Monitor, you can now tag your content with AI-powered suggestions based on existing tags. Internal Meltwater note: AI tags are being rolled out in 10% increments to all Monitor, Explore, and Analyze content streams over a period of two days. All users are expected to see AI tags by the end of Friday, July 14.


What’s the value? 

For users tasked with media monitoring, tags allow you to categorize content based on outcome, need, destination, or campaign type. Spend less time processing, and more time analyzing and actioning your content. After you’ve tagged content with your own tags, the suggested tags will make recommendations consistent with your categorization.

  • Boost your productivity and review a greater volume of content by categorizing it swiftly and intelligently.
  • Process and organize your tags in a way that seamlessly integrates with your unique workflows.


How does it work? 

You can find AI tag suggestions on content in content streams found in Explore, Monitor, and Analyze. After applying your own tags, our system will offer suggestions that match with your categorization. Simply use the toggle to activate your AI tag selections. If desired, you can easily disable AI tags by deselecting the toggle button.

More information about AI tags can be found here.


As long as the toggle is on, our AI technology will continue suggesting tags for you to use. 



Once your AI tag suggestions start appearing, click the tags in the perforated lines to apply the AI-suggested tags.

Bulk tagging is simplified with AI tag suggestions elevated to the top of the list. Select your AI tags, then hit apply to tag multiple content selections. 


Notes and limitations

AI tagging works best for consistent/high volume tag users, and accuracy increases the more content is tagged. 




Q: How do I get the most out of the AI tagging feature?
A: AI Tags work best if you consistently tag similar content with the same tag.. The more you tag, the faster we learn, and the better your suggestions will be.


Q: Is it possible to have a tag always show up for a given search? Example, if I want to tag all articles with a topic even if the topic isn’t contained in the article?
A: Not currently. Today, the content of the article or post determines the suggested tag. In the future, customized suggestions will be available.


Q: Will the AI tagging feature suggest new tags based on the document content?

A: No. After you’ve tagged content with your own tags, the suggested tags will make recommendations consistent with your categorization. In other words, the suggested tags will not be new, rather they suggest existing tags. 


Q: Why are there no AI tags showing up after I click the AI tag toggle?

A: As tag suggestions are based off of your existing tags, you must have at least one saved tag in your account for AI tags to work.


Q: Will my tags be used to train AI models?
A: No. Meltwater uses internal AI Large Language Models to suggest tags based on your existing tags.


For more information about how Meltwater uses AI, click here.

I’m wondering: how are others using tags? I’d like to start tagging content regularly, but I’m unsure of what tags to implement to optimize my results.

For context, I work at a PR agency with clients in the financial services space, and we have unique searches for each of our clients. I’m thinking I could tag based on product, topic, outlet...but should I make unique tags for each client or use the same tags across all my searches?

Any insight would be appreciated!


Is this covered in one of the Academy courses as well?