Don’t lose learners with bad content tagging

• 3 min read

Tag content better for improved eLearning results

Recently, we talked about the importance of properly tagging content in order to build a content repository that is relevant, accessible, and builds tribal knowledge.

There, we talked about the “dos”. Now, we need to talk about the “don’ts”.

In content tagging, it can be tempting to overtag. But, in applying tags, our goal has to be targeted.

Good tagging is:

  1. Relevant to our audience
  2. Accessible
  3. Focused and timely

With that in mind, here are three key mistakes made that result in improper (and unsuccessful) tagging.

1. Content is overtagged

Another way to make content tagging irrelevant is to over-tag content. This means applying ten thousand tags to one piece of content when it is only specifically related to, maybe, three or four key, relevant content areas.

Just as you keep tags limited, keep them focused. If you have a course on grooming a Golden Retriever and you tag it with the following terms:

  • Dog
  • Retriever
  • Golden Retriever
  • Hunting dogs
  • Bathing
  • Grooming
  • Long-coated breeds
  • Detection dogs
  • Upland-game hunters

Well, you get the picture. While there is something to be said for specificity, too much specificity can actually be a bad thing, because as soon as we enter the realm of tagging content, we enter a virtual rabbit’s hole of how many terms we can apply to content.

We must return our sense to the mind of someone engaging with a course and limit how many tags we apply to content. And, also, when we realize tagging is becoming so specific that we are creating new tags for net new content, that’s a problem. Tags need to be relevant to multiple forms and formats of content in order for them to be used effectively.

It also needs to be understood that tags live with content through the ages, and will ultimately help AI better understand how content is accessed and understood.

So, when applying content tags, don’t invent new tags because the content asset falls outside of the box of common usage. Sixty tags will ultimately serve the organization better than 600, so curtail tagging to a few descriptive parameters that help describe what the content is ultimately about, and how it will serve its audience.

2. Audiences are ignored

Far too frequently, content tagging ignores its audience. When a learner wants to find a certain piece of content, they will enter a list of search terms, just as we do in YouTube when we want to learn a new recipe or find out how to build a piece of Ikea furniture. And we often get to the results we need through that kind of channel because the content is tagged well. Because these platforms understand their audience.

Poor, improper content tagging, alternatively, ignores the audience base. It leaves tagging in the hands of the content curators and authors, in the backend, who have a limited understanding of the audience’s key priorities and learning needs.

When applying tags, we need to think with a “search” mentality. Put yourself in the shoes of a learner: if you were seeking a particular learning content resource, what kinds of search terms would you enter? Those are the terms you will want to apply to content as tags in order to make the content as easily found as possible.  

3. It’s linked ineffectively

When we apply tags to content, we aren’t simply trying to describe individual courses effectively. We’re also trying to tie one piece of course content to related pieces of course content.

If a learner is engaged in a job-critical course on environmental management, for example, they’ll want to have easy access to related courses on environmental management. When we bin content effectively, we apply content tags that essentially link one piece of content to an array of content that is related or supplementary to the content they’re consuming.Have you seen how effortless great content tagging can be? Try Docebo free for 14-days to witness it first hand.