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3 min read

Cluster Tags with AI - A Simple Approach

How often have you been in a situation where you didn't know which tag to choose, given the incredible number of tags in almost every possible context?

From blog posts to knowledge bases, tags create meaningful groupings that help readers (and search engines) find what they need. However, even the most meticulous taggers can misspell, duplicate, or slightly vary how they label content - leading to cluttered data and the potential loss of valuable insights.

AI-powered clustering can solve this problem by automatically grouping similar tags together, minimising inconsistencies and providing a clearer, more accurate taxonomy for your content. In this post, we'll explore how you can use AI (specifically GPT) to cluster your tags, and why it's important.

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Why Clustering Your Tags is Invaluable

  1. Consistency
    Inconsistent tagging is often the biggest culprit behind messy data. Tags like gpt4, gpt-4, GPT4, and GPT-4 all refer to the same topic but appear as separate entities in your system. Clustering and merging or aliasing them ensures that you don’t miss relevant content just because of a typographical or formatting difference.
  2. Better Discovery
    When tags are well-organized, it’s easier for readers (and you, as the author) to discover related content. This can increase your content’s overall engagement, as users are more likely to explore other pieces that share a relevant tag.
  3. Efficient Content Strategy
    By clustering and merging tags, you can more accurately analyze which topics are trending and how much coverage each category has. This leads to better data-driven decisions about your next piece of content.
  4. SEO Benefits
    Search engines reward well-structured sites where tags are consolidated. Instead of scattering your SEO potential across dozens of near-identical tags, clustering them into core categories can boost your content’s visibility.

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How It Works: A Simple, GPT-Powered Approach

1. Gather All Unique Tags

Start by exporting a list of unique tags from your blogging platform, CMS, or database. For instance, you might end up with something like this:

[
  "AI",
  "Artificial Intelligence",
  "ChatGPT",
  "chat gpt",
  "GPT-4",
  "gpt4",
  "content marketing",
  "Content Marketing",
  "SEO",
  "Search Engine Optimization"
]

2. Prompt GPT to Cluster Them

Using a prompt-based AI tool like GPT, you can provide instructions to group similar tags. A sample prompt might look like this:

Prompt to GPT:
I have a list of tags. Please cluster them by similarity and format them in a JSON structure where each cluster is a key, and the values are the related tags. If possible, suggest a primary tag name for each cluster.
Tags:
AI, Artificial Intelligence, ChatGPT, chat gpt, GPT-4, gpt4, content marketing, Content Marketing, SEO, Search Engine Optimization

The AI might respond with something like:

{
  "AI / Artificial Intelligence": [
    "AI",
    "Artificial Intelligence"
  ],
  "ChatGPT / GPT-4": [
    "ChatGPT",
    "chat gpt",
    "GPT-4",
    "gpt4"
  ],
  "Content Marketing": [
    "content marketing",
    "Content Marketing"
  ],
  "SEO / Search Engine Optimization": [
    "SEO",
    "Search Engine Optimization"
  ]
}

3. Merge, Alias, or Otherwise Clean Up

With the AI’s clustered output, you can decide how you want to handle each group:

  • Merge Tags: Choose a primary label for each cluster (e.g., “AI” for the AI cluster, “ChatGPT” for the GPT cluster, etc.) and merge other tags into it.
  • Create an Alias Column: If your platform supports aliases, you can keep multiple variations of the same tag to catch all possible user searches. For example, “gpt4” and “GPT-4” can both direct users to “ChatGPT / GPT-4.”

This step ensures a smoother user experience since variations (like “AI” and “Artificial Intelligence” or “ChatGPT” and “chat gpt”) no longer scatter your data.

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A few Practical Examples why this matters

  • Avoid Losing Traffic: If someone searches for “gpt4” while all your content is tagged “GPT-4,” AI-driven clustering ensures these variations are consolidated.
  • Simplify Analytics: When analyzing your most popular tags, you want to see the true size of your AI coverage. Without clustering, “AI” and “Artificial Intelligence” might appear as separate categories, splitting your data.
  • Improve Organization: A tidy, consolidated list of tags makes it easier to create curated feeds, filtered sections on your website, or recommended articles.

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Wrap-Up

Leveraging AI for tag clustering is an elegant solution to the age-old problem of tag chaos. It ensures consistency, boosts discovery, enhances SEO, and empowers content strategists to make data-driven decisions. As GPT and similar AI models become more accessible, integrating them into your workflow for organization and clean-up tasks like tag clustering can be a major time-saver and insight-booster.

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