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Automatic Tagging

This guide explains how to use Genway’s Automatic Tagging feature. A semantic tagging tool that helps you find, cluster, and analyze specific information across large interview datasets.

Moshe Salamon avatar
Written by Moshe Salamon
Updated over 2 weeks ago

Step 1: Explore the Tags Feature

Start by opening the Tags section in Genway. This advanced feature enables you to create Tag Groups and Tags tailored to your specific research needs.

Each tag can represent a concept, theme, or keyword that you want the Genway to track across all interviews. Tag groups help you organize related tags into categories for easier management and visualization.

Step 2: Define What You Want to Find

Use Genway’s proprietary semantic mechanism to describe what you want to identify within your dataset.
Instead of manually searching for keywords, simply describe your intent and Genway will understand what to look for.

For example:

  • To find all competitors mentioned in Netflix interviews, type a query such as “Competitors of Netflix.”

  • Genway will then scan all interviews using semantic search, not just keyword matching, and relate relevant quotes to your tags.

Step 3: Run the Auto-Tagging Process

🎥 [Video Placeholder – Running Auto Tagging]

Once your tags are defined, initiate the Auto Tag Interviews process. Genway will:

  1. Analyze the entire dataset.

  2. Identify and tag all relevant responses or quotes.

  3. Display clusters of related content based on your query.

Because the tagging uses semantic relationships, it doesn’t rely on exact phrases — it understands meaning and context.

Example: If you ask Genway to find “Netflix competitors,” it might surface quotes mentioning Disney+, HBO Max, Hulu, or Amazon Prime Video — even if you didn’t list them.

Step 4: Review and Understand Results

🎥 [Video Placeholder – Reviewing Tagged Results]

Once the auto-tagging process completes, you’ll see your results visualized and organized by tag group.
Each tag includes linked quotes and context showing why the AI associated that piece of data with the tag.

You can click any quote to see:

  • The full transcript context.

  • The logic behind why it was tagged.
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  • Related tags that share similar meaning.

You can refine your analysis by editing or adding new tags to explore additional themes.
Add custom tags to capture emerging topics or adjust existing tag queries to focus on specific contexts.

This iterative tagging process helps you refine your research focus over time, making your insights progressively sharper and more meaningful.

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