Our qualitative reporting auto-tagging feature streamlines your workflow by automatically tagging your dataset of open-ended comments according to your specified objectives. Whether you're interested in counting brand mentions or analyzing consumer sentiment, Fuel Cycle's AI does the heavy lifting.
Research objectives for AI
To fully harness a tool's potential, establish clear goals. When you use our AI summary feature, you receive both a narrative summary of your data and a summary table that counts the frequency of each tag. This effectively quantifies your qualitative data, providing a clear, measurable outcome for your research objectives. This strong foundation makes our summaries especially powerful, as they are designed to be relevant and specific to your needs.
Research objectives often attempt to accomplish too much, incorporating various stakeholder needs and complex phrasing. However, these types of objectives do not translate well to AI.
When you use our AI summary feature, the summary you receive includes a narrative summary of the data and a summary table that counts the frequency of each tag. This quantifies your qualitative data, providing a clear, measurable outcome of your research objectives. This concrete grounding makes our summaries so powerful — they are relevant and specific to your needs.
Research objectives often try to achieve too much. They are filled with various stakeholder needs and complex sentences. However, these types of research objectives do not translate well to AI. For AI to effectively analyze and summarize your data, develop your objectives according to the "SCRAM" mnemonic: Specific, Clear, Relevant, Actionable, and Measurable.
- Specific—Objectives should be focused on a particular (and narrow) aspect of the research.
- Clear—Vague goals produce vague outcomes. Ensure your objective is clear. If you have to read it twice to understand it, rewrite it!
- Relevant—Your research objective should be suitable to the topic and feasible for data analysis to yield results.
- Actionable—Use action verbs! This is nearly an extension of being clear – instruct the AI explicitly, and it will comply.
- Measurable—Give the AI something to calculate.
With these principles in mind, here are 5 sample prompts to get you started:
Sample Tag Objectives
| Tagging objective | Why it works |
|---|---|
| Analyze each comment's sentiment towards [product or topic] on a scale of Positive, Somewhat Positive, Neutral, Somewhat Negative, or Negative | Giving the AI clear guidance to analyze sentiment about the topic helps keep the tagging focused and relevant. Offering a specific set of sentiment descriptors makes your tag list predictable and easier to manage later on. |
| Identify each retail brand mention. | This tagging objective is specific and actionable, allowing the AI to identify retail brands and count their mentions. Without a predefined tag list, the AI can discover unexpected brands, but it’s important to review the results for accuracy. |
| Identify positive and negative onboarding experiences. | We're looking for the AI to identify and tag onboarding experiences as positive or negative. Following this, we want to categorize the perceived reasons for both positive and negative experiences to capture the full scope of our research goal. |
| Categorize all comments that refer to pricing or cost as a decision-making factor. | This objective's strength is its specificity; an objective like this is useful when you already know that cost will come up in the comments and want to quantify the mentions exactly. |
| Identify comments that did not address [topic / question]. Identify comments that violate [guidelines/rules]. Identify comments that necessitate a moderator response. | Use AI tags to increase your power and efficiency with moderation: give AI specific tasks and only follow-up on comments it identifies for you. |
Final Thoughts
The beauty of AI auto-tagging lies in its ability to quickly sift through large volumes of unstructured data, identifying patterns you might not have noticed otherwise. However, the effectiveness of this tool depends on your tagging prompt clarity. The more specific and aligned your prompt is with your goals, the more valuable the tags generated by the AI will be.
If you have a great prompt idea you would like to share or need some help fine-tuning your objectives, please let us know. Our team is here to help you get the most out of your AI-powered analysis.