Imagine what it would be like to sit down with all of your customers at the same time, ask them the questions you need answers to, and get real-time qualitative responses from everyone at the same time.

Of course this is impossible to do in a human moderated interview or focus group. But, with improvements in artificial intelligence and machine learning, this type of data collection and qualitative reporting isn’t far off base.

In fact, machine learning is advancing at a rate that now it’s possible for machines to quickly automate qualitative research tasks that were once only tedious manual human tasks. These tasks include things like:

  • Theme discovery
  • Quick data filtering
  • Qualitative coding
  • Advanced search
  • Robust filtering capabilities
  • Real-time customer feedback reporting
  • And more!

When you invest in smart market research tools, the ability to collect better qualitative data and experience quick qualitative reporting becomes a reality.

What does Fuel Cycle have to do with better qualitative reporting?

This is where Fuel Cycle enters to make an exciting announcement. Fuel Cycle has just released an awesome machine learning Qualitative Reporting feature that makes it possible to analyze unstructured data in a flash.

Here are some of the features to get excited about:

  • Theme Discovery. Qualitative discussion data is automatically analyzed by machine learning algorithms and tagged with keywords and entities that you can use to filter and group data by inside the platform.
  • Manual Tagging. Along with automated theme discovery, you can manually tag data for quick grouping and filtering of qualitative data.
  • Sentiment Analysis. Get a real-time view of attitudes and opinions with sentiment analysis at both the response and keyword level.
  • Advanced Search & Filters. One-click filtering on keywords, entities and tags allows you to instantly see all data based on a particular theme. Use search to find data based on a custom search term and tag all results instantly for quick coding.
  • Saving and Exporting. Save a full or partial response to help expedite the reporting process. Export data as a PDF or Excel file at any time whether viewing all responses, search results or saved responses.

How does it work?

It’s nice to know what you’re getting with Qualitative Reporting from Fuel Cycle, but you also may be wondering how it actually works.

The first step is to run a discussion activity inside the Fuel Cycle community. This helps you get responses to your research question. As responses are posted, the data is analyzed by machine learning algorithms.

You can then view data at any time during or after a project to discover themes and insights. The tool will also revealsentiment data so you can see attitudes and opinions in real-time.

Finally, you can save full or partial responses and export data as PDF or Excel for quick report building.

This speeds up the process of analyzingqualitative data, so you can get those business insights you need at lightening speed.

Wrap Up

You already know the importance of qualitative data. It gives you deep insights directly from your customers about what they like, what they need, what they want, and what is and what is not working for them.

Now, with the help of machine learning, you can get these insights quicker than ever before from a wider audience. New tools like Qualitative Reporting from Fuel Cycle will help you stay ahead of the game in terms of direct, qualitative, customer feedback.