Accelerating Qualitative Analysis with Tetra Insights

How a professional researcher uses Tetra to supercharge user research analysis

Here at Tetra, we love to eat our own dogfood by researching our users, who are researchers themselves! As we continually improve our product with research, we gain deep insight into our user’s effective methods and how they fit Tetra into their processes.

We’ve recently been working closely with a Tetra power user named Tim, a User Experience Researcher at a global technology company, to understand why he so heavily depends on Tetra to effectively analyze and generate insights from his qualitative research. Below we outline Tim’s processes which save time and produce better, more actionable analyses for his team. 

Background

As any researcher knows, quickly and effectively processing and analyzing qualitative data is no easy task. It can be one of the most time consuming aspects of working with qualitative data and it faces unique challenges to properly complete and produce the best insights, especially when dealing with up to 10 hours of video content per project. Preparing the analysis, taking notes, summarizing sessions, combining analysis into deliverables, creating video clips, and exporting videos for just one 60-minute interview can often take 2+ hours to complete (the estimated duration for almost 45% of all respondents in our recent Customer Insight Trends & Benchmarks report!)

Tim is a senior member of the research team at a very large research and data company. Since his organization started using Tetra as a primary research tool over the past year, Tim has developed a simple, yet thorough process to effectively analyze qualitative data. His process is paired with his fifteen plus years of experience as a researcher and the powerful capabilities that the Tetra platform offers. 

 

The Process

Tim’s process breaks down nicely, and unsurprisingly, into three key areas of most qualitative analysis processes: coding, analysis, and synthesis. What is distinctive, however, is how he pieces his personal research experience and process within each of those key areas together with Tetra. 

1. Coding

Throughout all phases of analyzing a single project, which often includes up to ten interviews, Tim creates and references a tag library outlining his coding schema. He determines his tags, or codes, with three primary methods: 

A.   Research questions generated by his team and stakeholders lead the initial tag creation. For example, when testing a prototype concept, a “What are users’ very first reaction after being explained the concept?” will turn into a “#FirstReaction” tag in his project tag library. 

B.    The Grounded Theory approach to tagging data guides Tim to “build from the ground up,” generating tags from the data while analyzing. The basic principles of this approach turn data into codes, then codes into categories or themes. This approach allows the data to organically contribute to the ultimate insights, without limiting the analysis focus to hypotheses and preconceived ideas. 

C.    A standard list of tags from years of experience also make it into his tag library, for example, #Confusion, #Excitement, and #Question.

Tim tags with a thoughtful blend of preparation, refinement, and experience. Incorporating each of these methods into his process allows him to ensure he’s capturing the specific research goals, opening his mind up to all possibilities with the data, and working most efficiently throughout the process.

2. Analysis

In the analysis phase, Tim’s screen setup with his tools may seem trivial, but is actually quite conducive to ensuring he annotates most productively. Tim positions the Tetra analysis page on the left two thirds of his screen and a Word document with his tag library on the right third of the screen for reference. 

Analysis Page Set Up - Accelerating Qualitative Research - Tetra Insights

This screen setup allows him to have access to the most important information all at once. Within Tetra, he has the transcript, the video, the annotations and tag bank, and then his tag library to guide him throughout the process.

From there, it’s quite simple. Tim always starts with his #FirstReaction tags, generating the entire first reaction annotation for full context and also creating a shorter version of each first reaction, #FirstReactionClip, for use when generating a highlight reel of first reactions across all interviews.

As Tim continues tagging and annotating through the first interview, he adequately ensures that he:

  • Captures all of the planned and key questions from his team and stakeholders with the tags generated from his tag library prep.
  • Adds tags that develop organically from the Grounded Theory approach.
  • Avoids duplicating, renaming, or rewording any preexisting tags within his project — a huge help when in the synthesis phase — with additional assistance from Tetra’s tag autocomplete. 
  • Keeps an eye out for new data and ideas that aren’t already within his tag library.
  • Includes a brief description or context of the tag within the Tetra annotation, making his insight synthesizing easier in the next step. 

 

Annotation and Tag Example - Accelerating Qualitative Research

He then repeats this process with all interviews in the project, expertly annotating and tagging with consistency to ease and improve synthesis and reporting. 

3. Synthesis

Last up, synthesizing, or turning your analysis into insights, is one of the most painstaking parts of any traditional research process. With Tetra, Tim sets himself up to efficiently and effectively gather and share his insights in the form of highlight reels. As Tim enters this phase, he is prepared to take advantage of the most critical capabilities that Tetra offers. 

Synthesis Page - Accelerating Qualitative Research

On Tetra’s synthesize page, Tim has a quick reference of all existing tags within his project. He utilizes this tag list for various cases:

  • To quickly verify that he has captured all of the tags that cover the critical project research questions.
  • To easily report high level data about the interviews, for example, six out of ten interviewees had a positive spin to their first reaction, while the four others were negative or neutral.
  • To instantly scan annotations within tags to promptly reference and speak intelligently about the research during meetings and prior to final report completion. 
  • To skillfully pull key insights from tags and annotations into reports for more accurate and methodical report generation. 
  • To directly combine clips and share powerful highlight reels that make the lasting and true impact of qualitative data!

This last phase brings everything together and offers genuine confidence in the results of qualitative data.  

 

Conclusion

Before Tetra, Tim never had the time to form compelling highlight reels — it just wasn’t feasible. Now, with Tetra, Tim not only knows he’s truly pulling the most out of his qualitative research, but also sees how his stakeholders understand the true value in highlight reels and continually desire more and more as they focus on making the best decisions for their consumers and business.

Overall, Tim achieves the most possible from his qualitative data by combining his research expertise with the compelling capabilities of Tetra Insights. The full process, from tagging to analyzing to synthesizing, is completely streamlined and reliable, and makes Tim’s distinctive steps and Tetra’s capabilities invaluable to generating true and powerful insights at his organization. 

Even more, we’ve learned from Tim and are currently working to further simplify his process by adding new features within the application around tag creation and management. Our ultimate goal is to empower people to reach the most robust and influential insights as quickly as possible, and we’re making updates everyday to ensure this is achievable. 

Curious how you can adapt your process to achieve the most effective and efficient results and insights through qualitative data analysis with Tetra? Reach out and we’ll happily discuss! 

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