Depends. Usercall focuses on providing users with simple and powerful AI tools to both gather and analyze qualitative data. There are many tools that provide qualitative data analysis like Dedoose, Atlas, Nivivo, QDA Miner and others that provide a range of coding features. However, many of these tools are outdated with difficult user experiences and lack the ability to accelerate research leveraging the latest AI & LLM models and agentic AI capabilities that Usercall AI  offers.

To properly do qualitative analysis, researchers and product teams often need to manually review hand written notes, transcripts and other data from participant data and 'tag' or code specific excerpts to organize and find patterns from what people said. This is a time consuming and laborious process that AI can effectively accelerate without compromising on quality.

For example, if a researcher conducted 10 user interviews, the resulting transcripts can be uploaded to an AI qualitative analysis tool like Usercall—and it will go through each transcript line-by-line to code patterns and larger themes that researchers can then refine and analyze. This saves hours to days of work for researchers while giving them control over how to analyze and find patterns in the data.

Researchers, PM's and UX professionals can use Usercall AI for various parts of their research needs—from quickly gathering qualitative user feedback to analyzing large sums of qualitative data from participants.

For example, dozens of user interview, focus group or open ended text responses in txt, csv or similar formats can be uploaded to the tool to automatically generate tags and themes with detailed summaries and excerpts. From this data, interactive charts such as frequency analysis, thematic coding and AI chat features allow for deep pattern finding and insights. It's like having a highly specialized AI research assistant by your side to help you better analyze and extract deep insights from your research.