Best Qualitative Data Analysis Software for Cloud - Page 3

Our systems intelligently gather a variety of high quality unstructured data streams across hundreds of sources, in the form of text, voice, images and videos. Our systems clean this data and are trained to extract signals across products, services, attributes, brands, sentiments, customers, markets, and trends. It gets synthesized and contextualized using our proprietary Deep Product Learning ® technology. Use our enterprise-grade integrations to ingest your private data. Assess and benchmark your view of your products and services with the competitive landscape. Our platform delivers powerful AI-driven actions where you need it - dashboard, APIs and integrations - and turn insights into action, across PIMs, CRMs, voice assistants, chatbots, and more.

Make better product decisions 5x faster. Find the signal in the noise - BuildBetter's proprietary Signal Engine powers everything from search to extractions, organizing, and summarizing your qualitative data. Find 78% more insights from your customers with existing data compared to teams using manual product research tools. A quantum leap in qualitative analysis. Save on average 200 hours a year on organizing insights from your customers into topics, themes, problems, and more. Summarizations that are so good it almost feels like cheating. Whether it's a summary of a call, a topic, a feature request, and anything else BuildBetter can process, we can turn it into sharable insights. Internal, external, and everything in between. BuildBetter's proprietary Call Intelligence powered by Signal Engine allows you to track and analyze every call that comes into your product team.

WizWhy determines how the values of one field in the data are affected by the values of other fields. The system performs its analysis based on one field selected by the user as the dependent variable, while the other fields are the independent variables (or conditions). The dependent variable can be analyzed as either Boolean or continuous. The user can fine-tune the analysis by defining parameters such as the minimum probability of the rules, the minimum number of cases in each rule and the cost of a miss vs. the cost of false alarm. WizWhy reveals and lists the rules that relate between the dependent variable and other fields (conditions). The rules are formulated as if-then and if-and-only-if statements. On the basis of the discovered rules WizWhy points out the main patterns, the unexpected rules (interesting phenomena) and the unexpected cases in the data. WizWhy can issue predictions for new cases on the basis of the discovered rules.