Struggling to choose between consider.ly and NVivo? Both products offer unique advantages, making it a tough decision.
consider.ly is a Business & Commerce solution with tags like feedback, research, surveys, interviews, analytics.
It boasts features such as Create surveys to collect quantitative feedback, Conduct 1-on-1 interviews to gather qualitative insights, Collect NPS scores to measure customer satisfaction, Analyze results and feedback to inform product decisions, Integrations with tools like Slack, Jira, etc, Customizable and branded surveys, Schedule and automate surveys and pros including Easy to create and send surveys, In-depth qualitative feedback from interviews, Quantitative data from surveys, Powerful analytics and reporting, Integrates with existing workflows, Customizable and on-brand.
On the other hand, NVivo is a Office & Productivity product tagged with qualitative-analysis, coding, transcription, interviews.
Its standout features include Import and analyze text, audio, video, emails, images, spreadsheets, Code and find themes in qualitative data, Annotate and highlight important passages, Visualize data through charts, maps and models, Collaborate with team members, Integrates with statistical analysis tools like R and Python, and it shines with pros like Powerful tools for qualitative analysis, Flexible importing and visualization, Collaboration features, Integrates with other analysis tools.
To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.
consider.ly is a feedback and product research platform that allows product teams to collect insights from customers and users. It provides features to create surveys, conduct 1-on-1 interviews, collect NPS feedback, and analyze results to inform product decisions.
NVivo is qualitative data analysis software used by researchers to organize, analyze and find insights in non-numerical or unstructured data like interviews, open-ended survey responses, articles, social media and web content. It allows you to import, classify, code and visualize various data types.