Displayr contains all the tools required to check and clean your survey. You can manually clean your study, working from variable to variable, or automate the entire process – whatever works best for you.
Displayr offers powerful text analysis tools that seamlessly blend human insights with AI and machine learning, making it effortless to uncover meanings in verbatims and social media data.
With a couple of mouse clicks, create summary tables of all your data.
Displayr has special-purpose visualizations for finding patterns in missing data and a great Sankey plot visualization for checking questionnaire routings.
Displayr can automatically hunt through your data finding all the standard problems: missing labels, missing data problems, flatlining, outliers, and categories that are so small that the categories need to be merged.
There’s no need to write code or go into a complex dialog box to merge categories. Just drag and drop. Or use advanced automation techniques to merge large quantities of data at the same time automatically.
Do all the standard recoding with the click of a button (e.g., NPS, top 2 boxes, etc.)
Have a new wave of data? When you import it in, all your data checking and cleaning will be automatically applied for you, without you having to do anything. Even your final report will be updated automatically, making it easy to go back and fix things.
Does your company have a standard way that it always does its cleaning and checking? You can entirely automate this process for new studies.
No matter what analysis you have done, you can always work out exactly how it was created and what data cleaning was done, tracing your way back to the raw data.
Founder, MAC Research
SQL, databases, Excel, CSV, text, SPSS, survey platforms, APIs, integrations, & more.
Summary tables, crosstabs, pivot tables, regression, text analysis, segmentation, machine learning, & more.
Data visualization, interactive data apps, dashboards, presentations, PowerPoint, Excel, PDF, web pages, & more.
AI automatically identifies and categorizes themes within your text data, providing deeper insights.
Understand and analyze complex emotions like frustration and sadness, helping you understand customer motives.
Extract key entities like names, places, and organizations to enrich your analysis.
Fine-tune and adjust categories to match your specific needs and preferences.
Create stunning word clouds, charts, and dashboards that help tell the story behind your text.
Analyze text data in any language, with true native language support to a global audience.
Analyze large volumes of text to gauge positive, negative, or neutral sentiments.
Extract insights with unrivalled accuracy, utilizing NLP to reduce manual effort and free up time.
Displayr helps Lewers cut reporting and analysis time by 2/3rds
Some typical examples of conjoint include:
Conjoint analysis is a quantitative research method.
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