From text data to
brilliant insights...in
a fraction of the time

Displayr has all the tools to help you quickly
and accurately categorize and analyze text
(plus handy updating features as well).

Book a free demo of Displayr

Text coding in a fraction of the time

Quickly transform text
to data

Of course, Displayr has all basics for text analysis, from manual coding to word clouds to sentiment. But if you have a just a little more time, our state-of-the-art guided machine learning tool will help you quickly categorize text with the level of accuracy previously only achieved with manual coding.

And if you don’t have time, use automatic categorization to instantly summarize your text into themes.

Semi-automatic text categorization means more accurate results

Categorize text in ¼ of the time, without sacrificing accuracy!

Displayr’s machine learning algorithms can be easily trained to understand the nuances in your own specific text data. Just code up a portion of your text and then let Displayr take over. Expect accuracy levels previously on possible with manual coding but done in a quarter of the time!

Automatic Text Categorization

Automatic categorization

For a fast way to summarize text into categories, or code brand lists and extract entities, Displayr has purpose-built algorithms and text visualizations that will get you there instantly.

Auto-update text data

Keep the flywheel in motion with auto-updating

When you have new data, Displayr will automatically update your text categories with the new text, along with any report or dashboard associated with it – instant and error free, saving you hours!

Text analysis

Easily squeeze every brilliant insight from your text data. Once you’ve categorized your text, Displayr treats it like any other variable in your data set. So you can automatically test for significance, crosstab with other variables, use it in multivariate analyses or create visualizations and interactive dashboards.

"A dashboard that would've taken a week to do previously
is now ready in two days.

Michelle Mercer, Lewers Research

Read Michelle’s story

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