Displayr Adds Reusable AI-Based Charting

Displayr has upgraded its charting offer with AI-based design and build of custom, reusable data visualizations from a user's description. Researchers can now build brand health funnels with significance-tested conversion rates, grid cartograms, and charts with images scaled to the data.

Displayr provides all-in-one analysis and reporting software purpose-built for survey data, and connects it with analysis, visualizations and reports. The platform already includes a Research Agernt, which automates the production of a full report from raw survey data; and a solution called Skills, which allows clients to encode their own unique research methods and choice of approach directly into its platform, to ensure they are applied correctly by anyone running a project, every time.

With the latest addition, the firm's AI can now write the code for a chart into a document, where researchers can read it and edit it using a table in the document rather than a static copy of the data. Filters, weights and rules apply to it, and researchers specifying up front how it should handle new categories and missing values. Charts can be saved as templates for the whole team to reuse; work in Displayr dashboards and reports; and export to PowerPoint as images.

'I kicked off project after project to get our developers to build a brand health conversion funnel,' says CEO and co-founder Tim Bock (pictured), 'and I cancelled every one of them because the engineering cost was too high. This time I built it myself by describing what I wanted. A reusable custom chart used to mean many months of developer time. Now it's minutes to hours.' The new feature should prove cost-effective against GenAI usage - Bock notes: 'The AI isn't drawing the chart. It writes the code that draws it. Once that code exists, the chart runs on its own, with no AI and no tokens. Ask a general AI assistant to redraw the same chart, and you pay again every time, even to change a color.'

Web site: www.displayr.com .

All articles 2006-23 written and edited by Mel Crowther and/or Nick Thomas, 2024- by Nick Thomas, unless otherwise stated.