{"id":1096996,"date":"2026-07-23T03:46:48","date_gmt":"2026-07-23T10:46:48","guid":{"rendered":"https:\/\/www.questionpro.com\/blog\/?p=1096996"},"modified":"2026-07-23T03:47:20","modified_gmt":"2026-07-23T10:47:20","slug":"text-analysis-surveys-questionpro-bi","status":"publish","type":"post","link":"https:\/\/www.questionpro.com\/blog\/text-analysis-surveys-questionpro-bi\/","title":{"rendered":"The slowest data in your survey just got fast: AI text analysis"},"content":{"rendered":"\n

Your open-ends deserve better than a coding spreadsheet<\/strong><\/h2>\n\n\n\n

Your survey’s open-ended answers carry the “why” behind every score. Now they get read as fast as the numbers.<\/em><\/p>\n\n\n\n\n\n

Your open-ends hold the answer. Reading them by hand is the problem.<\/strong><\/h3>\n\n\n\n

You asked one open-ended question. Six thousand people answered it. Now you have a folder of free text, a coding sheet, and a readout due Monday.<\/p>\n\n\n\n

This is the oldest trade-off in research. The open-ended answers carry the richest signal. They also take the longest to make sense of. Closed questions give you the score. The comments tell you why the score moved. Getting to that “why” has usually meant hours of manual coding, or quietly cutting the open-ends from the report to save time.<\/p>\n\n\n\n

TextAI, the advanced text analysis<\/a> module inside QuestionPro BI, takes that trade-off away. It reads open-ended responses with AI, groups them into themes you can trust, and shows them on the same dashboard as your numbers.<\/p>\n\n\n\n

Learn More:<\/strong> QuestionPro text analysis software<\/a><\/p>\n\n\n\n

What text analysis in QuestionPro BI does<\/strong><\/h3>\n\n\n\n

TextAI takes the free-text answers from your survey and turns them into structured, countable themes. You get topic modeling that surfaces the recurring ideas in the data, sentiment scoring<\/a> that reads each comment as positive, negative, or neutral, and a set of widgets, word clouds, sentiment charts, topic and sub-topic stacked bars, that make the patterns visible at a glance.<\/p>\n\n\n\n

It runs on QuestionPro AI<\/a>, the same AI that works across the platform. That matters for one reason. The text analysis is not a bolt-on. It reads your responses inside the tool where your data already lives, so there is no export, no third-party uploader, and no reformatting step between collecting answers and understanding them.<\/p>\n\n\n\n

QuestionPro AI does the sorting, you keep the judgment<\/strong><\/h3>\n\n\n\n

Good qualitative work is not “let the machine decide.” It is a fast first pass from AI, checked and shaped by a person who knows the study. TextAI is built that way.<\/p>\n\n\n\n

A codebook shaped around your study<\/h4>\n\n\n\n

A codebook is the set of themes and sub-themes used to classify your responses. When you build an Advanced Text Analytics dashboard, you can let QuestionPro AI generate the codebook<\/a> from your actual response data. You can also upload a code frame you already use, or reuse the codebook from an earlier report so a tracker stays consistent wave over wave. You add a short line describing your objective and a note of context per question, and the themes come back sharper because the AI knows what you are looking for.<\/p>\n\n\n\n

Theme configuration, where you stay in control<\/h4>\n\n\n\n

Once the themes are generated, you are not stuck with them. In theme configuration<\/a> you can create a new theme, merge two sub-themes that describe the same idea, tag individual responses by hand, remove a tag that does not fit, then recode the dataset to apply your edits. This is the part that separates a serious research tool from a novelty. The AI gets you most of the way in minutes. You decide the rest.<\/p>\n\n\n\n

The advantage of analysis that lives next to your numbers<\/h3>\n\n\n\n

Here is what a standalone text tool cannot do. Because TextAI sits inside QuestionPro BI, your themes and your closed-ended data share one dashboard. You can filter the open-ended themes by any segment in your study, region, age, customer tier, and watch the story change. Data slicers and stat testing<\/a> then flag where a difference between groups is real and not noise. A theme stops being a quote you liked. It becomes a measured share of voice you can compare, track, and defend in the room.<\/p>\n\n\n\n

A worked example: a UK bank reads its CX comments<\/strong><\/h3>\n\n\n\n

Say a UK bank runs a quarterly CX survey and asks customers to explain their score in their own words. It collects nine thousand comments. QuestionPro AI generates a codebook, and the themes come back: app reliability, branch wait times, fee clarity, call centre handling. Sentiment scoring shows fee clarity running strongly negative. The team drops “fees” into a filter and sees that negative feeling concentrated in one customer segment. Stat testing confirms the gap is significant. What used to be a two week coding job is a same day finding the team can act on before the next release.<\/p>\n\n\n\n

Setup takes minutes<\/strong><\/h3>\n\n\n\n

Starting a text analysis dashboard is a short, guided flow. You open bi.questionpro.com, choose TextAI, pick the survey with your open-ended responses, name the industry, and write one line describing your goal. Select the questions to include, add a note of context for each, and hit create. QuestionPro AI processes the responses and builds the themes for you. There is no setup workshop to sit through and no query language to learn. The full step-by-step guide<\/a> is in the help centre. If you can write a survey, you can run this.<\/p>\n\n\n\n

Get started<\/strong><\/h3>\n\n\n\n

Your open-ended answers are already sitting in your surveys, carrying the reasons behind every number you report. Reading them should not be the slow part anymore. Create a free QuestionPro account, point TextAI at an open-ended question<\/a>, and watch the themes build themselves in minutes.<\/p>\n\n\n\n

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