Connect open-text feedback with scores, segments, and outcomes
AddMaple keeps open-text columns in the same project as the rest of the survey. Code comments into themes, then pivot, filter, and run stats against NPS, satisfaction, segments, demographics, and outcomes using the same banners you use elsewhere.
This guide assumes your dataset includes at least one open-text column and structured columns such as scores, segments, demographics, choices, or outcomes.
Get oriented in the full dataset
From the Chart Dashboard, identify the columns you want to connect:
- The open-text column you want to analyze.
- The score, segment, or outcome columns you want to compare it with.
Check column types—the open-ended response should usually be Text; NPS, CSAT, likelihood scores, groups, departments, regions, or customer types should appear as numeric or categorical columns. If the text column is not detected correctly, change its type before coding.
See Exploring your data for the broader exploration workflow.
Turn open text into a usable analysis column
Open the text column and use AI Coding / Tagging to create a structured column from the comments.
Choose the approach that matches your question:
- Thematic coding — topics such as pricing, support, product quality, culture, or onboarding.
- Topic-based sentiment — whether each topic is discussed positively, neutrally, or negatively.
- Your own code frame — standard categories for a tracker, client project, or employee listening program.
Keep the first pass focused. Too many themes at once are harder to review. See How to analyze text data thematically or categorically with AI, Thematic Coding (Iterative), and Topic-Based Sentiment Analysis.
Review the coding before comparing it
Before treating themes as results, check a sample of row-level evidence in View text and codes—wrong theme assignments, overlapping themes, missing themes, or excerpts that do not match the code.
You do not need perfect coding before exploring; catch obvious issues so themes are good enough to compare with the rest of the dataset. If you add a new code during review, use the iterative workflow to apply it where relevant. See Thematic Coding (Iterative).
Compare themes with scores and segments
Once coding is complete, AddMaple creates a new column for your coded themes. Explore it like any other column:
- Pivot themes by a score group — NPS groups, satisfaction levels, engagement scores, or other rating columns.
- Pivot themes by a segment — customer types, regions, teams, roles, age groups, or channels.
- Filter to one theme — the rest of the project updates so you can see who mentioned it, what they scored, and how they answered other questions.
- Filter to one score or outcome — detractors, churned users, unhappy employees, or another outcome group, then inspect which themes are most common in that audience.
See Exploring your data for filtering, pivots, and subgroup exploration.
Related columns and stats on coded themes
Related columns shows which other columns are most strongly connected to a coded theme column—useful for spotting a complaint theme concentrated among low scorers, a feature request in one segment, or a support issue linked to renewal risk.
Review the chart, base sizes, and underlying comments before deciding what belongs in the deliverable. See Exploring Related Columns, Statistical Calculations, and Key Driver Analysis.
Trace findings back to verbatims
When a theme looks connected to a score, segment, or outcome:
- Filter to the theme.
- Add the score, segment, or outcome filter you care about.
- Open the row-level view.
- Read verbatims and highlighted excerpts.
- Save the clearest examples for your report, dashboard, or client readout.
Add connected findings to a deliverable
Once you have a theme, comparison, and supporting verbatims, add the chart to a dashboard or Insight Hub. For output-specific steps—deck vs hub vs explorable—see Turn findings into client-ready outputs and Share with clients.
Example workflows
NPS or customer satisfaction — code the "Why did you give that score?" response, pivot themes by NPS group, filter to detractors or low scorers, review verbatims for standout themes, add the strongest pattern to a dashboard.
Employee listening — code comments into themes such as workload, management, recognition, or communication; pivot by team, location, tenure, or engagement score; check whether a theme is broad or concentrated in one group.
Reviews and support feedback — code comments or tickets into themes and sentiment, connect to account type, product area, or region, filter to high-impact themes, inspect original text.