Creating your first charts

Charts in Formbricks are not built on survey responses. They are built on Feedback Records, which is why a brand-new workspace shows an empty Analysis page even when your surveys already have hundreds of responses. This guide walks the whole path once: from the NPS template to a dashboard your team can read at a glance.

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Responses and Feedback Records

A survey response is one submission of one survey. It lives with that survey, keeps the exact shape of the questions you asked, and is the right thing to read when you want to see what a single person said. A Feedback Record is one answer to one question, rewritten into a shape that is the same for every source. Each record carries when it was collected, which source it came from, what kind of question it was (nps, csat, rating, text, …) and the answer itself. One response becomes several records - one per answered question. That normalization is what makes records reportable:

• One shape across sources. NPS from a survey, a CSV upload, or the API all become nps records, so a single chart can cover all of them.
• Measures that know what a score means. Because the record is typed, Formbricks can offer NPS: Score, CSAT: Score or NPS: Detractors as ready-made measures instead of asking you to build the math yourself.
• Comparisons across surveys. Two surveys pointed at the same dataset can sit on the same chart and the same time axis.
• Enrichment. Open text is scored for sentiment and emotion as it arrives, which gives you dimensions you never asked a question about.

Creating records never changes or deletes your responses. The response stays exactly where it was; a record is an additional, chart-friendly copy.

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What you need before your first chart

Three things have to exist, in this order. Skipping the first is the most common reason Analysis looks broken: Once a source is live, the Feedback Sources page tells you which dataset it writes into. Several sources can feed the same dataset - that is the point.

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Use case 1: An NPS program you can read at a glance

The most common starting point. Create a survey from the NPS Survey template (Surveys → New Survey, search for “NPS”), publish it, collect some responses, and connect it as a source using the steps above. Now open Analyze → Analysis → Charts and click Create chart. You can describe the chart in natural language or build it by hand; the three charts below are built by hand so you can see exactly which controls do what.

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Chart 1: Overall NPS

Your headline number. One value, no dimensions.

• Chart type: Big Number
• Measure: NPS: Score

NPS: Score is the standard calculation - ((promoters − detractors) / NPS responses) × 100 - so the number is comparable to whatever your team quotes today.

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Chart 2: NPS over time

A single score tells you where you are. The trend tells you whether what you did last quarter worked.

• Chart type: Line Chart
• Measure: NPS: Score
• Add time-based grouping: on
  • Field: Collected At
  • Granularity: Month
  • Date Range: This year

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Chart 3: Promoters, passives and detractors

The score hides the shape of your base. A ten-point NPS made of loud promoters and loud detractors is a different business problem from one made of shrugs.

• Chart type: Bar Chart
• Measures: NPS: Promoters, NPS: Passives, NPS: Detractors

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Put them on a dashboard

Go to Analyze → Analysis → Dashboards, click Create dashboard, then Add charts and pick the three charts you just built. Drag and resize the widgets into the layout you want; a dashboard-level Date range filter sits above the grid.

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Use case 2: Why the score moved

The NPS template asks a follow-up question - “can you describe the reason(s) for your rating?” - and those answers land as text records. Enrichment scores each one for sentiment as it arrives, so you can chart the reasons without reading them all.

• Chart type: Pie Chart
• Measure: Responses
• Filter data: Question equals your follow-up question
• Group data → Group By: Sentiment

The filter matters. Without it the chart also counts the NPS number records, which have no sentiment, and roughly half of your pie becomes a “Not enriched” slice. From here, open Analyze → Feedback Data → Feedback Records, filter to the negative comments and read the verbatims behind the slice. See Enrichment for what else is scored.

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Use case 3: One dashboard across surveys

This is where records earn their keep. Add a second survey - a CSAT survey after checkout or a support interaction - and connect it as a second source into the same dataset. Both surveys now produce records on the same time axis, so they can share a chart.

• Chart type: Line Chart
• Measures: NPS: Score, CSAT: Score
• Add time-based grouping: Collected At, Month, This year

Both measures are percentages of a kind, so they read sensibly on one axis: NPS: Score runs from −100 to 100 and CSAT: Score is the share of responses rated 4 or 5 on the 1-5 scale. When relationship-level NPS and transactional CSAT diverge, that gap is usually the interesting part.

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When a chart looks empty

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Next steps