Topics

Topics help you identify recurring themes across your survey feedback so you can understand what users talk about most, detect friction earlier, and prioritize product decisions with more confidence.

Instead of reading every response one by one, Screeb groups tagged survey responses into clear subjects such as UX issues, missing information, bugs, feature requests, pricing concerns, onboarding, and more

What are Topics used for?

Topics help you:

• Identify the most frequent subjects in user feedback
• Spot recurring pain points and frustrations
• Detect feature requests and emerging needs
• Track how topics evolve over time
• Measure the impact of product changes or releases
• Share feedback trends more easily across teams

Topics are especially useful when you want to move from raw responses to a clearer view of what matters most to users.

Where to find Topics

To access Topics:

1. Open the left-hand menu
2. Go to Analyze
3. Click Topics

From this page, you can explore the list of detected topics for the selected period and filters.

Before you start

Topics require tagged survey responses.

If no tags are applied to your survey responses, Topics cannot group feedback into subjects.

Also, when tags are created or updated, Screeb re-analyzes past survey responses automatically. This means old feedback may take some time to appear in Topics after changes are made.

How Topics work

Topics are always based on tags.

Each topic represents a tag found in survey responses during the selected period. A single survey response can belong to multiple topics if it has multiple tags.

Supported tag types

Screeb Topics can include all tag types:

• Manual tags: tags applied manually from the UI
• Automatic tags: tags assigned when defined keywords are detected
• Smart tags: tags assigned by AI based on response content

This means Topics can reflect both manually reviewed feedback and automatically classified feedback.

How to configure Topics

Topics depend on your workspace Tagging settings.

To configure the tags used in Topics:

1. Go to your workspace settings **then **survey - tagging
2. Configure your tags
3. Set up Automatic Tagging and/or Smart Tagging if needed
4. Save your changes
5. Wait for Screeb to analyze existing feedback

Once tags are configured and applied to survey responses, they automatically feed the Topics page.

Configure Automatic Tagging

Automatic Tagging lets you define keyword sets and assign one or more tags when those keywords are detected.

For example, you might define a keyword set such as:

• “slow”
• “lag”
• “loading”
• “takes forever”

And assign tags such as:

• bug-slowness
• performance

When a survey response matches those keywords, Screeb applies the related tags automatically.

When to use Automatic Tagging

Automatic Tagging is useful when:

• You already know the terms users often use
• You want predictable tag assignment rules
• You need a fast way to classify repeated issues

Configure Smart Tagging

Smart Tagging lets you define the tags you want to use, and Screeb AI decides when to assign them based on the content of each survey response.

For example, you can define tags such as:

• missing-information
• feature-request
• pricing
• onboarding

Screeb then analyzes the response content and applies the most relevant tags automatically.

When to use Smart Tagging

Smart Tagging is useful when:

• Users describe the same issue in different ways
• Exact keyword matching is too limited
• You want broader and more flexible topic detection

How to read the Topics table

Each row in the Topics table represents a topic detected across tagged survey responses.

Topic

The name of the detected subject, based on a tag.

Examples:

• missing-information
• ux-layout
• feature-request
• pricing
• bug-slowness

Volume

The number of survey responses associated with the topic during the selected period.

A higher volume means the topic appears more often in feedback.

Topic Share

The percentage of analyzed survey responses that are associated with this topic.

For example, if a topic has a share of 29%, it means that nearly one in three analyzed responses includes that topic.

Evolution

The change in topic share compared with the previous period.

This helps you understand whether the topic is increasing, decreasing, or staying stable over time.

Positive Share

The percentage of responses associated with the topic that have a positive sentiment.

This is based on Screeb sentiment analysis.

Negative Share

The percentage of responses associated with the topic that have a negative sentiment.

This is also based on Screeb sentiment analysis and helps reveal which topics may represent stronger user pain points.

Open a topic to explore details

When you click a topic, Screeb opens a chart view for that topic.

This detail view helps you understand how the topic performs across your selected filters and time period.

The chart can be explored using filters such as:

• Date
• Survey response filters
• Respondent properties
• Events

The topic detail view displays:

• Number of responses
• Positive feedback rate
• Negative feedback rate

Filters in Topics

Both the Topics table and the topic detail view are affected by filters.

This means you can refine your analysis at both levels using:

• Date filters
• Survey response filters
• User tracking filters such as properties and events

Using filters helps you focus on a specific audience, timeframe, survey scope, or behavioral context.

How to use Topics to prioritize product actions

Topics help teams identify where to investigate first and where product changes may have the biggest impact.

Identify major pain points

Look for topics with a combination of:

• High volume
• High negative share
• Strong growth over the previous period

These are often the clearest signals of urgent product friction.

Track the impact of a release

After a release or product update, monitor related topics over time.

For example, if you improve onboarding, navigation, or content clarity, you can watch whether topics such as missing-information, ux-layout, or onboarding decrease afterward.

Detect product opportunities

Some topics may reveal repeated expectations or unmet needs, such as feature requests or repeated confusion around an existing workflow.

These signals can support roadmap discussions, product discovery, and future research.

Share insights across teams

Topics make it easier to summarize what users are saying and align teams around the most important feedback trends.

This can help Product, Design, Support, Customer Success, and Leadership work from the same feedback signals.

Example use case

A product team notices that missing-information has:

• High topic share
• High negative share
• Stable growth over several periods

This may indicate that users cannot find the information they need at the right moment in their journey.

The team can then:

1. Review the related survey feedback
2. Identify where information is unclear or missing
3. Improve help content, labels, onboarding steps, tooltips, or in-app guidance
4. Monitor the topic again after the change is released

If the topic share and negative share decrease over time, this may indicate that the change reduced friction.

Best practices

To get the most value from Topics:

• Make sure survey responses are tagged consistently
• Use a meaningful analysis period
• Compare trends over time rather than looking at a single snapshot
• Combine volume, evolution, and sentiment when prioritizing
• Use filters to isolate the right audience or context
• Remember that one response can belong to multiple topics
• Allow time for re-analysis after updating tags

Things to keep in mind

• Topics only work with survey responses
• Topics require tagged responses
• Updating tags triggers a replay of existing feedback
• Reprocessing older responses can take time
• Results update automatically once analysis is complete
• Topic sentiment metrics rely on Screeb sentiment analysis

Key takeaway

Topics help you move from raw survey feedback to clear thematic insights.

By structuring responses with tags and analyzing volume, share, evolution, and sentiment, Screeb helps you understand what users are talking about, what causes friction, and where your team should focus next.

Updated on: 29/04/2026